Features of the use of time-frequency distributions for controlling the mixture-producing aggregate

NASA Astrophysics Data System (ADS)

Fedosenkov, D. B.; Simikova, A. A.; Fedosenkov, B. A.

2018-05-01

The paper submits and argues the information on filtering properties of the mixing unit as a part of the mixture-producing aggregate. Relevant theoretical data concerning a channel transfer function of the mixing unit and multidimensional material flow signals are adduced here. Note that ordinary one-dimensional material flow signals are defined in terms of time-frequency distributions of Cohen’s class representations operating with Gabor wavelet functions. Two time-frequencies signal representations are written about in the paper to show how one can solve controlling problems as applied to mixture-producing systems: they are the so-called Rihaczek and Wigner-Ville distributions. In particular, the latter illustrates low-pass filtering properties that are practically available in any of low-pass elements of a physical system.

Frequency Dynamics of the First Heart Sound

NASA Astrophysics Data System (ADS)

Wood, John Charles

Cardiac auscultation is a fundamental clinical tool but first heart sound origins and significance remain controversial. Previous clinical studies have implicated resonant vibrations of both the myocardium and the valves. Accordingly, the goals of this thesis were threefold, (1) to characterize the frequency dynamics of the first heart sound, (2) to determine the relative contribution of the myocardium and the valves in determining first heart sound frequency, and (3) to develop new tools for non-stationary signal analysis. A resonant origin for first heart sound generation was tested through two studies in an open-chest canine preparation. Heart sounds were recorded using ultralight acceleration transducers cemented directly to the epicardium. The first heart sound was observed to be non-stationary and multicomponent. The most dominant feature was a powerful, rapidly-rising frequency component that preceded mitral valve closure. Two broadband components were observed; the first coincided with mitral valve closure while the second significantly preceded aortic valve opening. The spatial frequency of left ventricular vibrations was both high and non-stationary which indicated that the left ventricle was not vibrating passively in response to intracardiac pressure fluctuations but suggested instead that the first heart sound is a propagating transient. In the second study, regional myocardial ischemia was induced by left coronary circumflex arterial occlusion. Acceleration transducers were placed on the ischemic and non-ischemic myocardium to determine whether ischemia produced local or global changes in first heart sound amplitude and frequency. The two zones exhibited disparate amplitude and frequency behavior indicating that the first heart sound is not a resonant phenomenon. To objectively quantify the presence and orientation of signal components, Radon transformation of the time -frequency plane was performed and found to have considerable potential for pattern classification. Radon transformation of the Wigner spectrum (Radon-Wigner transform) was derived to be equivalent to dechirping in the time and frequency domains. Based upon this representation, an analogy between time-frequency estimation and computed tomography was drawn. Cohen's class of time-frequency representations was subsequently shown to result from simple changes in reconstruction filtering parameters. Time-varying filtering, adaptive time-frequency transformation and linear signal synthesis were also performed from the Radon-Wigner representation.

The use of Matlab for colour fuzzy representation of multichannel EEG short time spectra.

PubMed

Bigan, C; Strungaru, R

1998-01-01

During the last years, a lot of EEG research efforts was directed to intelligent methods for automatic analysis of data from multichannel EEG recordings. However, all the applications reported were focused on specific single tasks like detection of one specific "event" in the EEG signal: spikes, sleep spindles, epileptic seizures, K complexes, alpha or other rhythms or even artefacts. The aim of this paper is to present a complex system being able to perform a representation of the dynamic changes in frequency components of each EEG channel. This representation uses colours as a powerful means to show the only one frequency range chosen from the shortest epoch of signal able to be processed with the conventional "Short Time Fast Fourier Transform" (S.T.F.F.T.) method.

Application of Time-Frequency Representations To Non-Stationary Radar Cross Section

DTIC Science & Technology

2009-03-01

The three- dimensional plot produced by a TFR allows one to determine which spectral components of a signal vary with time [25... a range bin ( of width cT 2 ) from the stepped frequency waveform. 2. Cancel the clutter (stationary components) by zeroing out points associated with ...generating an infinite number of bilinear Time Frequency distributions based on a generalized equation and a change- able

System and method for constructing filters for detecting signals whose frequency content varies with time

DOEpatents

Qian, S.; Dunham, M.E.

1996-11-12

A system and method are disclosed for constructing a bank of filters which detect the presence of signals whose frequency content varies with time. The present invention includes a novel system and method for developing one or more time templates designed to match the received signals of interest and the bank of matched filters use the one or more time templates to detect the received signals. Each matched filter compares the received signal x(t) with a respective, unique time template that has been designed to approximate a form of the signals of interest. The robust time domain template is assumed to be of the order of w(t)=A(t)cos(2{pi}{phi}(t)) and the present invention uses the trajectory of a joint time-frequency representation of x(t) as an approximation of the instantaneous frequency function {phi}{prime}(t). First, numerous data samples of the received signal x(t) are collected. A joint time frequency representation is then applied to represent the signal, preferably using the time frequency distribution series. The joint time-frequency transformation represents the analyzed signal energy at time t and frequency f, P(t,f), which is a three-dimensional plot of time vs. frequency vs. signal energy. Then P(t,f) is reduced to a multivalued function f(t), a two dimensional plot of time vs. frequency, using a thresholding process. Curve fitting steps are then performed on the time/frequency plot, preferably using Levenberg-Marquardt curve fitting techniques, to derive a general instantaneous frequency function {phi}{prime}(t) which best fits the multivalued function f(t). Integrating {phi}{prime}(t) along t yields {phi}{prime}(t), which is then inserted into the form of the time template equation. A suitable amplitude A(t) is also preferably determined. Once the time template has been determined, one or more filters are developed which each use a version or form of the time template. 7 figs.

Time-frequency representation of autoionization dynamics in helium

NASA Astrophysics Data System (ADS)

Busto, D.; Barreau, L.; Isinger, M.; Turconi, M.; Alexandridi, C.; Harth, A.; Zhong, S.; Squibb, R. J.; Kroon, D.; Plogmaker, S.; Miranda, M.; Jiménez-Galán, Á.; Argenti, L.; Arnold, C. L.; Feifel, R.; Martín, F.; Gisselbrecht, M.; L'Huillier, A.; Salières, P.

2018-02-01

Autoionization, which results from the interference between direct photoionization and photoexcitation to a discrete state decaying to the continuum by configuration interaction, is a well known example of the important role of electron correlation in light-matter interaction. Information on this process can be obtained by studying the spectral, or equivalently, temporal complex amplitude of the ionized electron wave packet. Using an energy-resolved interferometric technique, we measure the spectral amplitude and phase of autoionized wave packets emitted via the sp2+ and sp3+ resonances in helium. These measurements allow us to reconstruct the corresponding temporal profiles by Fourier transform. In addition, applying various time-frequency representations, we observe the build-up of the wave packets in the continuum, monitor the instantaneous frequencies emitted at any time and disentangle the dynamics of the direct and resonant ionization channels.

Advanced Beamforming Concepts: Source Localization Using the Bispectrum, Gabor Transform, Wigner-Ville Distribution, and Nonstationary Signal Representation

DTIC Science & Technology

1991-12-01

TRANSFORM, WIGNER - VILLE DISTRIBUTION , AND NONSTATIONARY SIGNAL REPRESENTATIONS 6. AUTHOR(S) J. C. Allen 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS...bispectrum yields a bispectral direction finder. Estimates of time-frequency distributions produce Wigner - Ville and Gabor direction-finders. Some types...Beamforming Concepts: Source Localization Using the Bispectrum, Gabor Transform, Wigner - Ville Distribution , and Nonstationary Signal Representations

Time-frequency and advanced frequency estimation techniques for the investigation of bat echolocation calls.

PubMed

Kopsinis, Yannis; Aboutanios, Elias; Waters, Dean A; McLaughlin, Steve

2010-02-01

In this paper, techniques for time-frequency analysis and investigation of bat echolocation calls are studied. Particularly, enhanced resolution techniques are developed and/or used in this specific context for the first time. When compared to traditional time-frequency representation methods, the proposed techniques are more capable of showing previously unseen features in the structure of bat echolocation calls. It should be emphasized that although the study is focused on bat echolocation recordings, the results are more general and applicable to many other types of signal.

Time-frequency analysis of backscattered signals from diffuse radar targets

NASA Astrophysics Data System (ADS)

Kenny, O. P.; Boashash, B.

1993-06-01

The need for analysis of time-varying signals has led to the formulation of a class of joint time-frequency distributions (TFDs). One of these TFDs, the Wigner-Ville distribution (WVD), has useful properties which can be applied to radar imaging. The authors discuss time-frequency representation of the backscattered signal from a diffuse radar target. It is then shown that for point scatterers which are statistically dependent or for which the reflectivity coefficient has a nonzero mean value, reconstruction using time of flight positron emission tomography on time-frequency images is effective for estimating the scattering function of the target.

Time-varying higher order spectra

NASA Astrophysics Data System (ADS)

Boashash, Boualem; O'Shea, Peter

1991-12-01

A general solution for the problem of time-frequency signal representation of nonlinear FM signals is provided, based on a generalization of the Wigner-Ville distribution. The Wigner- Ville distribution (WVD) is a second order time-frequency representation. That is, it is able to give ideal energy concentration for quadratic phase signals and its ensemble average is a second order time-varying spectrum. The same holds for Cohen's class of time-frequency distributions, which are smoothed versions of the WVD. The WVD may be extended so as to achieve ideal energy concentration for higher order phase laws, and such that the expectation is a time-varying higher order spectrum. The usefulness of these generalized Wigner-Ville distributions (GWVD) is twofold. Firstly, because they achieve ideal energy concentration for polynomial phase signals, they may be used for optimal instantaneous frequency estimation. Second, they are useful for discriminating between nonstationary processes of differing higher order moments. In the same way that the WVD is generalized, we generalize Cohen's class of TFDs by defining a class of generalized time-frequency distributions (GTFDs) obtained by a two dimensional smoothing of the GWVD. Another results derived from this approach is a method based on higher order spectra which allows the separation of cross-terms and auto- terms in the WVD.

Analytical representation for ephemeris with short time-span - Aplication to the longitude of Titan

NASA Astrophysics Data System (ADS)

XI, Xiaojin; Vienne, Alain

2017-06-01

Ephemerides of the natural satellites are generally presented in the form of tables, or computed on line, for example like some best ones from JPL or IMCCE. In the sense of fitted the more recent and best observations, analytical representation is not so sufficient, although these representations are valid over a very long time-span. But in some analytical studies, it could be benefitted to have the both advantages. We present here the case of the study of the rotation of Titan, in which we need a representation of the true longitude of Titan. Frequency analysis can be used partially on the numerical ephemerides because of limited time-span. To complete it, we use the form of the analytical representation to obtained their numerical parameters.The method is presented and some results are given.

Analysis of the circumferential acoustic waves backscattered by a tube using the time-frequency representation of Wigner-Ville

NASA Astrophysics Data System (ADS)

Latif, R.; Aassif, E.; Maze, G.; Decultot, D.; Moudden, A.; Faiz, B.

2000-01-01

This paper presents a study of the group velocity dispersion of some circumferential waves propagating around an elastic tube. The dispersive character of the circumferential waves is theoretically known, but the experimental measurement of the group velocity in a dispersive medium is still a complex operation. We have determined the characteristics of the circumferential wave dispersion for aluminium and steel tubes using a time-frequency representation. Among these time-frequency techniques, the Wigner-Ville distribution (WVD) is used here for its interesting properties in terms of acoustic applications. The WVD is applied to the analysis of the dispersion of S0 symmetric and A1 antisymmetric circumferential waves propagating around a tube with a radii ratio equal to 0.95 (internal radius:external radius). This allowed us to determine their group velocities and reduced cutoff frequencies. The results obtained are in good agreement with the calculated values using the proper modes theory.

Molecular quantum control landscapes in von Neumann time-frequency phase space

NASA Astrophysics Data System (ADS)

Ruetzel, Stefan; Stolzenberger, Christoph; Fechner, Susanne; Dimler, Frank; Brixner, Tobias; Tannor, David J.

2010-10-01

Recently we introduced the von Neumann representation as a joint time-frequency description for femtosecond laser pulses and suggested its use as a basis for pulse shaping experiments. Here we use the von Neumann basis to represent multidimensional molecular control landscapes, providing insight into the molecular dynamics. We present three kinds of time-frequency phase space scanning procedures based on the von Neumann formalism: variation of intensity, time-frequency phase space position, and/or the relative phase of single subpulses. The shaped pulses produced are characterized via Fourier-transform spectral interferometry. Quantum control is demonstrated on the laser dye IR140 elucidating a time-frequency pump-dump mechanism.

Molecular quantum control landscapes in von Neumann time-frequency phase space.

PubMed

Ruetzel, Stefan; Stolzenberger, Christoph; Fechner, Susanne; Dimler, Frank; Brixner, Tobias; Tannor, David J

2010-10-28

Recently we introduced the von Neumann representation as a joint time-frequency description for femtosecond laser pulses and suggested its use as a basis for pulse shaping experiments. Here we use the von Neumann basis to represent multidimensional molecular control landscapes, providing insight into the molecular dynamics. We present three kinds of time-frequency phase space scanning procedures based on the von Neumann formalism: variation of intensity, time-frequency phase space position, and/or the relative phase of single subpulses. The shaped pulses produced are characterized via Fourier-transform spectral interferometry. Quantum control is demonstrated on the laser dye IR140 elucidating a time-frequency pump-dump mechanism.

Complex-valued time-series correlation increases sensitivity in FMRI analysis.

PubMed

Kociuba, Mary C; Rowe, Daniel B

2016-07-01

To develop a linear matrix representation of correlation between complex-valued (CV) time-series in the temporal Fourier frequency domain, and demonstrate its increased sensitivity over correlation between magnitude-only (MO) time-series in functional MRI (fMRI) analysis. The standard in fMRI is to discard the phase before the statistical analysis of the data, despite evidence of task related change in the phase time-series. With a real-valued isomorphism representation of Fourier reconstruction, correlation is computed in the temporal frequency domain with CV time-series data, rather than with the standard of MO data. A MATLAB simulation compares the Fisher-z transform of MO and CV correlations for varying degrees of task related magnitude and phase amplitude change in the time-series. The increased sensitivity of the complex-valued Fourier representation of correlation is also demonstrated with experimental human data. Since the correlation description in the temporal frequency domain is represented as a summation of second order temporal frequencies, the correlation is easily divided into experimentally relevant frequency bands for each voxel's temporal frequency spectrum. The MO and CV correlations for the experimental human data are analyzed for four voxels of interest (VOIs) to show the framework with high and low contrast-to-noise ratios in the motor cortex and the supplementary motor cortex. The simulation demonstrates the increased strength of CV correlations over MO correlations for low magnitude contrast-to-noise time-series. In the experimental human data, the MO correlation maps are noisier than the CV maps, and it is more difficult to distinguish the motor cortex in the MO correlation maps after spatial processing. Including both magnitude and phase in the spatial correlation computations more accurately defines the correlated left and right motor cortices. Sensitivity in correlation analysis is important to preserve the signal of interest in fMRI data sets with high noise variance, and avoid excessive processing induced correlation. Copyright © 2016 Elsevier Inc. All rights reserved.

Eulerian frequency analysis of structural vibrations from high-speed video

DOE Office of Scientific and Technical Information (OSTI.GOV)

Venanzoni, Andrea; Siemens Industry Software NV, Interleuvenlaan 68, B-3001 Leuven; De Ryck, Laurent

An approach for the analysis of the frequency content of structural vibrations from high-speed video recordings is proposed. The techniques and tools proposed rely on an Eulerian approach, that is, using the time history of pixels independently to analyse structural motion, as opposed to Lagrangian approaches, where the motion of the structure is tracked in time. The starting point is an existing Eulerian motion magnification method, which consists in decomposing the video frames into a set of spatial scales through a so-called Laplacian pyramid [1]. Each scale — or level — can be amplified independently to reconstruct a magnified motionmore » of the observed structure. The approach proposed here provides two analysis tools or pre-amplification steps. The first tool provides a representation of the global frequency content of a video per pyramid level. This may be further enhanced by applying an angular filter in the spatial frequency domain to each frame of the video before the Laplacian pyramid decomposition, which allows for the identification of the frequency content of the structural vibrations in a particular direction of space. This proposed tool complements the existing Eulerian magnification method by amplifying selectively the levels containing relevant motion information with respect to their frequency content. This magnifies the displacement while limiting the noise contribution. The second tool is a holographic representation of the frequency content of a vibrating structure, yielding a map of the predominant frequency components across the structure. In contrast to the global frequency content representation of the video, this tool provides a local analysis of the periodic gray scale intensity changes of the frame in order to identify the vibrating parts of the structure and their main frequencies. Validation cases are provided and the advantages and limits of the approaches are discussed. The first validation case consists of the frequency content retrieval of the tip of a shaker, excited at selected fixed frequencies. The goal of this setup is to retrieve the frequencies at which the tip is excited. The second validation case consists of two thin metal beams connected to a randomly excited bar. It is shown that the holographic representation visually highlights the predominant frequency content of each pixel and locates the global frequencies of the motion, thus retrieving the natural frequencies for each beam.« less

Group Analysis in FieldTrip of Time-Frequency Responses: A Pipeline for Reproducibility at Every Step of Processing, Going From Individual Sensor Space Representations to an Across-Group Source Space Representation.

PubMed

Andersen, Lau M

2018-01-01

An important aim of an analysis pipeline for magnetoencephalographic (MEG) data is that it allows for the researcher spending maximal effort on making the statistical comparisons that will answer his or her questions. The example question being answered here is whether the so-called beta rebound differs between novel and repeated stimulations. Two analyses are presented: going from individual sensor space representations to, respectively, an across-group sensor space representation and an across-group source space representation. The data analyzed are neural responses to tactile stimulations of the right index finger in a group of 20 healthy participants acquired from an Elekta Neuromag System. The processing steps covered for the first analysis are MaxFiltering the raw data, defining, preprocessing and epoching the data, cleaning the data, finding and removing independent components related to eye blinks, eye movements and heart beats, calculating participants' individual evoked responses by averaging over epoched data and subsequently removing the average response from single epochs, calculating a time-frequency representation and baselining it with non-stimulation trials and finally calculating a grand average, an across-group sensor space representation. The second analysis starts from the grand average sensor space representation and after identification of the beta rebound the neural origin is imaged using beamformer source reconstruction. This analysis covers reading in co-registered magnetic resonance images, segmenting the data, creating a volume conductor, creating a forward model, cutting out MEG data of interest in the time and frequency domains, getting Fourier transforms and estimating source activity with a beamformer model where power is expressed relative to MEG data measured during periods of non-stimulation. Finally, morphing the source estimates onto a common template and performing group-level statistics on the data are covered. Functions for saving relevant figures in an automated and structured manner are also included. The protocol presented here can be applied to any research protocol where the emphasis is on source reconstruction of induced responses where the underlying sources are not coherent.

Time-frequency analysis of electric motors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bentley, C.L.; Dunn, M.E.; Mattingly, J.K.

1995-12-31

Physical signals such as the current of an electric motor become nonstationary as a consequence of degraded operation and broken parts. In this instance, their power spectral densities become time dependent, and time-frequency analysis techniques become the appropriate tools for signal analysis. The first among these techniques, generally called the short-time Fourier transform (STFT) method, is the Gabor transform 2 (GT) of a signal S(t), which decomposes the signal into time-local frequency modes: where the window function, {Phi}(t-{tau}), is a normalized Gaussian. Alternatively, one can decompose the signal into its multi-resolution representation at different levels of magnification. This representation ismore » achieved by the continuous wavelet transform (CWT) where the function g(t) is a kernel of zero average belonging to a family of scaled and shifted wavelet kernels. The CWT can be interpreted as the action of a microscope that locates the signal by the shift parameter b and adjusts its magnification by changing the scale parameter a. The Fourier-transformed CWT, W,{sub g}(a, {omega}), acts as a filter that places the high-frequency content of a signal into the lower end of the scale spectrum and vice versa for the low frequencies. Signals from a motor in three different states were analyzed.« less

Incorporating Auditory Models in Speech/Audio Applications

NASA Astrophysics Data System (ADS)

Krishnamoorthi, Harish

2011-12-01

Following the success in incorporating perceptual models in audio coding algorithms, their application in other speech/audio processing systems is expanding. In general, all perceptual speech/audio processing algorithms involve minimization of an objective function that directly/indirectly incorporates properties of human perception. This dissertation primarily investigates the problems associated with directly embedding an auditory model in the objective function formulation and proposes possible solutions to overcome high complexity issues for use in real-time speech/audio algorithms. Specific problems addressed in this dissertation include: 1) the development of approximate but computationally efficient auditory model implementations that are consistent with the principles of psychoacoustics, 2) the development of a mapping scheme that allows synthesizing a time/frequency domain representation from its equivalent auditory model output. The first problem is aimed at addressing the high computational complexity involved in solving perceptual objective functions that require repeated application of auditory model for evaluation of different candidate solutions. In this dissertation, a frequency pruning and a detector pruning algorithm is developed that efficiently implements the various auditory model stages. The performance of the pruned model is compared to that of the original auditory model for different types of test signals in the SQAM database. Experimental results indicate only a 4-7% relative error in loudness while attaining up to 80-90 % reduction in computational complexity. Similarly, a hybrid algorithm is developed specifically for use with sinusoidal signals and employs the proposed auditory pattern combining technique together with a look-up table to store representative auditory patterns. The second problem obtains an estimate of the auditory representation that minimizes a perceptual objective function and transforms the auditory pattern back to its equivalent time/frequency representation. This avoids the repeated application of auditory model stages to test different candidate time/frequency vectors in minimizing perceptual objective functions. In this dissertation, a constrained mapping scheme is developed by linearizing certain auditory model stages that ensures obtaining a time/frequency mapping corresponding to the estimated auditory representation. This paradigm was successfully incorporated in a perceptual speech enhancement algorithm and a sinusoidal component selection task.

The topography of frequency and time representation in primate auditory cortices

PubMed Central

Baumann, Simon; Joly, Olivier; Rees, Adrian; Petkov, Christopher I; Sun, Li; Thiele, Alexander; Griffiths, Timothy D

2015-01-01

Natural sounds can be characterised by their spectral content and temporal modulation, but how the brain is organized to analyse these two critical sound dimensions remains uncertain. Using functional magnetic resonance imaging, we demonstrate a topographical representation of amplitude modulation rate in the auditory cortex of awake macaques. The representation of this temporal dimension is organized in approximately concentric bands of equal rates across the superior temporal plane in both hemispheres, progressing from high rates in the posterior core to low rates in the anterior core and lateral belt cortex. In A1 the resulting gradient of modulation rate runs approximately perpendicular to the axis of the tonotopic gradient, suggesting an orthogonal organisation of spectral and temporal sound dimensions. In auditory belt areas this relationship is more complex. The data suggest a continuous representation of modulation rate across several physiological areas, in contradistinction to a separate representation of frequency within each area. DOI: http://dx.doi.org/10.7554/eLife.03256.001 PMID:25590651

A fast algorithm for vertex-frequency representations of signals on graphs

PubMed Central

Jestrović, Iva; Coyle, James L.; Sejdić, Ervin

2016-01-01

The windowed Fourier transform (short time Fourier transform) and the S-transform are widely used signal processing tools for extracting frequency information from non-stationary signals. Previously, the windowed Fourier transform had been adopted for signals on graphs and has been shown to be very useful for extracting vertex-frequency information from graphs. However, high computational complexity makes these algorithms impractical. We sought to develop a fast windowed graph Fourier transform and a fast graph S-transform requiring significantly shorter computation time. The proposed schemes have been tested with synthetic test graph signals and real graph signals derived from electroencephalography recordings made during swallowing. The results showed that the proposed schemes provide significantly lower computation time in comparison with the standard windowed graph Fourier transform and the fast graph S-transform. Also, the results showed that noise has no effect on the results of the algorithm for the fast windowed graph Fourier transform or on the graph S-transform. Finally, we showed that graphs can be reconstructed from the vertex-frequency representations obtained with the proposed algorithms. PMID:28479645

Stabilization of Taylor-Couette flow due to time-periodic outer cylinder oscillation

NASA Technical Reports Server (NTRS)

Murray, B. T.; Mcfadden, G. B.; Coriell, S. R.

1990-01-01

The linear stability of circular Couette flow between concentric infinite cylinders is considered for the case when the inner cylinder is rotated at a constant angular velocity and the outer cylinder is driven sinusoidally in time with zero mean rotation. This configuration was studied experimentally by Walsh and Donnelly. The critical Reynolds numbers calculated from linear stability theory agree well with the experimental values, except at large modulation amplitudes and small frequencies. The theoretical values are obtained using Floquet theory implemented in two distinct approaches: a truncated Fourier series representation in time, and a fundamental solution matrix based on a Chebyshev pseudospectral representation in space. For large amplitude, low frequency modulation, the linear eigenfunctions are temporally complex, consisting of a quiescent region followed by rapid change in the perturbed flow velocities.

Radar Imaging Using The Wigner-Ville Distribution

NASA Astrophysics Data System (ADS)

Boashash, Boualem; Kenny, Owen P.; Whitehouse, Harper J.

1989-12-01

The need for analysis of time-varying signals has led to the formulation of a class of joint time-frequency distributions (TFDs). One of these TFDs, the Wigner-Ville distribution (WVD), has useful properties which can be applied to radar imaging. This paper first discusses the radar equation in terms of the time-frequency representation of the signal received from a radar system. It then presents a method of tomographic reconstruction for time-frequency images to estimate the scattering function of the aircraft. An optical archi-tecture is then discussed for the real-time implementation of the analysis method based on the WVD.

Pseudo Wigner-Ville Distribution, Computer Program and its Applications to Time-Frequency Domain Problems

DTIC Science & Technology

1993-03-01

representation is needed to characterize such signature. Pseudo Wigner - Ville distribution is ideally suited for portraying non-stationary signal in the...features jointly in time and frequency. 14, SUBJECT TERIMS 15. NUMBER OF PAGES Pseudo Wigner - Ville Distribution , Analytic Signal, 83 Hilbert Transform...D U C T IO N ............................................................................ . 1 II. PSEUDO WIGNER - VILLE DISTRIBUTION

Multi-frequency data analysis in AFM by wavelet transform

NASA Astrophysics Data System (ADS)

Pukhova, V.; Ferrini, G.

2017-10-01

Interacting cantilevers in AFM experiments generate non-stationary, multi-frequency signals consisting of numerous excited flexural and torsional modes and their harmonics. The analysis of such signals is challenging, requiring special methodological approaches and a powerful mathematical apparatus. The most common approach to the signal analysis is to apply Fourier transform analysis. However, FT gives accurate spectra for stationary signals, and for signals changing their spectral content over time, FT provides only an averaged spectrum. Hence, for non-stationary and rapidly varying signals, such as those from interacting cantilevers, a method that shows the spectral evolution in time is needed. One of the most powerful techniques, allowing detailed time-frequency representation of signals, is the wavelet transform. It is a method of analysis that allows representation of energy associated to the signal at a particular frequency and time, providing correlation between the spectral and temporal features of the signal, unlike FT. This is particularly important in AFM experiments because signals nonlinearities contains valuable information about tip-sample interactions and consequently surfaces properties. The present work is aimed to show the advantages of wavelet transform in comparison with FT using as an example the force curve analysis in dynamic force spectroscopy.

Wavelet processing techniques for digital mammography

NASA Astrophysics Data System (ADS)

Laine, Andrew F.; Song, Shuwu

1992-09-01

This paper introduces a novel approach for accomplishing mammographic feature analysis through multiresolution representations. We show that efficient (nonredundant) representations may be identified from digital mammography and used to enhance specific mammographic features within a continuum of scale space. The multiresolution decomposition of wavelet transforms provides a natural hierarchy in which to embed an interactive paradigm for accomplishing scale space feature analysis. Similar to traditional coarse to fine matching strategies, the radiologist may first choose to look for coarse features (e.g., dominant mass) within low frequency levels of a wavelet transform and later examine finer features (e.g., microcalcifications) at higher frequency levels. In addition, features may be extracted by applying geometric constraints within each level of the transform. Choosing wavelets (or analyzing functions) that are simultaneously localized in both space and frequency, results in a powerful methodology for image analysis. Multiresolution and orientation selectivity, known biological mechanisms in primate vision, are ingrained in wavelet representations and inspire the techniques presented in this paper. Our approach includes local analysis of complete multiscale representations. Mammograms are reconstructed from wavelet representations, enhanced by linear, exponential and constant weight functions through scale space. By improving the visualization of breast pathology we can improve the chances of early detection of breast cancers (improve quality) while requiring less time to evaluate mammograms for most patients (lower costs).

Optical linear algebra processors - Architectures and algorithms

NASA Technical Reports Server (NTRS)

Casasent, David

1986-01-01

Attention is given to the component design and optical configuration features of a generic optical linear algebra processor (OLAP) architecture, as well as the large number of OLAP architectures, number representations, algorithms and applications encountered in current literature. Number-representation issues associated with bipolar and complex-valued data representations, high-accuracy (including floating point) performance, and the base or radix to be employed, are discussed, together with case studies on a space-integrating frequency-multiplexed architecture and a hybrid space-integrating and time-integrating multichannel architecture.

Speech transformations based on a sinusoidal representation

NASA Astrophysics Data System (ADS)

Quatieri, T. E.; McAulay, R. J.

1986-05-01

A new speech analysis/synthesis technique is presented which provides the basis for a general class of speech transformation including time-scale modification, frequency scaling, and pitch modification. These modifications can be performed with a time-varying change, permitting continuous adjustment of a speaker's fundamental frequency and rate of articulation. The method is based on a sinusoidal representation of the speech production mechanism that has been shown to produce synthetic speech that preserves the waveform shape and is essentially perceptually indistinguishable from the original. Although the analysis/synthesis system originally was designed for single-speaker signals, it is equally capable of recovering and modifying nonspeech signals such as music; multiple speakers, marine biologic sounds, and speakers in the presence of interferences such as noise and musical backgrounds.

Children Can Solve Bayesian Problems: The Role of Representation in Mental Computation

ERIC Educational Resources Information Center

Zhu, Liqi; Gigerenzer, Gerd

2006-01-01

Can children reason the Bayesian way? We argue that the answer to this question depends on how numbers are represented, because a representation can do part of the computation. We test, for the first time, whether Bayesian reasoning can be elicited in children by means of natural frequencies. We show that when information was presented to fourth,…

Investigation into the bistatic evolution of the acoustic scattering from a cylindrical shell using time-frequency analysis

NASA Astrophysics Data System (ADS)

Agounad, Said; Aassif, El Houcein; Khandouch, Younes; Maze, Gérard; Décultot, Dominique

2018-01-01

The time and frequency analyses of the acoustic scattering by an elastic cylindrical shell in bistatic method show that the arrival times of the echoes and the resonance frequencies of the elastic waves propagating in and around the cylindrical shell are a function of the bistatic angle, β, between the emitter and receiver transducers. The aim of this work is to explain the observed results in time and frequency domains using time-frequency analysis and graphical interpretations. The performance of four widely used time-frequency representations, the Smoothed Pseudo Wigner-Ville (SPWV), the Spectrogram (SP), the reassignment SPWV, and the reassignment SP, are studied. The investigation into the evolution of the time-frequency plane as a function of the bistatic angle β shows that there are the waves propagating in counter-clockwise direction (labeled wave+) and the waves which propagate in clockwise direction (labeled waves-). In this paper the A, S0, and A1 circumferential waves are investigated. The graphical interpretations are used to explain the formation mechanism of these waves and the acoustic scattering in monostatic and bistatic configurations. The delay between the echoes of the waves+ and those of the waves- is expressed in the case of the circumnavigating wave (Scholte-Stoneley wave). This study shows that the observed waves at β = 0 ° and β = 18 0 ° are the result of the constructive interferences between the waves+ and the waves-. A comparative study of the physical properties (group velocity dispersion and cut-off frequency) of the waves+, the waves- and the waves observed in monostatic configuration is conducted. Furthermore, it is shown that the ability of the time-frequency representation to highlight the waves+ and the waves- is very useful, for example, for the detection and the localization of defaults, the classification purposes, etc.

Time-Frequency Learning Machines for Nonstationarity Detection Using Surrogates

NASA Astrophysics Data System (ADS)

Borgnat, Pierre; Flandrin, Patrick; Richard, Cédric; Ferrari, André; Amoud, Hassan; Honeine, Paul

2012-03-01

Time-frequency representations provide a powerful tool for nonstationary signal analysis and classification, supporting a wide range of applications [12]. As opposed to conventional Fourier analysis, these techniques reveal the evolution in time of the spectral content of signals. In Ref. [7,38], time-frequency analysis is used to test stationarity of any signal. The proposed method consists of a comparison between global and local time-frequency features. The originality is to make use of a family of stationary surrogate signals for defining the null hypothesis of stationarity and, based upon this information, to derive statistical tests. An open question remains, however, about how to choose relevant time-frequency features. Over the last decade, a number of new pattern recognition methods based on reproducing kernels have been introduced. These learning machines have gained popularity due to their conceptual simplicity and their outstanding performance [30]. Initiated by Vapnik’s support vector machines (SVM) [35], they offer now a wide class of supervised and unsupervised learning algorithms. In Ref. [17-19], the authors have shown how the most effective and innovative learning machines can be tuned to operate in the time-frequency domain. This chapter follows this line of research by taking advantage of learning machines to test and quantify stationarity. Based on one-class SVM, our approach uses the entire time-frequency representation and does not require arbitrary feature extraction. Applied to a set of surrogates, it provides the domain boundary that includes most of these stationarized signals. This allows us to test the stationarity of the signal under investigation. This chapter is organized as follows. In Section 22.2, we introduce the surrogate data method to generate stationarized signals, namely, the null hypothesis of stationarity. The concept of time-frequency learning machines is presented in Section 22.3, and applied to one-class SVM in order to derive a stationarity test in Section 22.4. The relevance of the latter is illustrated by simulation results in Section 22.5.

A New Instantaneous Frequency Measure Based on The Stockwell Transform

NASA Astrophysics Data System (ADS)

yedlin, M. J.; Ben-Horrin, Y.; Fraser, J. D.

2011-12-01

We propose the use of a new transform, the Stockwell transform[1], as a means of creating time-frequency maps and applying them to distinguish blasts from earthquakes. This new transform, the Stockwell transform can be considered as a variant of the continuous wavelet transform, that preserves the absolute phase.The Stockwell transform employs a complex Morlet mother wavelet. The novelty of this transform lies in its resolution properties. High frequencies in the candidate signal are well-resolved in time but poorly resolved in frequency, while the converse is true for low frequency signal components. The goal of this research is to obtain the instantaneous frequency as a function of time for both the earthquakes and the blasts. Two methods will be compared. In the first method, we will compute the analytic signal, the envelope and the instantaneous phase as a function of time[2]. The instantaneous phase derivative will yield the instantaneous angular frequency. The second method will be based on time-frequency analysis using the Stockwell transform. The Stockwell transform will be computed in non-redundant fashion using a dyadic representation[3]. For each time-point, the frequency centroid will be computed -- a representation for the most likely frequency at that time. A detailed comparison will be presented for both approaches to the computation of the instantaneous frequency. An advantage of the Stockwell approach is that no differentiation is applied. The Hilbert transform method can be less sensitive to edge effects. The goal of this research is to see if the new Stockwell-based method could be used as a discriminant between earthquakes and blasts. References [1] Stockwell, R.G., Mansinha, L. and Lowe, R.P. "Localization of the complex spectrum: the S transform", IEEE Trans. Signal Processing, vol.44, no.4, pp.998-1001, (1996). [2]Taner, M.T., Koehler, F. "Complex seismic trace analysis", Geophysics, vol. 44, Issue 6, pp. 1041-1063 (1979). [3] Brown, R.A., Lauzon, M.L. and Frayne, R. "General Description of Linear Time-Frequency Transforms and Formulation of a Fast, Invertible Transform That Samples the Continuous S-Transform Spectrum Nonredundantly", IEEE Transactions on Signal Processing, 1:281-90 (2010).

On Holo-Hilbert Spectral Analysis: A Full Informational Spectral Representation for Nonlinear and Non-Stationary Data

NASA Technical Reports Server (NTRS)

Huang, Norden E.; Hu, Kun; Yang, Albert C. C.; Chang, Hsing-Chih; Jia, Deng; Liang, Wei-Kuang; Yeh, Jia Rong; Kao, Chu-Lan; Juan, Chi-Huang; Peng, Chung Kang;

Time-frequency representations of the sternocleidomastoid muscle electromyographic signal recorded with concentric ring electrodes.

PubMed

Estrada, Luis; Torres, Abel; Garcia-Casado, Javier; Sarlabous, Leonardo; Prats-Boluda, Gema; Jane, Raimon

2016-08-01

The use of non-invasive methods for the study of respiratory muscle signals can provide clinical information for the evaluation of the respiratory muscle function. The aim of this study was to evaluate time-frequency characteristics of the electrical activity of the sternocleidomastoid muscle recorded superficially by means of concentric ring electrodes (CREs) in a bipolar configuration. The CREs enhance the spatial resolution, attenuate interferences, as the cardiac activity, and also simplify the orientation problem associated to the electrode location. Five healthy subjects underwent a respiratory load test in which an inspiratory load was imposed during the inspiratory phase. During the test, the electromyographic signal of the sternocleidomastoid muscle (EMGsc) and the inspiratory mouth pressure (Pmouth) were acquired. Time-frequency characteristics of the EMGsc signal were analyzed by means of eight time-frequency representations (TFRs): the spectrogram (SPEC), the Morlet scalogram (SCAL), the Wigner-Ville distribution (WVD), the Choi-Williams distribution (CHWD), two generalized exponential distributions (GED1 and GED2), the Born-Jordan distribution (BJD) and the Cone-Kernel distribution (CKD). The instantaneous central frequency of the EMGsc showed an increasing behavior during the inspiratory cycle and with the increase of the inspiratory load. The bilinear TFRs (WVD, CHWD, GEDs and BJD) were less sensitive to cardiac activity interference than classical TFRs (SPEC and SCAL). The GED2 was the TFR that shown the best results for the characterization of the instantaneous central frequency of the EMGsc.

Measurement system

NASA Technical Reports Server (NTRS)

Turner, J. W. (Inventor)

1973-01-01

A measurement system is described for providing an indication of a varying physical quantity represented by or converted to a variable frequency signal. Timing pulses are obtained marking the duration of a fixed number, or set, of cycles of the sampled signal and these timing pulses are employed to control the period of counting of cycles of a higher fixed and known frequency source. The counts of cycles obtained from the fixed frequency source provide a precise measurement of the average frequency of each set of cycles sampled, and thus successive discrete values of the quantity being measured. The frequency of the known frequency source is made such that each measurement is presented as a direct digital representation of the quantity measured.

Ultrasonic data compression via parameter estimation.

PubMed

Cardoso, Guilherme; Saniie, Jafar

2005-02-01

Ultrasonic imaging in medical and industrial applications often requires a large amount of data collection. Consequently, it is desirable to use data compression techniques to reduce data and to facilitate the analysis and remote access of ultrasonic information. The precise data representation is paramount to the accurate analysis of the shape, size, and orientation of ultrasonic reflectors, as well as to the determination of the properties of the propagation path. In this study, a successive parameter estimation algorithm based on a modified version of the continuous wavelet transform (CWT) to compress and denoise ultrasonic signals is presented. It has been shown analytically that the CWT (i.e., time x frequency representation) yields an exact solution for the time-of-arrival and a biased solution for the center frequency. Consequently, a modified CWT (MCWT) based on the Gabor-Helstrom transform is introduced as a means to exactly estimate both time-of-arrival and center frequency of ultrasonic echoes. Furthermore, the MCWT also has been used to generate a phase x bandwidth representation of the ultrasonic echo. This representation allows the exact estimation of the phase and the bandwidth. The performance of this algorithm for data compression and signal analysis is studied using simulated and experimental ultrasonic signals. The successive parameter estimation algorithm achieves a data compression ratio of (1-5N/J), where J is the number of samples and N is the number of echoes in the signal. For a signal with 10 echoes and 2048 samples, a compression ratio of 96% is achieved with a signal-to-noise ratio (SNR) improvement above 20 dB. Furthermore, this algorithm performs robustly, yields accurate echo estimation, and results in SNR enhancements ranging from 10 to 60 dB for composite signals having SNR as low as -10 dB.

The time course of spoken word learning and recognition: studies with artificial lexicons.

PubMed

Magnuson, James S; Tanenhaus, Michael K; Aslin, Richard N; Dahan, Delphine

2003-06-01

The time course of spoken word recognition depends largely on the frequencies of a word and its competitors, or neighbors (similar-sounding words). However, variability in natural lexicons makes systematic analysis of frequency and neighbor similarity difficult. Artificial lexicons were used to achieve precise control over word frequency and phonological similarity. Eye tracking provided time course measures of lexical activation and competition (during spoken instructions to perform visually guided tasks) both during and after word learning, as a function of word frequency, neighbor type, and neighbor frequency. Apparent shifts from holistic to incremental competitor effects were observed in adults and neural network simulations, suggesting such shifts reflect general properties of learning rather than changes in the nature of lexical representations.

A Hybrid Solution for Simultaneous Transfer of Ultrastable Optical Frequency, RF Frequency, and UTC Time-Tags Over Optical Fiber.

PubMed

Krehlik, Przemyslaw; Schnatz, Harald; Sliwczynski, Lukasz

2017-12-01

We describe a fiber-optic solution for simultaneous distribution of all signals generated at today's most advanced time and frequency laboratories, i.e., an ultrastable optical reference frequency derived from an optical atomic clock, a radio frequency precisely linked to a realization of the SI-Second, and a realization of an atomic timescale, being the local representation of the virtual, global UTC timescale. In our solution both the phase of the optical carrier and the delay of electrical signals (10-MHz frequency reference and one-pulse-per-second time tags) are stabilized against environmental perturbations influencing the fiber link instability and accuracy. We experimentally demonstrate optical transfer stabilities of and for 100 s averaging period, for optical carrier and 10-MHz signals, respectively.

Frequency-Selective Attention in Auditory Scenes Recruits Frequency Representations Throughout Human Superior Temporal Cortex.

PubMed

Riecke, Lars; Peters, Judith C; Valente, Giancarlo; Kemper, Valentin G; Formisano, Elia; Sorger, Bettina

2017-05-01

A sound of interest may be tracked amid other salient sounds by focusing attention on its characteristic features including its frequency. Functional magnetic resonance imaging findings have indicated that frequency representations in human primary auditory cortex (AC) contribute to this feat. However, attentional modulations were examined at relatively low spatial and spectral resolutions, and frequency-selective contributions outside the primary AC could not be established. To address these issues, we compared blood oxygenation level-dependent (BOLD) responses in the superior temporal cortex of human listeners while they identified single frequencies versus listened selectively for various frequencies within a multifrequency scene. Using best-frequency mapping, we observed that the detailed spatial layout of attention-induced BOLD response enhancements in primary AC follows the tonotopy of stimulus-driven frequency representations-analogous to the "spotlight" of attention enhancing visuospatial representations in retinotopic visual cortex. Moreover, using an algorithm trained to discriminate stimulus-driven frequency representations, we could successfully decode the focus of frequency-selective attention from listeners' BOLD response patterns in nonprimary AC. Our results indicate that the human brain facilitates selective listening to a frequency of interest in a scene by reinforcing the fine-grained activity pattern throughout the entire superior temporal cortex that would be evoked if that frequency was present alone. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

The non-equilibrium allele frequency spectrum in a Poisson random field framework.

PubMed

Kaj, Ingemar; Mugal, Carina F

2016-10-01

In population genetic studies, the allele frequency spectrum (AFS) efficiently summarizes genome-wide polymorphism data and shapes a variety of allele frequency-based summary statistics. While existing theory typically features equilibrium conditions, emerging methodology requires an analytical understanding of the build-up of the allele frequencies over time. In this work, we use the framework of Poisson random fields to derive new representations of the non-equilibrium AFS for the case of a Wright-Fisher population model with selection. In our approach, the AFS is a scaling-limit of the expectation of a Poisson stochastic integral and the representation of the non-equilibrium AFS arises in terms of a fixation time probability distribution. The known duality between the Wright-Fisher diffusion process and a birth and death process generalizing Kingman's coalescent yields an additional representation. The results carry over to the setting of a random sample drawn from the population and provide the non-equilibrium behavior of sample statistics. Our findings are consistent with and extend a previous approach where the non-equilibrium AFS solves a partial differential forward equation with a non-traditional boundary condition. Moreover, we provide a bridge to previous coalescent-based work, and hence tie several frameworks together. Since frequency-based summary statistics are widely used in population genetics, for example, to identify candidate loci of adaptive evolution, to infer the demographic history of a population, or to improve our understanding of the underlying mechanics of speciation events, the presented results are potentially useful for a broad range of topics. Copyright © 2016 Elsevier Inc. All rights reserved.

Self-control and frequency of model presentation: effects on learning a ballet passé relevé.

PubMed

Fagundes, Julie; Chen, David D; Laguna, Patricia

2013-08-01

The purpose of this experiment was to examine the combined effects of self-control and frequency of model presentation on learning a complex motor skill, i.e., ballet passé relevé. Before practice started self-control participants were asked to choose two viewings or six viewings (before practice and then every five trials) and the externally controlled groups were yoked to their self-control counterparts. All participants completed 15 acquisition trials followed by 5 trials for the immediate and 5 trials for the delayed retention tests 48 hours later. Dependent variables included cognitive representation scores, physical reproduction rankings, and balance time. Statistical analyses indicated that under limited physical practice conditions self-control and higher frequency of model presentation facilitated the development of cognitive representation and did not produce further benefits in movement reproductions and balance time. The results were discussed with respect to the social cognitive theory. Published by Elsevier B.V.

Time-Frequency Signal Representations Using Interpolations in Joint-Variable Domains

DTIC Science & Technology

2016-06-14

distribution kernels,” IEEE Trans. Signal Process., vol. 42, no. 5, pp. 1156–1165, May 1994. [25] G. S. Cunningham and W. J. Williams , “Kernel...interpolated data. For comparison, we include sparse reconstruction and WVD and Choi– Williams distribution (CWD) [23], which are directly applied to...Prentice-Hall, 1995. [23] H. I. Choi and W. J. Williams , “Improved time-frequency representa- tion of multicomponent signals using exponential kernels

Applications of fractional lower order S transform time frequency filtering algorithm to machine fault diagnosis

PubMed Central

Wang, Haibin; Zha, Daifeng; Li, Peng; Xie, Huicheng; Mao, Lili

2017-01-01

Stockwell transform(ST) time-frequency representation(ST-TFR) is a time frequency analysis method which combines short time Fourier transform with wavelet transform, and ST time frequency filtering(ST-TFF) method which takes advantage of time-frequency localized spectra can separate the signals from Gaussian noise. The ST-TFR and ST-TFF methods are used to analyze the fault signals, which is reasonable and effective in general Gaussian noise cases. However, it is proved that the mechanical bearing fault signal belongs to Alpha(α) stable distribution process(1 < α < 2) in this paper, even the noise also is α stable distribution in some special cases. The performance of ST-TFR method will degrade under α stable distribution noise environment, following the ST-TFF method fail. Hence, a new fractional lower order ST time frequency representation(FLOST-TFR) method employing fractional lower order moment and ST and inverse FLOST(IFLOST) are proposed in this paper. A new FLOST time frequency filtering(FLOST-TFF) algorithm based on FLOST-TFR method and IFLOST is also proposed, whose simplified method is presented in this paper. The discrete implementation of FLOST-TFF algorithm is deduced, and relevant steps are summarized. Simulation results demonstrate that FLOST-TFR algorithm is obviously better than the existing ST-TFR algorithm under α stable distribution noise, which can work better under Gaussian noise environment, and is robust. The FLOST-TFF method can effectively filter out α stable distribution noise, and restore the original signal. The performance of FLOST-TFF algorithm is better than the ST-TFF method, employing which mixed MSEs are smaller when α and generalized signal noise ratio(GSNR) change. Finally, the FLOST-TFR and FLOST-TFF methods are applied to analyze the outer race fault signal and extract their fault features under α stable distribution noise, where excellent performances can be shown. PMID:28406916

Ridge extraction from the time-frequency representation (TFR) of signals based on an image processing approach: application to the analysis of uterine electromyogram AR TFR.

PubMed

Terrien, Jérémy; Marque, Catherine; Germain, Guy

2008-05-01

Time-frequency representations (TFRs) of signals are increasingly being used in biomedical research. Analysis of such representations is sometimes difficult, however, and is often reduced to the extraction of ridges, or local energy maxima. In this paper, we describe a new ridge extraction method based on the image processing technique of active contours or snakes. We have tested our method on several synthetic signals and for the analysis of uterine electromyogram or electrohysterogram (EHG) recorded during gestation in monkeys. We have also evaluated a postprocessing algorithm that is especially suited for EHG analysis. Parameters are evaluated on real EHG signals in different gestational periods. The presented method gives good results when applied to synthetic as well as EHG signals. We have been able to obtain smaller ridge extraction errors when compared to two other methods specially developed for EHG. The gradient vector flow (GVF) snake method, or GVF-snake method, appears to be a good ridge extraction tool, which could be used on TFR of mono or multicomponent signals with good results.

Time and frequency domain characteristics of detrending-operation-based scaling analysis: Exact DFA and DMA frequency responses

NASA Astrophysics Data System (ADS)

Kiyono, Ken; Tsujimoto, Yutaka

2016-07-01

We develop a general framework to study the time and frequency domain characteristics of detrending-operation-based scaling analysis methods, such as detrended fluctuation analysis (DFA) and detrending moving average (DMA) analysis. In this framework, using either the time or frequency domain approach, the frequency responses of detrending operations are calculated analytically. Although the frequency domain approach based on conventional linear analysis techniques is only applicable to linear detrending operations, the time domain approach presented here is applicable to both linear and nonlinear detrending operations. Furthermore, using the relationship between the time and frequency domain representations of the frequency responses, the frequency domain characteristics of nonlinear detrending operations can be obtained. Based on the calculated frequency responses, it is possible to establish a direct connection between the root-mean-square deviation of the detrending-operation-based scaling analysis and the power spectrum for linear stochastic processes. Here, by applying our methods to DFA and DMA, including higher-order cases, exact frequency responses are calculated. In addition, we analytically investigate the cutoff frequencies of DFA and DMA detrending operations and show that these frequencies are not optimally adjusted to coincide with the corresponding time scale.

Time and frequency domain characteristics of detrending-operation-based scaling analysis: Exact DFA and DMA frequency responses.

PubMed

Kiyono, Ken; Tsujimoto, Yutaka

2016-07-01

We develop a general framework to study the time and frequency domain characteristics of detrending-operation-based scaling analysis methods, such as detrended fluctuation analysis (DFA) and detrending moving average (DMA) analysis. In this framework, using either the time or frequency domain approach, the frequency responses of detrending operations are calculated analytically. Although the frequency domain approach based on conventional linear analysis techniques is only applicable to linear detrending operations, the time domain approach presented here is applicable to both linear and nonlinear detrending operations. Furthermore, using the relationship between the time and frequency domain representations of the frequency responses, the frequency domain characteristics of nonlinear detrending operations can be obtained. Based on the calculated frequency responses, it is possible to establish a direct connection between the root-mean-square deviation of the detrending-operation-based scaling analysis and the power spectrum for linear stochastic processes. Here, by applying our methods to DFA and DMA, including higher-order cases, exact frequency responses are calculated. In addition, we analytically investigate the cutoff frequencies of DFA and DMA detrending operations and show that these frequencies are not optimally adjusted to coincide with the corresponding time scale.

Inhalation Frequency Controls Reformatting of Mitral/Tufted Cell Odor Representations in the Olfactory Bulb.

PubMed

Díaz-Quesada, Marta; Youngstrom, Isaac A; Tsuno, Yusuke; Hansen, Kyle R; Economo, Michael N; Wachowiak, Matt

2018-02-28

In mammals, olfactory sensation depends on inhalation, which controls activation of sensory neurons and temporal patterning of central activity. Odor representations by mitral and tufted (MT) cells, the main output from the olfactory bulb (OB), reflect sensory input as well as excitation and inhibition from OB circuits, which may change as sniff frequency increases. To test the impact of sampling frequency on MT cell odor responses, we obtained whole-cell recordings from MT cells in anesthetized male and female mice while varying inhalation frequency via tracheotomy, allowing comparison of inhalation-linked responses across cells. We characterized frequency effects on MT cell responses during inhalation of air and odorants using inhalation pulses and also "playback" of sniffing recorded from awake mice. Inhalation-linked changes in membrane potential were well predicted across frequency from linear convolution of 1 Hz responses; and, as frequency increased, near-identical temporal responses could emerge from depolarizing, hyperpolarizing, or multiphasic MT responses. However, net excitation was not well predicted from 1 Hz responses and varied substantially across MT cells, with some cells increasing and others decreasing in spike rate. As a result, sustained odorant sampling at higher frequencies led to increasing decorrelation of the MT cell population response pattern over time. Bulk activation of sensory inputs by optogenetic stimulation affected MT cells more uniformly across frequency, suggesting that frequency-dependent decorrelation emerges from odor-specific patterns of activity in the OB network. These results suggest that sampling behavior alone can reformat early sensory representations, possibly to optimize sensory perception during repeated sampling. SIGNIFICANCE STATEMENT Olfactory sensation in mammals depends on inhalation, which increases in frequency during active sampling of olfactory stimuli. We asked how inhalation frequency can shape the neural coding of odor information by recording from projection neurons of the olfactory bulb while artificially varying odor sampling frequency in the anesthetized mouse. We found that sampling an odor at higher frequencies led to diverse changes in net responsiveness, as measured by action potential output, that were not predicted from low-frequency responses. These changes led to a reorganization of the pattern of neural activity evoked by a given odorant that occurred preferentially during sustained, high-frequency inhalation. These results point to a novel mechanism for modulating early sensory representations solely as a function of sampling behavior. Copyright © 2018 the authors 0270-6474/18/382189-18$15.00/0.

Wright-Fisher diffusion bridges.

PubMed

Griffiths, Robert C; Jenkins, Paul A; Spanò, Dario

2017-10-06

The trajectory of the frequency of an allele which begins at x at time 0 and is known to have frequency z at time T can be modelled by the bridge process of the Wright-Fisher diffusion. Bridges when x=z=0 are particularly interesting because they model the trajectory of the frequency of an allele which appears at a time, then is lost by random drift or mutation after a time T. The coalescent genealogy back in time of a population in a neutral Wright-Fisher diffusion process is well understood. In this paper we obtain a new interpretation of the coalescent genealogy of the population in a bridge from a time t∈(0,T). In a bridge with allele frequencies of 0 at times 0 and T the coalescence structure is that the population coalesces in two directions from t to 0 and t to T such that there is just one lineage of the allele under consideration at times 0 and T. The genealogy in Wright-Fisher diffusion bridges with selection is more complex than in the neutral model, but still with the property of the population branching and coalescing in two directions from time t∈(0,T). The density of the frequency of an allele at time t is expressed in a way that shows coalescence in the two directions. A new algorithm for exact simulation of a neutral Wright-Fisher bridge is derived. This follows from knowing the density of the frequency in a bridge and exact simulation from the Wright-Fisher diffusion. The genealogy of the neutral Wright-Fisher bridge is also modelled by branching Pólya urns, extending a representation in a Wright-Fisher diffusion. This is a new very interesting representation that relates Wright-Fisher bridges to classical urn models in a Bayesian setting. Copyright © 2017 Elsevier Inc. All rights reserved.

Time-frequency signal analysis and synthesis - The choice of a method and its application

NASA Astrophysics Data System (ADS)

Boashash, Boualem

In this paper, the problem of choosing a method for time-frequency signal analysis is discussed. It is shown that a natural approach leads to the introduction of the concepts of the analytic signal and instantaneous frequency. The Wigner-Ville Distribution (WVD) is a method of analysis based upon these concepts and it is shown that an accurate Time-Frequency representation of a signal can be obtained by using the WVD for the analysis of a class of signals referred to as 'asymptotic'. For this class of signals, the instantaneous frequency describes an important physical parameter characteristic of the process under investigation. The WVD procedure for signal analysis and synthesis is outlined and its properties are reviewed for deterministic and random signals.

Time-Frequency Signal Analysis And Synthesis The Choice Of A Method And Its Application

NASA Astrophysics Data System (ADS)

Boashash, Boualem

1988-02-01

In this paper, the problem of choosing a method for time-frequency signal analysis is discussed. It is shown that a natural approach leads to the introduction of the concepts of the analytic signal and in-stantaneous frequency. The Wigner-Ville Distribution (WVD) is a method of analysis based upon these concepts and it is shown that an accurate Time-Frequency representation of a signal can be obtained by using the WVD for the analysis of a class of signals referred to as "asymptotic". For this class of signals, the instantaneous frequency describes an important physical parameter characteristic of the process under investigation. The WVD procedure for signal analysis and synthesis is outlined and its properties are reviewed for deterministic and random signals.

Comparison of the results of refractometric measurements in the process of diffusion, obtained by means of the backgroundoriented schlieren method and the holographic interferometry method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kraiskii, A V; Mironova, T V

2015-08-31

The results of the study of interdiffusion of two liquids, obtained using the holographic recording scheme with a nonstationary reference wave with the frequency linearly varying in space and time are compared with the results of correlation processing of digital photographs, made with a random background screen. The spatio-temporal behaviour of the signal in four basic representations ('space – temporal frequency', 'space – time', 'spatial frequency – temporal frequency' and 'spatial frequency – time') is found in the holographic experiment and calculated (in the appropriate coordinates) based on the background-oriented schlieren method. Practical coincidence of the results of the correlationmore » analysis and the holographic double-exposure interferometry is demonstrated. (interferometry)« less

2D DOST based local phase pattern for face recognition

NASA Astrophysics Data System (ADS)

Moniruzzaman, Md.; Alam, Mohammad S.

2017-05-01

A new two dimensional (2-D) Discrete Orthogonal Stcokwell Transform (DOST) based Local Phase Pattern (LPP) technique has been proposed for efficient face recognition. The proposed technique uses 2-D DOST as preliminary preprocessing and local phase pattern to form robust feature signature which can effectively accommodate various 3D facial distortions and illumination variations. The S-transform, is an extension of the ideas of the continuous wavelet transform (CWT), is also known for its local spectral phase properties in time-frequency representation (TFR). It provides a frequency dependent resolution of the time-frequency space and absolutely referenced local phase information while maintaining a direct relationship with the Fourier spectrum which is unique in TFR. After utilizing 2-D Stransform as the preprocessing and build local phase pattern from extracted phase information yield fast and efficient technique for face recognition. The proposed technique shows better correlation discrimination compared to alternate pattern recognition techniques such as wavelet or Gabor based face recognition. The performance of the proposed method has been tested using the Yale and extended Yale facial database under different environments such as illumination variation and 3D changes in facial expressions. Test results show that the proposed technique yields better performance compared to alternate time-frequency representation (TFR) based face recognition techniques.

Comparing nouns and verbs in a lexical task.

PubMed

Cordier, Françoise; Croizet, Jean-Claude; Rigalleau, François

2013-02-01

We analyzed the differential processing of nouns and verbs in a lexical decision task. Moderate and high-frequency nouns and verbs were compared. The characteristics of our material were specified at the formal level (number of letters and syllables, number of homographs, orthographic neighbors, frequency and age of acquisition), and at the semantic level (imagery, number and strength of associations, number of meanings, context dependency). A regression analysis indicated a classical frequency effect and a word-type effect, with latencies for verbs being slower than for nouns. The regression analysis did not permit the conclusion that semantic effects were involved (particularly imageability). Nevertheless, the semantic opposition between nouns as prototypical representations of objects, and verbs as prototypical representation of actions was not tested in this experiment and remains a good candidate explanation of the response time discrepancies between verbs and nouns.

Development of Phase Locking and Frequency Representation in the Infant Frequency-Following Response

ERIC Educational Resources Information Center

Van Dyke, Katlyn B.; Lieberman, Rachel; Presacco, Alessandro; Anderson, Samira

2017-01-01

Purpose: This study investigates the development of phase locking and frequency representation in infants using the frequency-following response to consonant-vowel syllables. Method: The frequency-following response was recorded in 56 infants and 15 young adults to 2 speech syllables (/ba/ and /ga/), which were presented in randomized order to the…

Cortical mechanisms for the segregation and representation of acoustic textures.

PubMed

Overath, Tobias; Kumar, Sukhbinder; Stewart, Lauren; von Kriegstein, Katharina; Cusack, Rhodri; Rees, Adrian; Griffiths, Timothy D

2010-02-10

Auditory object analysis requires two fundamental perceptual processes: the definition of the boundaries between objects, and the abstraction and maintenance of an object's characteristic features. Although it is intuitive to assume that the detection of the discontinuities at an object's boundaries precedes the subsequent precise representation of the object, the specific underlying cortical mechanisms for segregating and representing auditory objects within the auditory scene are unknown. We investigated the cortical bases of these two processes for one type of auditory object, an "acoustic texture," composed of multiple frequency-modulated ramps. In these stimuli, we independently manipulated the statistical rules governing (1) the frequency-time space within individual textures (comprising ramps with a given spectrotemporal coherence) and (2) the boundaries between textures (adjacent textures with different spectrotemporal coherences). Using functional magnetic resonance imaging, we show mechanisms defining boundaries between textures with different coherences in primary and association auditory cortices, whereas texture coherence is represented only in association cortex. Furthermore, participants' superior detection of boundaries across which texture coherence increased (as opposed to decreased) was reflected in a greater neural response in auditory association cortex at these boundaries. The results suggest a hierarchical mechanism for processing acoustic textures that is relevant to auditory object analysis: boundaries between objects are first detected as a change in statistical rules over frequency-time space, before a representation that corresponds to the characteristics of the perceived object is formed.

Robustness properties of discrete time regulators, LOG regulators and hybrid systems

NASA Technical Reports Server (NTRS)

Stein, G.; Athans, M.

1979-01-01

Robustness properites of sample-data LQ regulators are derived which show that these regulators have fundamentally inferior uncertainty tolerances when compared to their continuous-time counterparts. Results are also presented in stability theory, multivariable frequency domain analysis, LQG robustness, and mathematical representations of hybrid systems.

Applying matching pursuit decomposition time-frequency processing to UGS footstep classification

NASA Astrophysics Data System (ADS)

Larsen, Brett W.; Chung, Hugh; Dominguez, Alfonso; Sciacca, Jacob; Kovvali, Narayan; Papandreou-Suppappola, Antonia; Allee, David R.

2013-06-01

The challenge of rapid footstep detection and classification in remote locations has long been an important area of study for defense technology and national security. Also, as the military seeks to create effective and disposable unattended ground sensors (UGS), computational complexity and power consumption have become essential considerations in the development of classification techniques. In response to these issues, a research project at the Flexible Display Center at Arizona State University (ASU) has experimented with footstep classification using the matching pursuit decomposition (MPD) time-frequency analysis method. The MPD provides a parsimonious signal representation by iteratively selecting matched signal components from a pre-determined dictionary. The resulting time-frequency representation of the decomposed signal provides distinctive features for different types of footsteps, including footsteps during walking or running activities. The MPD features were used in a Bayesian classification method to successfully distinguish between the different activities. The computational cost of the iterative MPD algorithm was reduced, without significant loss in performance, using a modified MPD with a dictionary consisting of signals matched to cadence temporal gait patterns obtained from real seismic measurements. The classification results were demonstrated with real data from footsteps under various conditions recorded using a low-cost seismic sensor.

Convergence to equilibrium under a random Hamiltonian.

PubMed

Brandão, Fernando G S L; Ćwikliński, Piotr; Horodecki, Michał; Horodecki, Paweł; Korbicz, Jarosław K; Mozrzymas, Marek

2012-09-01

We analyze equilibration times of subsystems of a larger system under a random total Hamiltonian, in which the basis of the Hamiltonian is drawn from the Haar measure. We obtain that the time of equilibration is of the order of the inverse of the arithmetic average of the Bohr frequencies. To compute the average over a random basis, we compute the inverse of a matrix of overlaps of operators which permute four systems. We first obtain results on such a matrix for a representation of an arbitrary finite group and then apply it to the particular representation of the permutation group under consideration.

Convergence to equilibrium under a random Hamiltonian

NASA Astrophysics Data System (ADS)

Brandão, Fernando G. S. L.; Ćwikliński, Piotr; Horodecki, Michał; Horodecki, Paweł; Korbicz, Jarosław K.; Mozrzymas, Marek

2012-09-01

We analyze equilibration times of subsystems of a larger system under a random total Hamiltonian, in which the basis of the Hamiltonian is drawn from the Haar measure. We obtain that the time of equilibration is of the order of the inverse of the arithmetic average of the Bohr frequencies. To compute the average over a random basis, we compute the inverse of a matrix of overlaps of operators which permute four systems. We first obtain results on such a matrix for a representation of an arbitrary finite group and then apply it to the particular representation of the permutation group under consideration.

Estimation of modal parameters using bilinear joint time frequency distributions

NASA Astrophysics Data System (ADS)

Roshan-Ghias, A.; Shamsollahi, M. B.; Mobed, M.; Behzad, M.

2007-07-01

In this paper, a new method is proposed for modal parameter estimation using time-frequency representations. Smoothed Pseudo Wigner-Ville distribution which is a member of the Cohen's class distributions is used to decouple vibration modes completely in order to study each mode separately. This distribution reduces cross-terms which are troublesome in Wigner-Ville distribution and retains the resolution as well. The method was applied to highly damped systems, and results were superior to those obtained via other conventional methods.

[A wavelet neural network algorithm of EEG signals data compression and spikes recognition].

PubMed

Zhang, Y; Liu, A; Yu, K

1999-06-01

A novel method of EEG signals compression representation and epileptiform spikes recognition based on wavelet neural network and its algorithm is presented. The wavelet network not only can compress data effectively but also can recover original signal. In addition, the characters of the spikes and the spike-slow rhythm are auto-detected from the time-frequency isoline of EEG signal. This method is well worth using in the field of the electrophysiological signal processing and time-frequency analyzing.

Envelope contributions to the representation of interaural time difference in the forebrain of barn owls.

PubMed

Tellers, Philipp; Lehmann, Jessica; Führ, Hartmut; Wagner, Hermann

2017-09-01

Birds and mammals use the interaural time difference (ITD) for azimuthal sound localization. While barn owls can use the ITD of the stimulus carrier frequency over nearly their entire hearing range, mammals have to utilize the ITD of the stimulus envelope to extend the upper frequency limit of ITD-based sound localization. ITD is computed and processed in a dedicated neural circuit that consists of two pathways. In the barn owl, ITD representation is more complex in the forebrain than in the midbrain pathway because of the combination of two inputs that represent different ITDs. We speculated that one of the two inputs includes an envelope contribution. To estimate the envelope contribution, we recorded ITD response functions for correlated and anticorrelated noise stimuli in the barn owl's auditory arcopallium. Our findings indicate that barn owls, like mammals, represent both carrier and envelope ITDs of overlapping frequency ranges, supporting the hypothesis that carrier and envelope ITD-based localization are complementary beyond a mere extension of the upper frequency limit. NEW & NOTEWORTHY The results presented in this study show for the first time that the barn owl is able to extract and represent the interaural time difference (ITD) information conveyed by the envelope of a broadband acoustic signal. Like mammals, the barn owl extracts the ITD of the envelope and the carrier of a signal from the same frequency range. These results are of general interest, since they reinforce a trend found in neural signal processing across different species. Copyright © 2017 the American Physiological Society.

Coarse-to-Fine Encoding of Spatial Frequency Information into Visual Short-Term Memory for Faces but Impartial Decay

ERIC Educational Resources Information Center

Gao, Zaifeng; Bentin, Shlomo

2011-01-01

Face perception studies investigated how spatial frequencies (SF) are extracted from retinal display while forming a perceptual representation, or their selective use during task-imposed categorization. Here we focused on the order of encoding low-spatial frequencies (LSF) and high-spatial frequencies (HSF) from perceptual representations into…

Algorithms for computing the time-corrected instantaneous frequency (reassigned) spectrogram, with applications.

PubMed

Fulop, Sean A; Fitz, Kelly

2006-01-01

A modification of the spectrogram (log magnitude of the short-time Fourier transform) to more accurately show the instantaneous frequencies of signal components was first proposed in 1976 [Kodera et al., Phys. Earth Planet. Inter. 12, 142-150 (1976)], and has been considered or reinvented a few times since but never widely adopted. This paper presents a unified theoretical picture of this time-frequency analysis method, the time-corrected instantaneous frequency spectrogram, together with detailed implementable algorithms comparing three published techniques for its computation. The new representation is evaluated against the conventional spectrogram for its superior ability to track signal components. The lack of a uniform framework for either mathematics or implementation details which has characterized the disparate literature on the schemes has been remedied here. Fruitful application of the method is shown in the realms of speech phonation analysis, whale song pitch tracking, and additive sound modeling.

Commercial bus crashes in North Carolina 1995-1999

DOT National Transportation Integrated Search

2000-04-01

Tables and figures are shown to depict a statistical representation of commercial bus crashes in North Carolina. Information displayed includes crash frequency, crashes by county, accident severity, time of day, month of the year, class of roadway, r...

Multisensor signal denoising based on matching synchrosqueezing wavelet transform for mechanical fault condition assessment

NASA Astrophysics Data System (ADS)

Yi, Cancan; Lv, Yong; Xiao, Han; Huang, Tao; You, Guanghui

2018-04-01

Since it is difficult to obtain the accurate running status of mechanical equipment with only one sensor, multisensor measurement technology has attracted extensive attention. In the field of mechanical fault diagnosis and condition assessment based on vibration signal analysis, multisensor signal denoising has emerged as an important tool to improve the reliability of the measurement result. A reassignment technique termed the synchrosqueezing wavelet transform (SWT) has obvious superiority in slow time-varying signal representation and denoising for fault diagnosis applications. The SWT uses the time-frequency reassignment scheme, which can provide signal properties in 2D domains (time and frequency). However, when the measured signal contains strong noise components and fast varying instantaneous frequency, the performance of SWT-based analysis still depends on the accuracy of instantaneous frequency estimation. In this paper, a matching synchrosqueezing wavelet transform (MSWT) is investigated as a potential candidate to replace the conventional synchrosqueezing transform for the applications of denoising and fault feature extraction. The improved technology utilizes the comprehensive instantaneous frequency estimation by chirp rate estimation to achieve a highly concentrated time-frequency representation so that the signal resolution can be significantly improved. To exploit inter-channel dependencies, the multisensor denoising strategy is performed by using a modulated multivariate oscillation model to partition the time-frequency domain; then, the common characteristics of the multivariate data can be effectively identified. Furthermore, a modified universal threshold is utilized to remove noise components, while the signal components of interest can be retained. Thus, a novel MSWT-based multisensor signal denoising algorithm is proposed in this paper. The validity of this method is verified by numerical simulation, and experiments including a rolling bearing system and a gear system. The results show that the proposed multisensor matching synchronous squeezing wavelet transform (MMSWT) is superior to existing methods.

The temporal representation of the delay of dynamic iterated rippled noise with positive and negative gain by single units in the ventral cochlear nucleus.

PubMed

Sayles, Mark; Winter, Ian Michael

2007-09-26

Spike trains were recorded from single units in the ventral cochlear nucleus of the anaesthetised guinea-pig in response to dynamic iterated rippled noise with positive and negative gain. The short-term running waveform autocorrelation functions of these stimuli show peaks at integer multiples of the time-varying delay when the gain is +1, and troughs at odd-integer multiples and peaks at even-integer multiples of the time-varying delay when the gain is -1. In contrast, the short-term autocorrelation of the Hilbert envelope shows peaks at integer multiples of the time-varying delay for both positive and negative gain stimuli. A running short-term all-order interspike interval analysis demonstrates the ability of single units to represent the modulated pitch contour in their short-term interval statistics. For units with low best frequency (approximate < or = 1.1 kHz) the temporal discharge pattern reflected the waveform fine structure regardless of unit classification (Primary-like, Chopper). For higher best frequency units the pattern of response varied according to unit type. Chopper units with best frequency approximate > or = 1.1 kHz responded to envelope modulation; showing no difference between their response to stimuli with positive and negative gain. Primary-like units with best frequencies in the range 1-3 kHz were still able to represent the difference in the temporal fine structure between dynamic rippled noise with positive and negative gain. No unit with a best frequency above 3 kHz showed a response to the temporal fine structure. Chopper units in this high frequency group showed significantly greater representation of envelope modulation relative to primary-like units with the same range of best frequencies. These results show that at the level of the cochlear nucleus there exists sufficient information in the time domain to represent the time-varying pitch associated with dynamic iterated rippled noise.

A time-frequency classifier for human gait recognition

NASA Astrophysics Data System (ADS)

Mobasseri, Bijan G.; Amin, Moeness G.

2009-05-01

Radar has established itself as an effective all-weather, day or night sensor. Radar signals can penetrate walls and provide information on moving targets. Recently, radar has been used as an effective biometric sensor for classification of gait. The return from a coherent radar system contains a frequency offset in the carrier frequency, known as the Doppler Effect. The movements of arms and legs give rise to micro Doppler which can be clearly detailed in the time-frequency domain using traditional or modern time-frequency signal representation. In this paper we propose a gait classifier based on subspace learning using principal components analysis(PCA). The training set consists of feature vectors defined as either time or frequency snapshots taken from the spectrogram of radar backscatter. We show that gait signature is captured effectively in feature vectors. Feature vectors are then used in training a minimum distance classifier based on Mahalanobis distance metric. Results show that gait classification with high accuracy and short observation window is achievable using the proposed classifier.

A hybrid approach to fault diagnosis of roller bearings under variable speed conditions

NASA Astrophysics Data System (ADS)

Wang, Yanxue; Yang, Lin; Xiang, Jiawei; Yang, Jianwei; He, Shuilong

2017-12-01

Rolling element bearings are one of the main elements in rotating machines, whose failure may lead to a fatal breakdown and significant economic losses. Conventional vibration-based diagnostic methods are based on the stationary assumption, thus they are not applicable to the diagnosis of bearings working under varying speeds. This constraint limits the bearing diagnosis to the industrial application significantly. A hybrid approach to fault diagnosis of roller bearings under variable speed conditions is proposed in this work, based on computed order tracking (COT) and variational mode decomposition (VMD)-based time frequency representation (VTFR). COT is utilized to resample the non-stationary vibration signal in the angular domain, while VMD is used to decompose the resampled signal into a number of band-limited intrinsic mode functions (BLIMFs). A VTFR is then constructed based on the estimated instantaneous frequency and instantaneous amplitude of each BLIMF. Moreover, the Gini index and time-frequency kurtosis are both proposed to quantitatively measure the sparsity and concentration measurement of time-frequency representation, respectively. The effectiveness of the VTFR for extracting nonlinear components has been verified by a bat signal. Results of this numerical simulation also show the sparsity and concentration of the VTFR are better than those of short-time Fourier transform, continuous wavelet transform, Hilbert-Huang transform and Wigner-Ville distribution techniques. Several experimental results have further demonstrated that the proposed method can well detect bearing faults under variable speed conditions.

Individual Differences in the Frequency-Following Response: Relation to Pitch Perception

PubMed Central

Coffey, Emily B. J.; Colagrosso, Emilia M. G.; Lehmann, Alexandre; Schönwiesner, Marc; Zatorre, Robert J.

2016-01-01

The scalp-recorded frequency-following response (FFR) is a measure of the auditory nervous system’s representation of periodic sound, and may serve as a marker of training-related enhancements, behavioural deficits, and clinical conditions. However, FFRs of healthy normal subjects show considerable variability that remains unexplained. We investigated whether the FFR representation of the frequency content of a complex tone is related to the perception of the pitch of the fundamental frequency. The strength of the fundamental frequency in the FFR of 39 people with normal hearing was assessed when they listened to complex tones that either included or lacked energy at the fundamental frequency. We found that the strength of the fundamental representation of the missing fundamental tone complex correlated significantly with people's general tendency to perceive the pitch of the tone as either matching the frequency of the spectral components that were present, or that of the missing fundamental. Although at a group level the fundamental representation in the FFR did not appear to be affected by the presence or absence of energy at the same frequency in the stimulus, the two conditions were statistically distinguishable for some subjects individually, indicating that the neural representation is not linearly dependent on the stimulus content. In a second experiment using a within-subjects paradigm, we showed that subjects can learn to reversibly select between either fundamental or spectral perception, and that this is accompanied both by changes to the fundamental representation in the FFR and to cortical-based gamma activity. These results suggest that both fundamental and spectral representations coexist, and are available for later auditory processing stages, the requirements of which may also influence their relative strength and thus modulate FFR variability. The data also highlight voluntary mode perception as a new paradigm with which to study top-down vs bottom-up mechanisms that support the emerging view of the FFR as the outcome of integrated processing in the entire auditory system. PMID:27015271

Wavelet Analyses of F/A-18 Aeroelastic and Aeroservoelastic Flight Test Data

NASA Technical Reports Server (NTRS)

Brenner, Martin J.

1997-01-01

Time-frequency signal representations combined with subspace identification methods were used to analyze aeroelastic flight data from the F/A-18 Systems Research Aircraft (SRA) and aeroservoelastic data from the F/A-18 High Alpha Research Vehicle (HARV). The F/A-18 SRA data were produced from a wingtip excitation system that generated linear frequency chirps and logarithmic sweeps. HARV data were acquired from digital Schroeder-phased and sinc pulse excitation signals to actuator commands. Nondilated continuous Morlet wavelets implemented as a filter bank were chosen for the time-frequency analysis to eliminate phase distortion as it occurs with sliding window discrete Fourier transform techniques. Wavelet coefficients were filtered to reduce effects of noise and nonlinear distortions identically in all inputs and outputs. Cleaned reconstructed time domain signals were used to compute improved transfer functions. Time and frequency domain subspace identification methods were applied to enhanced reconstructed time domain data and improved transfer functions, respectively. Time domain subspace performed poorly, even with the enhanced data, compared with frequency domain techniques. A frequency domain subspace method is shown to produce better results with the data processed using the Morlet time-frequency technique.

Time-domain representation of frequency-dependent foundation impedance functions

USGS Publications Warehouse

Safak, E.

2006-01-01

Foundation impedance functions provide a simple means to account for soil-structure interaction (SSI) when studying seismic response of structures. Impedance functions represent the dynamic stiffness of the soil media surrounding the foundation. The fact that impedance functions are frequency dependent makes it difficult to incorporate SSI in standard time-history analysis software. This paper introduces a simple method to convert frequency-dependent impedance functions into time-domain filters. The method is based on the least-squares approximation of impedance functions by ratios of two complex polynomials. Such ratios are equivalent, in the time-domain, to discrete-time recursive filters, which are simple finite-difference equations giving the relationship between foundation forces and displacements. These filters can easily be incorporated into standard time-history analysis programs. Three examples are presented to show the applications of the method.

A time-frequency approach for the analysis of normal and arrhythmia cardiac signals.

PubMed

Mahmoud, Seedahmed S; Fang, Qiang; Davidović, Dragomir M; Cosic, Irena

2006-01-01

Previously, electrocardiogram (ECG) signals have been analyzed in either a time-indexed or spectral form. The reality, is that the ECG and all other biological signals belong to the family of multicomponent nonstationary signals. Due to this reason, the use of time-frequency analysis can be unavoidable for these signals. The Husimi and Wigner distributions are normally used in quantum mechanics for phase space representations of the wavefunction. In this paper, we introduce the Husimi distribution (HD) to analyze the normal and abnormal ECG signals in time-frequency domain. The abnormal cardiac signal was taken from a patient with supraventricular arrhythmia. Simulation results show that the HD has a good performance in the analysis of the ECG signals comparing with the Wigner-Ville distribution (WVD).

Automated segmentation of linear time-frequency representations of marine-mammal sounds.

PubMed

Dadouchi, Florian; Gervaise, Cedric; Ioana, Cornel; Huillery, Julien; Mars, Jérôme I

2013-09-01

Many marine mammals produce highly nonlinear frequency modulations. Determining the time-frequency support of these sounds offers various applications, which include recognition, localization, and density estimation. This study introduces a low parameterized automated spectrogram segmentation method that is based on a theoretical probabilistic framework. In the first step, the background noise in the spectrogram is fitted with a Chi-squared distribution and thresholded using a Neyman-Pearson approach. In the second step, the number of false detections in time-frequency regions is modeled as a binomial distribution, and then through a Neyman-Pearson strategy, the time-frequency bins are gathered into regions of interest. The proposed method is validated on real data of large sequences of whistles from common dolphins, collected in the Bay of Biscay (France). The proposed method is also compared with two alternative approaches: the first is smoothing and thresholding of the spectrogram; the second is thresholding of the spectrogram followed by the use of morphological operators to gather the time-frequency bins and to remove false positives. This method is shown to increase the probability of detection for the same probability of false alarms.

Double Fourier analysis for Emotion Identification in Voiced Speech

NASA Astrophysics Data System (ADS)

Sierra-Sosa, D.; Bastidas, M.; Ortiz P., D.; Quintero, O. L.

2016-04-01

We propose a novel analysis alternative, based on two Fourier Transforms for emotion recognition from speech. Fourier analysis allows for display and synthesizes different signals, in terms of power spectral density distributions. A spectrogram of the voice signal is obtained performing a short time Fourier Transform with Gaussian windows, this spectrogram portraits frequency related features, such as vocal tract resonances and quasi-periodic excitations during voiced sounds. Emotions induce such characteristics in speech, which become apparent in spectrogram time-frequency distributions. Later, the signal time-frequency representation from spectrogram is considered an image, and processed through a 2-dimensional Fourier Transform in order to perform the spatial Fourier analysis from it. Finally features related with emotions in voiced speech are extracted and presented.

Spatial frequency supports the emergence of categorical representations in visual cortex during natural scene perception.

PubMed

Dima, Diana C; Perry, Gavin; Singh, Krish D

2018-06-11

In navigating our environment, we rapidly process and extract meaning from visual cues. However, the relationship between visual features and categorical representations in natural scene perception is still not well understood. Here, we used natural scene stimuli from different categories and filtered at different spatial frequencies to address this question in a passive viewing paradigm. Using representational similarity analysis (RSA) and cross-decoding of magnetoencephalography (MEG) data, we show that categorical representations emerge in human visual cortex at ∼180 ms and are linked to spatial frequency processing. Furthermore, dorsal and ventral stream areas reveal temporally and spatially overlapping representations of low and high-level layer activations extracted from a feedforward neural network. Our results suggest that neural patterns from extrastriate visual cortex switch from low-level to categorical representations within 200 ms, highlighting the rapid cascade of processing stages essential in human visual perception. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Detection of physiological changes after exercise via a remote optophysiological imaging system

NASA Astrophysics Data System (ADS)

Sun, Yu; Hu, Sijung; Azorin-Peris, Vicente; Zheng, Jia; Greenwald, Stephen; Chambers, Jonathon; Zhu, Yisheng

2011-03-01

A study of blood perfusion mapping was performed with a remote opto-physiological imaging (OPI) system coupling a sensitive CMOS camera and a custom-built resonant cavity light emitting diode (RCLED) ringlight. The setup is suitable for the remote assessment of blood perfusion in tissue over a wide range of anatomical locations. The purpose of this study is to evaluate the reliability and stability of the OPI system when measuring a cardiovascular variable of clinical interest, in this case, heart rate. To this end, the non-contact and contact photoplethysmographic (PPG) signals obtained from the OPI system and conventional PPG sensor were recorded simultaneously from each of 12 subjects before and after 5-min of cycling exercise. The time-frequency representation (TFR) method was used to visualize the time-dependent behavior of the signal frequency. The physiological parameters derived from the images captured by the OPI system exhibit comparable functional characteristics to those taken from conventional contact PPG pulse waveform measurements in both the time and frequency domains. Finally and more importantly, a previously developed opto-physiological model was employed to provide a 3-D representation of blood perfusion in human tissue which could provide a new insight into clinical assessment and diagnosis of circulatory pathology in various tissue segments.

On Holo-Hilbert spectral analysis: a full informational spectral representation for nonlinear and non-stationary data

PubMed Central

Huang, Norden E.; Hu, Kun; Yang, Albert C. C.; Chang, Hsing-Chih; Jia, Deng; Liang, Wei-Kuang; Yeh, Jia Rong; Kao, Chu-Lan; Juan, Chi-Hung; Peng, Chung Kang; Meijer, Johanna H.; Wang, Yung-Hung; Long, Steven R.; Wu, Zhauhua

2016-01-01

The Holo-Hilbert spectral analysis (HHSA) method is introduced to cure the deficiencies of traditional spectral analysis and to give a full informational representation of nonlinear and non-stationary data. It uses a nested empirical mode decomposition and Hilbert–Huang transform (HHT) approach to identify intrinsic amplitude and frequency modulations often present in nonlinear systems. Comparisons are first made with traditional spectrum analysis, which usually achieved its results through convolutional integral transforms based on additive expansions of an a priori determined basis, mostly under linear and stationary assumptions. Thus, for non-stationary processes, the best one could do historically was to use the time–frequency representations, in which the amplitude (or energy density) variation is still represented in terms of time. For nonlinear processes, the data can have both amplitude and frequency modulations (intra-mode and inter-mode) generated by two different mechanisms: linear additive or nonlinear multiplicative processes. As all existing spectral analysis methods are based on additive expansions, either a priori or adaptive, none of them could possibly represent the multiplicative processes. While the earlier adaptive HHT spectral analysis approach could accommodate the intra-wave nonlinearity quite remarkably, it remained that any inter-wave nonlinear multiplicative mechanisms that include cross-scale coupling and phase-lock modulations were left untreated. To resolve the multiplicative processes issue, additional dimensions in the spectrum result are needed to account for the variations in both the amplitude and frequency modulations simultaneously. HHSA accommodates all the processes: additive and multiplicative, intra-mode and inter-mode, stationary and non-stationary, linear and nonlinear interactions. The Holo prefix in HHSA denotes a multiple dimensional representation with both additive and multiplicative capabilities. PMID:26953180

Best chirplet chain: Near-optimal detection of gravitational wave chirps

NASA Astrophysics Data System (ADS)

Chassande-Mottin, Éric; Pai, Archana

2006-02-01

The list of putative sources of gravitational waves possibly detected by the ongoing worldwide network of large scale interferometers has been continuously growing in the last years. For some of them, the detection is made difficult by the lack of a complete information about the expected signal. We concentrate on the case where the expected gravitational wave (GW) is a quasiperiodic frequency modulated signal i.e., a chirp. In this article, we address the question of detecting an a priori unknown GW chirp. We introduce a general chirp model and claim that it includes all physically realistic GW chirps. We produce a finite grid of template waveforms which samples the resulting set of possible chirps. If we follow the classical approach (used for the detection of inspiralling binary chirps, for instance), we would build a bank of quadrature matched filters comparing the data to each of the templates of this grid. The detection would then be achieved by thresholding the output, the maximum giving the individual which best fits the data. In the present case, this exhaustive search is not tractable because of the very large number of templates in the grid. We show that the exhaustive search can be reformulated (using approximations) as a pattern search in the time-frequency plane. This motivates an approximate but feasible alternative solution which is clearly linked to the optimal one. The time-frequency representation and pattern search algorithm are fully determined by the reformulation. This contrasts with the other time-frequency based methods presented in the literature for the same problem, where these choices are justified by “ad hoc” arguments. In particular, the time-frequency representation has to be unitary. Finally, we assess the performance, robustness and computational cost of the proposed method with several benchmarks using simulated data.

Automatic classification of sleep stages based on the time-frequency image of EEG signals.

PubMed

Bajaj, Varun; Pachori, Ram Bilas

2013-12-01

In this paper, a new method for automatic sleep stage classification based on time-frequency image (TFI) of electroencephalogram (EEG) signals is proposed. Automatic classification of sleep stages is an important part for diagnosis and treatment of sleep disorders. The smoothed pseudo Wigner-Ville distribution (SPWVD) based time-frequency representation (TFR) of EEG signal has been used to obtain the time-frequency image (TFI). The segmentation of TFI has been performed based on the frequency-bands of the rhythms of EEG signals. The features derived from the histogram of segmented TFI have been used as an input feature set to multiclass least squares support vector machines (MC-LS-SVM) together with the radial basis function (RBF), Mexican hat wavelet, and Morlet wavelet kernel functions for automatic classification of sleep stages from EEG signals. The experimental results are presented to show the effectiveness of the proposed method for classification of sleep stages from EEG signals. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Effects of rail dynamics and friction characteristics on curve squeal

NASA Astrophysics Data System (ADS)

Ding, B.; Squicciarini, G.; Thompson, D. J.

2016-09-01

Curve squeal in railway vehicles is an instability mechanism that arises in tight curves under certain running and environmental conditions. In developing a model the most important elements are the characterisation of friction coupled with an accurate representation of the structural dynamics of the wheel. However, the role played by the dynamics of the rail is not fully understood and it is unclear whether this should be included in a model or whether it can be safely neglected. This paper makes use of previously developed time domain and frequency domain curve squeal models to assess whether the presence of the rail and the falling characteristics of the friction force can modify the instability mechanisms and the final response. For this purpose, the time-domain model has been updated to include the rail dynamics in terms of its state space representation in various directions. Frequency domain and time domain analyses results show that falling friction is not the only reason for squeal and rail dynamics can play an important role, especially under constant friction conditions.

Seismic event classification system

DOEpatents

Dowla, F.U.; Jarpe, S.P.; Maurer, W.

1994-12-13

In the computer interpretation of seismic data, the critical first step is to identify the general class of an unknown event. For example, the classification might be: teleseismic, regional, local, vehicular, or noise. Self-organizing neural networks (SONNs) can be used for classifying such events. Both Kohonen and Adaptive Resonance Theory (ART) SONNs are useful for this purpose. Given the detection of a seismic event and the corresponding signal, computation is made of: the time-frequency distribution, its binary representation, and finally a shift-invariant representation, which is the magnitude of the two-dimensional Fourier transform (2-D FFT) of the binary time-frequency distribution. This pre-processed input is fed into the SONNs. These neural networks are able to group events that look similar. The ART SONN has an advantage in classifying the event because the types of cluster groups do not need to be pre-defined. The results from the SONNs together with an expert seismologist's classification are then used to derive event classification probabilities. 21 figures.

Seismic event classification system

DOEpatents

Dowla, Farid U.; Jarpe, Stephen P.; Maurer, William

1994-01-01

In the computer interpretation of seismic data, the critical first step is to identify the general class of an unknown event. For example, the classification might be: teleseismic, regional, local, vehicular, or noise. Self-organizing neural networks (SONNs) can be used for classifying such events. Both Kohonen and Adaptive Resonance Theory (ART) SONNs are useful for this purpose. Given the detection of a seismic event and the corresponding signal, computation is made of: the time-frequency distribution, its binary representation, and finally a shift-invariant representation, which is the magnitude of the two-dimensional Fourier transform (2-D FFT) of the binary time-frequency distribution. This pre-processed input is fed into the SONNs. These neural networks are able to group events that look similar. The ART SONN has an advantage in classifying the event because the types of cluster groups do not need to be pre-defined. The results from the SONNs together with an expert seismologist's classification are then used to derive event classification probabilities.

Time-Frequency Representations for Speech Signals.

DTIC Science & Technology

1987-06-01

and subsequent processing can take these weights into account . This is, in principle , safer, but pratically it is much harder to think about processing...and frequency along the other. But how should this idea be made precise (the well-known uncertainty principle of fourier analysis is one of the thorny...produce similar results. q2.3. Non-stationarity 19 it is the unique shape that meets the uncertainty principle with equality. 2.2. The quasi-stationary

Seismic spectrograms analysis applying the Hough transform to estimate the front speed of mass movements: Application to snow avalanches

NASA Astrophysics Data System (ADS)

Flores-Marquez, L.; Suriñach-Cornet, E., Sr.

2017-12-01

Seismic signals generated by snow avalanches and other mass movements are analyzed in their spectrogram representation. Spectrogram displays the evolution in time of the frequency content of the signals. The spectrogram of a seismic signal of a station to which a sliding mass, such as a snow avalanche, approaches, exhibits a triangular time / frequency signature. This increase in its higher frequency content over time is a consequence of the attenuation of the waves propagating in a media. Recognition of characteristic footprints in a spectrogram could help to identify and characterize diverse mass movement events such as landslides or snow avalanches. In order to recognize spectrogram features of seismic signals of Alpine snow avalanches, we propose an algorithm based on the Hough transform. The proposed algorithm is applied on an edge representation image of the seismic spectrogram obtained after fixing a threshold filter to the spectrogram, which enhances the most interesting frequencies of the seismogram that appear over time. This enables us to identify parameters (slopes) that correspond to the speeds associated with the type of snow avalanches, such as, powder, dense or transitional snow avalanches. The data analyzed in this work correspond to twenty different seismic signals generated by snow avalanches artificially released in the experimental site of Vallée de la Sionne (VDLS, SLF, Switzerland). The shape of the signal spectrograms are linked to the flow regimes previously identified. Our findings show that some ranges of speeds are inherent to the type of avalanche.

Time-frequency characterisation of paediatric heart sounds

NASA Astrophysics Data System (ADS)

Leung, Terence Sze-Tat

1998-08-01

The operation of the heart can be monitored by the sounds it emits. Structural defects or malfunction of the heart valves will cause additional abnormal sounds such as murmurs and ejection clicks. This thesis aims to characterise the heart sounds of three groups of children who either have an Atrial Septal Defect (ASD), a Ventricular Septal Defect (VSD), or are normal. Two aspects of heart sounds have been specifically investigated; the time-frequency analysis of systolic murmurs and the identification of splitting patterns in the second heart sound. The analysis is based on 42 paediatric heart sound recordings. Murmurs are sounds generated by turbulent flow of blood in the heart. They can be found in patients with both pathological and non-pathological conditions. The acoustic quality of the murmurs generated in each heart condition are different. The first aspect of this work is to characterise the three types of murmurs in the time- frequency domain. Modern time-frequency methods including, the Wigner-Ville Distribution, Smoothed Pseudo Wigner-Ville Distribution, Choi-Williams Distribution and spectrogram have been applied to characterise the murmurs. It was found that the three classes of murmurs exhibited different signatures in their time-frequency representations. By performing Discriminant Analysis, it was shown that spectral features extracted from the time- frequency representations can be used to distinguish between the three classes. The second aspect of the research is to identify splitting patterns in the second heart sound, which consists of two acoustic components due to the closure of the aortic valve and pulmonary valve. The aortic valve usually closes before the pulmonary valve, introducing a time delay known as 'split'. The split normally varies in duration over the respiratory cycle. In certain pathologies such as the ASD, the split becomes fixed over the respiration cycle. A technique based on adaptive signal decomposition is developed to measure the split and hence to identify the splitting pattern as either 'variable' or 'fixed'. This work has successfully characterised the murmurs and splitting patterns in the three groups of patients. Features extracted can be used for diagnostic purposes.

Source localization of non-stationary acoustic data using time-frequency analysis

NASA Astrophysics Data System (ADS)

Stoughton, Jack; Edmonson, William

2005-04-01

An improvement in temporal locality of the generalized cross-correlation (GCC) for angle of arrival (AOA) estimation can be achieved by employing 2-D cross-correlation of infrasonic sensor data transformed to its time-frequency (TF) representation. Intermediate to the AOA evaluation is the time delay between pairs of sensors. The signal class of interest includes far field sources which are partially coherent across the array, nonstationary, and wideband. In addition, signals can occur as multiple short bursts, for which TF representations may be more appropriate for time delay estimation. The GCC tends to smooth out such temporal energy bursts. Simulation and experimental results will demonstrate the improvement in using a TF-based GCC, using the Cohen class, over the classic GCC method. Comparative demonstration of the methods will be performed on data captured on an infrasonic sensor array located at NASA Langley Research Center (LaRC). The infrasonic data sources include Delta IV and Space Shuttle launches from Kennedy Space Center which belong to the stated signal class. Of interest is to apply this method to the AOA estimation of atmospheric turbulence. [Work supported by NASA LaRC Creativity and Innovation project: Infrasonic Detection of Clear Air Turbulence and Severe Storms.

Aurally-adequate time-frequency analysis for scattered sound in auditoria

NASA Astrophysics Data System (ADS)

Norris, Molly K.; Xiang, Ning; Kleiner, Mendel

2005-04-01

The goal of this work was to apply an aurally-adequate time-frequency analysis technique to the analysis of sound scattering effects in auditoria. Time-frequency representations were developed as a motivated effort that takes into account binaural hearing, with a specific implementation of interaural cross-correlation process. A model of the human auditory system was implemented in the MATLAB platform based on two previous models [A. Härmä and K. Palomäki, HUTear, Espoo, Finland; and M. A. Akeroyd, A. Binaural Cross-correlogram Toolbox for MATLAB (2001), University of Sussex, Brighton]. These stages include proper frequency selectivity, the conversion of the mechanical motion of the basilar membrane to neural impulses, and binaural hearing effects. The model was then used in the analysis of room impulse responses with varying scattering characteristics. This paper discusses the analysis results using simulated and measured room impulse responses. [Work supported by the Frank H. and Eva B. Buck Foundation.

Considering the influence of artificial environmental noise to study cough time-frequency features

NASA Astrophysics Data System (ADS)

Van Hirtum, A.; Berckmans, D.

2003-09-01

In general the study of the cough mechanism and sound in both animal and human is performed by eliciting coughing in a reproducible way by nebulization of an irritating substance. Due to ventilation the controlled evaporation-protocol causes artificial noises from a mechanical origin. The resulting environmental low-frequency noises complicate cough time-frequency features. In order to optimize the study of the cough-sound the research described in this paper attempts on the one hand to characterize and model the environmental noises and on the other hand to evaluate the influence of the noise on the time-frequency representation for the intended cough sounds by comparing different de-noising approaches. Free field acoustic sound is continuously registered during 30 min citric acid cough-challenges on individual Belgian Landrace piglets and during respiratory infection experiments, with a duration of about 10 days, where room-ventilation was present.

Multiscale wavelet representations for mammographic feature analysis

NASA Astrophysics Data System (ADS)

Laine, Andrew F.; Song, Shuwu

1992-12-01

This paper introduces a novel approach for accomplishing mammographic feature analysis through multiresolution representations. We show that efficient (nonredundant) representations may be identified from digital mammography and used to enhance specific mammographic features within a continuum of scale space. The multiresolution decomposition of wavelet transforms provides a natural hierarchy in which to embed an interactive paradigm for accomplishing scale space feature analysis. Choosing wavelets (or analyzing functions) that are simultaneously localized in both space and frequency, results in a powerful methodology for image analysis. Multiresolution and orientation selectivity, known biological mechanisms in primate vision, are ingrained in wavelet representations and inspire the techniques presented in this paper. Our approach includes local analysis of complete multiscale representations. Mammograms are reconstructed from wavelet coefficients, enhanced by linear, exponential and constant weight functions localized in scale space. By improving the visualization of breast pathology we can improve the changes of early detection of breast cancers (improve quality) while requiring less time to evaluate mammograms for most patients (lower costs).

Genomic variant representation in a Chlamydia population is dynamic and adaptive with dependence on in vitro and in vivo passage.

PubMed

Jasper, Deana K; Sigar, Ira M; Schripsema, Justin H; Sainvil, Carlyn K; Smith, Christopher L; Yeruva, Laxmi; Rank, Roger G; Murthy, Ashlesh K; Widder, Jared R; Ramsey, Kyle H

2015-02-01

We have previously shown that Chlamydia muridarum has multiple genomic variants that concomitantly vary in their in vitro and in vivo phenotype. Herein, we used real-time polymerase chain reaction-based genotyping assays to query plaque-cloned isolates of C. muridarum for the frequency of eight selected polymorphisms. These strains had no history of passage in vivo since their original isolation from laboratory mice. There was significant variance in the frequency of two of the eight polymorphisms assessed with the remaining exhibiting a low rate of variance. To determine if any of these polymorphisms were more favorable for in vivo conditions, we blindly passaged non-clonal C. muridarum three times at 7-day intervals through the urogenital tract of mice. Seven of the eight polymorphisms varied in frequency following in vivo passage and four of these varied between C. muridarum strains. Selected isolates displayed variable growth rates and cytopathic effect in vitro. We conclude that multiple genotypic variants are present within the existing known C. muridarum strains and that the frequency of these variants changes upon introduction into the mouse host. These findings lend support to the concept that genotypic proportional representation in a chlamydial population is dynamic and adaptive. © The Author 2015. Published by Oxford University Press on behalf of on behalf of Federation of European Microbiological Society.

Physiological effects of indomethacin and celecobix: an S-transform laser Doppler flowmetry signal analysis

NASA Astrophysics Data System (ADS)

Assous, S.; Humeau, A.; Tartas, M.; Abraham, P.; L'Huillier, J. P.

2005-05-01

Conventional signal processing typically involves frequency selective techniques which are highly inadequate for nonstationary signals. In this paper, we present an approach to perform time-frequency selective processing of laser Doppler flowmetry (LDF) signals using the S-transform. The approach is motivated by the excellent localization, in both time and frequency, afforded by the wavelet basis functions. Suitably chosen Gaussian wavelet functions are used to characterize the subspace of signals that have a given localized time-frequency support, thus enabling a time-frequency partitioning of signals. In this paper, the goal is to study the influence of various pharmacological substances taken by the oral way (celecobix (Celebrex®), indomethacin (Indocid®) and placebo) on the physiological activity behaviour. The results show that no statistical differences are observed in the energy computed from the time-frequency representation of LDF signals, for the myogenic, neurogenic and endothelial related metabolic activities between Celebrex and placebo, and Indocid and placebo. The work therefore proves that these drugs do not affect these physiological activities. For future physiological studies, there will therefore be no need to exclude patients having taken cyclo-oxygenase 1 inhibitions.

Granger Causality Testing with Intensive Longitudinal Data.

PubMed

Molenaar, Peter C M

2018-06-01

The availability of intensive longitudinal data obtained by means of ambulatory assessment opens up new prospects for prevention research in that it allows the derivation of subject-specific dynamic networks of interacting variables by means of vector autoregressive (VAR) modeling. The dynamic networks thus obtained can be subjected to Granger causality testing in order to identify causal relations among the observed time-dependent variables. VARs have two equivalent representations: standard and structural. Results obtained with Granger causality testing depend upon which representation is chosen, yet no criteria exist on which this important choice can be based. A new equivalent representation is introduced called hybrid VARs with which the best representation can be chosen in a data-driven way. Partial directed coherence, a frequency-domain statistic for Granger causality testing, is shown to perform optimally when based on hybrid VARs. An application to real data is provided.

Signals in Communication Engineering History

ERIC Educational Resources Information Center

Consonni, Denise; Silva, Magno T. M.

2010-01-01

This paper is a study of various electric signals, which have been employed throughout the history of communication engineering in its two main landmarks: the telegraph and the telephone. The signals are presented in their time and frequency domain representations. The historical order has been followed in the presentation: wired systems, spark…

Matching synchrosqueezing transform: A useful tool for characterizing signals with fast varying instantaneous frequency and application to machine fault diagnosis

NASA Astrophysics Data System (ADS)

Wang, Shibin; Chen, Xuefeng; Selesnick, Ivan W.; Guo, Yanjie; Tong, Chaowei; Zhang, Xingwu

2018-02-01

Synchrosqueezing transform (SST) can effectively improve the readability of the time-frequency (TF) representation (TFR) of nonstationary signals composed of multiple components with slow varying instantaneous frequency (IF). However, for signals composed of multiple components with fast varying IF, SST still suffers from TF blurs. In this paper, we introduce a time-frequency analysis (TFA) method called matching synchrosqueezing transform (MSST) that achieves a highly concentrated TF representation comparable to the standard TF reassignment methods (STFRM), even for signals with fast varying IF, and furthermore, MSST retains the reconstruction benefit of SST. MSST captures the philosophy of STFRM to simultaneously consider time and frequency variables, and incorporates three estimators (i.e., the IF estimator, the group delay estimator, and a chirp-rate estimator) into a comprehensive and accurate IF estimator. In this paper, we first introduce the motivation of MSST with three heuristic examples. Then we introduce a precise mathematical definition of a class of chirp-like intrinsic-mode-type functions that locally can be viewed as a sum of a reasonably small number of approximate chirp signals, and we prove that MSST does indeed succeed in estimating chirp-rate and IF of arbitrary functions in this class and succeed in decomposing these functions. Furthermore, we describe an efficient numerical algorithm for the practical implementation of the MSST, and we provide an adaptive IF extraction method for MSST reconstruction. Finally, we verify the effectiveness of the MSST in practical applications for machine fault diagnosis, including gearbox fault diagnosis for a wind turbine in variable speed conditions and rotor rub-impact fault diagnosis for a dual-rotor turbofan engine.

Phonological Awareness Deficits in Developmental Dyslexia and the Phonological Representations Hypothesis.

ERIC Educational Resources Information Center

Swan, Denise; Goswami, Usha

1997-01-01

Used picture-naming task to identify accurate/inaccurate phonological representations by dyslexic and control children; compared performance on phonological measures for words with precise/imprecise representations. Found that frequency effects in phonological tasks disappeared after considering representational quality, and that availability of…

Combined non-parametric and parametric approach for identification of time-variant systems

NASA Astrophysics Data System (ADS)

Dziedziech, Kajetan; Czop, Piotr; Staszewski, Wieslaw J.; Uhl, Tadeusz

2018-03-01

Identification of systems, structures and machines with variable physical parameters is a challenging task especially when time-varying vibration modes are involved. The paper proposes a new combined, two-step - i.e. non-parametric and parametric - modelling approach in order to determine time-varying vibration modes based on input-output measurements. Single-degree-of-freedom (SDOF) vibration modes from multi-degree-of-freedom (MDOF) non-parametric system representation are extracted in the first step with the use of time-frequency wavelet-based filters. The second step involves time-varying parametric representation of extracted modes with the use of recursive linear autoregressive-moving-average with exogenous inputs (ARMAX) models. The combined approach is demonstrated using system identification analysis based on the experimental mass-varying MDOF frame-like structure subjected to random excitation. The results show that the proposed combined method correctly captures the dynamics of the analysed structure, using minimum a priori information on the model.

Epileptic seizure classification of EEG time-series using rational discrete short-time fourier transform.

PubMed

Samiee, Kaveh; Kovács, Petér; Gabbouj, Moncef

2015-02-01

A system for epileptic seizure detection in electroencephalography (EEG) is described in this paper. One of the challenges is to distinguish rhythmic discharges from nonstationary patterns occurring during seizures. The proposed approach is based on an adaptive and localized time-frequency representation of EEG signals by means of rational functions. The corresponding rational discrete short-time Fourier transform (DSTFT) is a novel feature extraction technique for epileptic EEG data. A multilayer perceptron classifier is fed by the coefficients of the rational DSTFT in order to separate seizure epochs from seizure-free epochs. The effectiveness of the proposed method is compared with several state-of-art feature extraction algorithms used in offline epileptic seizure detection. The results of the comparative evaluations show that the proposed method outperforms competing techniques in terms of classification accuracy. In addition, it provides a compact representation of EEG time-series.

Target Identification Using Harmonic Wavelet Based ISAR Imaging

NASA Astrophysics Data System (ADS)

Shreyamsha Kumar, B. K.; Prabhakar, B.; Suryanarayana, K.; Thilagavathi, V.; Rajagopal, R.

2006-12-01

A new approach has been proposed to reduce the computations involved in the ISAR imaging, which uses harmonic wavelet-(HW) based time-frequency representation (TFR). Since the HW-based TFR falls into a category of nonparametric time-frequency (T-F) analysis tool, it is computationally efficient compared to parametric T-F analysis tools such as adaptive joint time-frequency transform (AJTFT), adaptive wavelet transform (AWT), and evolutionary AWT (EAWT). Further, the performance of the proposed method of ISAR imaging is compared with the ISAR imaging by other nonparametric T-F analysis tools such as short-time Fourier transform (STFT) and Choi-Williams distribution (CWD). In the ISAR imaging, the use of HW-based TFR provides similar/better results with significant (92%) computational advantage compared to that obtained by CWD. The ISAR images thus obtained are identified using a neural network-based classification scheme with feature set invariant to translation, rotation, and scaling.

The association of personal semantic memory to identity representations: insight into higher-order networks of autobiographical contents.

PubMed

Grilli, Matthew D

2017-11-01

Identity representations are higher-order knowledge structures that organise autobiographical memories on the basis of personality and role-based themes of one's self-concept. In two experiments, the extent to which different types of personal semantic content are reflected in these higher-order networks of memories was investigated. Healthy, young adult participants generated identity representations that varied in remoteness of formation and verbally reflected on these themes in an open-ended narrative task. The narrative responses were scored for retrieval of episodic, experience-near personal semantic and experience-far (i.e., abstract) personal semantic contents. Results revealed that to reflect on remotely formed identity representations, experience-far personal semantic contents were retrieved more than experience-near personal semantic contents. In contrast, to reflect on recently formed identity representations, experience-near personal semantic contents were retrieved more than experience-far personal semantic contents. Although episodic memory contents were retrieved less than both personal semantic content types to reflect on remotely formed identity representations, this content type was retrieved at a similar frequency as experience-far personal semantic content to reflect on recently formed identity representations. These findings indicate that the association of personal semantic content to identity representations is robust and related to time since acquisition of these knowledge structures.

Speech coding and compression using wavelets and lateral inhibitory networks

NASA Astrophysics Data System (ADS)

Ricart, Richard

1990-12-01

The purpose of this thesis is to introduce the concept of lateral inhibition as a generalized technique for compressing time/frequency representations of electromagnetic and acoustical signals, particularly speech. This requires at least a rudimentary treatment of the theory of frames- which generalizes most commonly known time/frequency distributions -the biology of hearing, and digital signal processing. As such, this material, along with the interrelationships of the disparate subjects, is presented in a tutorial style. This may leave the mathematician longing for more rigor, the neurophysiological psychologist longing for more substantive support of the hypotheses presented, and the engineer longing for a reprieve from the theoretical barrage. Despite the problems that arise when trying to appeal to too wide an audience, this thesis should be a cogent analysis of the compression of time/frequency distributions via lateral inhibitory networks.

Bayesian reconstruction of gravitational wave bursts using chirplets

NASA Astrophysics Data System (ADS)

Millhouse, Margaret; Cornish, Neil J.; Littenberg, Tyson

2018-05-01

The LIGO-Virgo Collaboration uses a variety of techniques to detect and characterize gravitational waves. One approach is to use templates—models for the signals derived from Einstein's equations. Another approach is to extract the signals directly from the coherent response of the detectors in the LIGO-Virgo network. Both approaches played an important role in the first gravitational wave detections. Here we extend the BayesWave analysis algorithm, which reconstructs gravitational wave signals using a collection of continuous wavelets, to use a generalized wavelet family, known as chirplets, that have time-evolving frequency content. Since generic gravitational wave signals have frequency content that evolves in time, a collection of chirplets provides a more compact representation of the signal, resulting in more accurate waveform reconstructions, especially for low signal-to-noise events, and events that occupy a large time-frequency volume.

Fault diagnosis for analog circuits utilizing time-frequency features and improved VVRKFA

NASA Astrophysics Data System (ADS)

He, Wei; He, Yigang; Luo, Qiwu; Zhang, Chaolong

2018-04-01

This paper proposes a novel scheme for analog circuit fault diagnosis utilizing features extracted from the time-frequency representations of signals and an improved vector-valued regularized kernel function approximation (VVRKFA). First, the cross-wavelet transform is employed to yield the energy-phase distribution of the fault signals over the time and frequency domain. Since the distribution is high-dimensional, a supervised dimensionality reduction technique—the bilateral 2D linear discriminant analysis—is applied to build a concise feature set from the distributions. Finally, VVRKFA is utilized to locate the fault. In order to improve the classification performance, the quantum-behaved particle swarm optimization technique is employed to gradually tune the learning parameter of the VVRKFA classifier. The experimental results for the analog circuit faults classification have demonstrated that the proposed diagnosis scheme has an advantage over other approaches.

Region Segmentation in the Frequency Domain Applied to Upper Airway Real-Time Magnetic Resonance Images

PubMed Central

Narayanan, Shrikanth

2009-01-01

We describe a method for unsupervised region segmentation of an image using its spatial frequency domain representation. The algorithm was designed to process large sequences of real-time magnetic resonance (MR) images containing the 2-D midsagittal view of a human vocal tract airway. The segmentation algorithm uses an anatomically informed object model, whose fit to the observed image data is hierarchically optimized using a gradient descent procedure. The goal of the algorithm is to automatically extract the time-varying vocal tract outline and the position of the articulators to facilitate the study of the shaping of the vocal tract during speech production. PMID:19244005

Gear fault diagnosis based on the structured sparsity time-frequency analysis

NASA Astrophysics Data System (ADS)

Sun, Ruobin; Yang, Zhibo; Chen, Xuefeng; Tian, Shaohua; Xie, Yong

2018-03-01

Over the last decade, sparse representation has become a powerful paradigm in mechanical fault diagnosis due to its excellent capability and the high flexibility for complex signal description. The structured sparsity time-frequency analysis (SSTFA) is a novel signal processing method, which utilizes mixed-norm priors on time-frequency coefficients to obtain a fine match for the structure of signals. In order to extract the transient feature from gear vibration signals, a gear fault diagnosis method based on SSTFA is proposed in this work. The steady modulation components and impulsive components of the defective gear vibration signals can be extracted simultaneously by choosing different time-frequency neighborhood and generalized thresholding operators. Besides, the time-frequency distribution with high resolution is obtained by piling different components in the same diagram. The diagnostic conclusion can be made according to the envelope spectrum of the impulsive components or by the periodicity of impulses. The effectiveness of the method is verified by numerical simulations, and the vibration signals registered from a gearbox fault simulator and a wind turbine. To validate the efficiency of the presented methodology, comparisons are made among some state-of-the-art vibration separation methods and the traditional time-frequency analysis methods. The comparisons show that the proposed method possesses advantages in separating feature signals under strong noise and accounting for the inner time-frequency structure of the gear vibration signals.

Weighted network analysis of high-frequency cross-correlation measures

NASA Astrophysics Data System (ADS)

Iori, Giulia; Precup, Ovidiu V.

2007-03-01

In this paper we implement a Fourier method to estimate high-frequency correlation matrices from small data sets. The Fourier estimates are shown to be considerably less noisy than the standard Pearson correlation measures and thus capable of detecting subtle changes in correlation matrices with just a month of data. The evolution of correlation at different time scales is analyzed from the full correlation matrix and its minimum spanning tree representation. The analysis is performed by implementing measures from the theory of random weighted networks.

Local spatial frequency analysis for computer vision

NASA Technical Reports Server (NTRS)

Krumm, John; Shafer, Steven A.

1990-01-01

A sense of vision is a prerequisite for a robot to function in an unstructured environment. However, real-world scenes contain many interacting phenomena that lead to complex images which are difficult to interpret automatically. Typical computer vision research proceeds by analyzing various effects in isolation (e.g., shading, texture, stereo, defocus), usually on images devoid of realistic complicating factors. This leads to specialized algorithms which fail on real-world images. Part of this failure is due to the dichotomy of useful representations for these phenomena. Some effects are best described in the spatial domain, while others are more naturally expressed in frequency. In order to resolve this dichotomy, we present the combined space/frequency representation which, for each point in an image, shows the spatial frequencies at that point. Within this common representation, we develop a set of simple, natural theories describing phenomena such as texture, shape, aliasing and lens parameters. We show these theories lead to algorithms for shape from texture and for dealiasing image data. The space/frequency representation should be a key aid in untangling the complex interaction of phenomena in images, allowing automatic understanding of real-world scenes.

Warped frequency transform analysis of ultrasonic guided waves in long bones

NASA Astrophysics Data System (ADS)

De Marchi, L.; Baravelli, E.; Xu, K.; Ta, D.; Speciale, N.; Marzani, A.; Viola, E.

2010-03-01

Long bones can be seen as irregular hollow tubes, in which, for a given excitation frequency, many ultrasonic Guided Waves (GWs) can propagate. The analysis of GWs is potential to reflect more information on both geometry and material properties of the bone than any other method (such as dual-energy X-ray absorptiometry, or quantitative computed tomography), and can be used in the assessment of osteoporosis and in the evaluation of fracture healing. In this study, time frequency representations (TFRs) were used to gain insights into the expected behavior of GWs in bones. To this aim, we implemented a dedicated Warped Frequency Transform (WFT) which decomposes the spectrotemporal components of the different propagating modes by selecting an appropriate warping map to reshape the frequency axis. The map can be designed once the GWs group velocity dispersion curves can be predicted. To this purpose, the bone is considered as a hollow cylinder with inner and outer diameter of 16.6 and 24.7 mm, respectively, and linear poroelastic material properties in agreement with the low level of stresses induced by the waves. Timetransient events obtained experimentally, via a piezoelectric ultrasonic set-up applied to bovine tibiae, are analyzed. The results show that WFT limits interference patterns which appear with others TFRs (such as scalograms or warpograms) and produces a sparse representation suitable for characterization purposes. In particular, the mode-frequency combinations propagating with minimal losses are identified.

Two-Dimensional Optical Processing Of One-Dimensional Acoustic Data

NASA Astrophysics Data System (ADS)

Szu, Harold H.

1982-10-01

The concept of carrier-mean-frequency-selective convolution is introduced to solve the undersea problem of passive acoustic surveillance (PAS) and compared with the conventional notion of difference-frequency Doppler-corrected correlation. The former results in the cross-Wigner distribution function (WD), and the latter results in the cross-ambiguity function (AF). When the persistent time of a sound emitter is more important than the characteristic tone of the sound emitter, WD will be more useful than AF for PAS activity detection, and vice versa. Their mutual relationships with the instantaneous power spectrum (IPS) show the importance of the phase information that must be kept in any 2-D representation of a 1 -D signal. If a square-law detector is used, or an unsymmetric version of WD or AF is gener-ated, then one must produce the other 2-D representations directly, rather than transform one to the other.

Adaptive eigenspace method for inverse scattering problems in the frequency domain

NASA Astrophysics Data System (ADS)

Grote, Marcus J.; Kray, Marie; Nahum, Uri

2017-02-01

A nonlinear optimization method is proposed for the solution of inverse scattering problems in the frequency domain, when the scattered field is governed by the Helmholtz equation. The time-harmonic inverse medium problem is formulated as a PDE-constrained optimization problem and solved by an inexact truncated Newton-type iteration. Instead of a grid-based discrete representation, the unknown wave speed is projected to a particular finite-dimensional basis of eigenfunctions, which is iteratively adapted during the optimization. Truncating the adaptive eigenspace (AE) basis at a (small and slowly increasing) finite number of eigenfunctions effectively introduces regularization into the inversion and thus avoids the need for standard Tikhonov-type regularization. Both analytical and numerical evidence underpins the accuracy of the AE representation. Numerical experiments demonstrate the efficiency and robustness to missing or noisy data of the resulting adaptive eigenspace inversion method.

Sound Frequency Representation in the Auditory Cortex of the Common Marmoset Visualized Using Optical Intrinsic Signal Imaging

PubMed Central

Tani, Toshiki; Abe, Hiroshi; Hayami, Taku; Banno, Taku; Kitamura, Naohito; Mashiko, Hiromi

2018-01-01

Abstract Natural sound is composed of various frequencies. Although the core region of the primate auditory cortex has functionally defined sound frequency preference maps, how the map is organized in the auditory areas of the belt and parabelt regions is not well known. In this study, we investigated the functional organizations of the core, belt, and parabelt regions encompassed by the lateral sulcus and the superior temporal sulcus in the common marmoset (Callithrix jacchus). Using optical intrinsic signal imaging, we obtained evoked responses to band-pass noise stimuli in a range of sound frequencies (0.5–16 kHz) in anesthetized adult animals and visualized the preferred sound frequency map on the cortical surface. We characterized the functionally defined organization using histologically defined brain areas in the same animals. We found tonotopic representation of a set of sound frequencies (low to high) within the primary (A1), rostral (R), and rostrotemporal (RT) areas of the core region. In the belt region, the tonotopic representation existed only in the mediolateral (ML) area. This representation was symmetric with that found in A1 along the border between areas A1 and ML. The functional structure was not very clear in the anterolateral (AL) area. Low frequencies were mainly preferred in the rostrotemplatal (RTL) area, while high frequencies were preferred in the caudolateral (CL) area. There was a portion of the parabelt region that strongly responded to higher sound frequencies (>5.8 kHz) along the border between the rostral parabelt (RPB) and caudal parabelt (CPB) regions. PMID:29736410

Digital signal processing of the phonocardiogram: review of the most recent advancements.

PubMed

Durand, L G; Pibarot, P

1995-01-01

The objective of the present paper is to provide a detailed review of the most recent developments in instrumentation and signal processing of digital phonocardiography and heart auscultation. After a short introduction, the paper presents a brief history of heart auscultation and phonocardiography, which is followed by a summary of the basic theories and controversies regarding the genesis of the heart sounds. The application of spectral analysis and the potential of new time-frequency representations and cardiac acoustic mapping to resolve the controversies and better understand the genesis and transmission of heart sounds and murmurs within the heart-thorax acoustic system are reviewed. The most recent developments in the application of linear predictive coding, spectral analysis, time-frequency representation techniques, and pattern recognition for the detection and follow-up of native and prosthetic valve degeneration and dysfunction are also presented in detail. New areas of research and clinical applications and areas of potential future developments are then highlighted. The final section is a discussion about a multidegree of freedom theory on the origin of the heart sounds and murmurs, which is completed by the authors' conclusion.

Knowledge inhibition and N400: a study with words that look like common words.

PubMed

Debruille, J B

1998-04-01

In addition to their own representations, low frequency words, such as BRIBE, can covertly activate the representations of higher frequency words they look like (e.g., BRIDE). Hence, look-alike words can activate knowledge that is incompatible with the knowledge corresponding to accurate representations. Comparatively, eccentric words, that is, low frequency words that do not look as much like higher frequency words, are less likely to activate incompatible knowledge. This study focuses on the hypothesis that the N400 component of the event-related potential reflects the inhibition of incompatible knowledge. This hypothesis predicts that look-alike words elicit N400s of greater amplitudes than eccentric words in conditions where incompatible knowledge is inhibited. Results from a single item lexical decision experiment are reported which support the inhibition hypothesis. Copyright 1998 Academic Press.

Aerodynamic Indicial Functions and Their Use in Aeroelastic Formulation of Lifting Surfaces

NASA Technical Reports Server (NTRS)

Marzocca, Piergiovanni; Librescu, Liviu; Silva, Walter A.

2000-01-01

An investigation related to the use of linear indicial functions in the time and frequency domains, enabling one to derive the proper aerodynamic loads as to study the subcritical response and flutter of swept lifting surfaces, respectively, of the open/closed loop aeroelastic system is presented. The expressions of the lift and aerodynamic moment in the frequency domain are given in terms of the Theodorsen's function, while, in the time domain, these are obtained directly with the help of the Wagner's function. Closed form solutions of aerodynamic derivatives are obtained, graphical representations are supplied and conclusions and prospects for further developments are outlined.

Signal existence verification (SEV) for GPS low received power signal detection using the time-frequency approach.

PubMed

Jan, Shau-Shiun; Sun, Chih-Cheng

2010-01-01

The detection of low received power of global positioning system (GPS) signals in the signal acquisition process is an important issue for GPS applications. Improving the miss-detection problem of low received power signal is crucial, especially for urban or indoor environments. This paper proposes a signal existence verification (SEV) process to detect and subsequently verify low received power GPS signals. The SEV process is based on the time-frequency representation of GPS signal, and it can capture the characteristic of GPS signal in the time-frequency plane to enhance the GPS signal acquisition performance. Several simulations and experiments are conducted to show the effectiveness of the proposed method for low received power signal detection. The contribution of this work is that the SEV process is an additional scheme to assist the GPS signal acquisition process in low received power signal detection, without changing the original signal acquisition or tracking algorithms.

The Frequency and Type of Graphical Representations in Science Trade Books for Children

ERIC Educational Resources Information Center

Coleman, Julianne M.; Dantzler, John A.

2016-01-01

This study sought to examine the frequency and type of graphical representations in science trade books for children from 1972 to 2007. Specifically questions addressed differences in graphical forms in science discipline and for intended audience age for books. The results revealed that there is an increase in the presence and variation of…

Radar modulation classification using time-frequency representation and nonlinear regression

NASA Astrophysics Data System (ADS)

De Luigi, Christophe; Arques, Pierre-Yves; Lopez, Jean-Marc; Moreau, Eric

1999-09-01

In naval electronic environment, pulses emitted by radars are collected by ESM receivers. For most of them the intrapulse signal is modulated by a particular law. To help the classical identification process, a classification and estimation of this modulation law is applied on the intrapulse signal measurements. To estimate with a good accuracy the time-varying frequency of a signal corrupted by an additive noise, one method has been chosen. This method consists on the Wigner distribution calculation, the instantaneous frequency is then estimated by the peak location of the distribution. Bias and variance of the estimator are performed by computed simulations. In a estimated sequence of frequencies, we assume the presence of false and good estimated ones, the hypothesis of Gaussian distribution is made on the errors. A robust non linear regression method, based on the Levenberg-Marquardt algorithm, is thus applied on these estimated frequencies using a Maximum Likelihood Estimator. The performances of the method are tested by using varied modulation laws and different signal to noise ratios.

ISAC: A tool for aeroservoelastic modeling and analysis

NASA Technical Reports Server (NTRS)

Adams, William M., Jr.; Hoadley, Sherwood Tiffany

1993-01-01

The capabilities of the Interaction of Structures, Aerodynamics, and Controls (ISAC) system of program modules is discussed. The major modeling, analysis, and data management components of ISAC are identified. Equations of motion are displayed for a Laplace-domain representation of the unsteady aerodynamic forces. Options for approximating a frequency-domain representation of unsteady aerodynamic forces with rational functions of the Laplace variable are shown. Linear time invariant state-space equations of motion that result are discussed. Model generation and analyses of stability and dynamic response characteristics are shown for an aeroelastic vehicle which illustrates some of the capabilities of ISAC as a modeling and analysis tool for aeroelastic applications.

Spectral estimation—What is new? What is next?

NASA Astrophysics Data System (ADS)

Tary, Jean Baptiste; Herrera, Roberto Henry; Han, Jiajun; van der Baan, Mirko

2014-12-01

Spectral estimation, and corresponding time-frequency representation for nonstationary signals, is a cornerstone in geophysical signal processing and interpretation. The last 10-15 years have seen the development of many new high-resolution decompositions that are often fundamentally different from Fourier and wavelet transforms. These conventional techniques, like the short-time Fourier transform and the continuous wavelet transform, show some limitations in terms of resolution (localization) due to the trade-off between time and frequency localizations and smearing due to the finite size of the time series of their template. Well-known techniques, like autoregressive methods and basis pursuit, and recently developed techniques, such as empirical mode decomposition and the synchrosqueezing transform, can achieve higher time-frequency localization due to reduced spectral smearing and leakage. We first review the theory of various established and novel techniques, pointing out their assumptions, adaptability, and expected time-frequency localization. We illustrate their performances on a provided collection of benchmark signals, including a laughing voice, a volcano tremor, a microseismic event, and a global earthquake, with the intention to provide a fair comparison of the pros and cons of each method. Finally, their outcomes are discussed and possible avenues for improvements are proposed.

Signal analysis of the female singing voice: Features for perceptual singer identity

NASA Astrophysics Data System (ADS)

Mellody, Maureen

2001-07-01

Individual singing voices tend to be easy for a listener to identify, particularly when compared to the difficulty of identifying the performer of any other musical instrument. What cues does a listener use to identify a particular singing voice? This work seeks to identify a set of features with which one can synthesize notes with the vocal quality of a particular singer. Such analysis and synthesis influences computer music (in the creation of synthetic sounds with different timbre), vocal pedagogy (as a training tool to help singers understand properties of their own voice as well as different professional-quality voices), and vocal health (to identify improper behavior in vocal production). The problem of singer identification is approached in three phases: signal analysis, the development of low- order representations, and perceptual evaluation. To perform the signal analysis, a high-resolution time- frequency distribution is applied to vowel tokens from sopranos and mezzo-sopranos. From these results, low- order representations are created for each singer's notes, which are used to synthesize sounds with the timbral quality of that singer. Finally, these synthesized sounds, along with original recordings, are evaluated by trained listeners in a variety of perceptual experiments to determine the extent to which the vocal quality of the desired singer is captured. Results from the signal analysis show that amplitude and frequency estimates extracted from the time-frequency signal analysis can be used to re-create each signal with little degradation in quality and no loss of perceptual identity. Low-order representations derived from the signal analysis are used in clustering and classification, which successfully clusters signals with corresponding singer identity. Finally, perceptual results indicate that trained listeners are, surprisingly, only modestly successful at correctly identifying the singer of a recording, and find the task to be particularly difficult for certain voices and extremely easy for others. Listeners also indicate that the majority of sounds synthesized with the low-order representations sufficiently capture the desired vocal timbre. Again, the task is easy for certain voices and much more difficult when evaluating other singers, consistent with the results from the original recordings.

Time and Frequency-Domain Cross-Verification of SLS 6DOF Trajectory Simulations

NASA Technical Reports Server (NTRS)

Johnson, Matthew; McCullough, John

2017-01-01

The Space Launch System (SLS) Guidance, Navigation, and Control (GNC) team and its partners have developed several time- and frequency-based simulations for development and analysis of the proposed SLS launch vehicle. The simulations differ in fidelity and some have unique functionality that allows them to perform specific analyses. Some examples of the purposes of the various models are: trajectory simulation, multi-body separation, Monte Carlo, hardware in the loop, loads, and frequency domain stability analyses. While no two simulations are identical, many of the models are essentially six degree-of-freedom (6DOF) representations of the SLS plant dynamics, hardware implementation, and flight software. Thus at a high level all of those models should be in agreement. Comparison of outputs from several SLS trajectory and stability analysis tools are ongoing as part of the program's current verification effort. The purpose of these comparisons is to highlight modeling and analysis differences, verify simulation data sources, identify inconsistencies and minor errors, and ultimately to verify output data as being a good representation of the vehicle and subsystem dynamics. This paper will show selected verification work in both the time and frequency domain from the current design analysis cycle of the SLS for several of the design and analysis simulations. In the time domain, the tools that will be compared are MAVERIC, CLVTOPS, SAVANT, STARS, ARTEMIS, and POST 2. For the frequency domain analysis, the tools to be compared are FRACTAL, SAVANT, and STARS. The paper will include discussion of these tools including their capabilities, configurations, and the uses to which they are put in the SLS program. Determination of the criteria by which the simulations are compared (matching criteria) requires thoughtful consideration, and there are several pitfalls that may occur that can severely punish a simulation if not considered carefully. The paper will discuss these considerations and will present a framework for responding to these issues when they arise. For example, small event timing differences can lead to large differences in mass properties if the criteria are to measure those properties at the same time, or large differences in altitude if the criteria are to measure those properties when the simulation experiences a staging event. Similarly, a tiny difference in phase can lead to large gain margin differences for frequency-domain comparisons of gain margins.

Tensorial dynamic time warping with articulation index representation for efficient audio-template learning.

PubMed

Le, Long N; Jones, Douglas L

2018-03-01

Audio classification techniques often depend on the availability of a large labeled training dataset for successful performance. However, in many application domains of audio classification (e.g., wildlife monitoring), obtaining labeled data is still a costly and laborious process. Motivated by this observation, a technique is proposed to efficiently learn a clean template from a few labeled, but likely corrupted (by noise and interferences), data samples. This learning can be done efficiently via tensorial dynamic time warping on the articulation index-based time-frequency representations of audio data. The learned template can then be used in audio classification following the standard template-based approach. Experimental results show that the proposed approach outperforms both (1) the recurrent neural network approach and (2) the state-of-the-art in the template-based approach on a wildlife detection application with few training samples.

High-resolution Temporal Representations of Alcohol and Tobacco Behaviors from Social Media Data.

PubMed

Huang, Tom; Elghafari, Anas; Relia, Kunal; Chunara, Rumi

2017-11-01

Understanding tobacco- and alcohol-related behavioral patterns is critical for uncovering risk factors and potentially designing targeted social computing intervention systems. Given that we make choices multiple times per day, hourly and daily patterns are critical for better understanding behaviors. Here, we combine natural language processing, machine learning and time series analyses to assess Twitter activity specifically related to alcohol and tobacco consumption and their sub-daily, daily and weekly cycles. Twitter self-reports of alcohol and tobacco use are compared to other data streams available at similar temporal resolution. We assess if discussion of drinking by inferred underage versus legal age people or discussion of use of different types of tobacco products can be differentiated using these temporal patterns. We find that time and frequency domain representations of behaviors on social media can provide meaningful and unique insights, and we discuss the types of behaviors for which the approach may be most useful.

Adapted wavelet transform improves time-frequency representations: a study of auditory elicited P300-like event-related potentials in rats.

PubMed

Richard, Nelly; Laursen, Bettina; Grupe, Morten; Drewes, Asbjørn M; Graversen, Carina; Sørensen, Helge B D; Bastlund, Jesper F

2017-04-01

Active auditory oddball paradigms are simple tone discrimination tasks used to study the P300 deflection of event-related potentials (ERPs). These ERPs may be quantified by time-frequency analysis. As auditory stimuli cause early high frequency and late low frequency ERP oscillations, the continuous wavelet transform (CWT) is often chosen for decomposition due to its multi-resolution properties. However, as the conventional CWT traditionally applies only one mother wavelet to represent the entire spectrum, the time-frequency resolution is not optimal across all scales. To account for this, we developed and validated a novel method specifically refined to analyse P300-like ERPs in rats. An adapted CWT (aCWT) was implemented to preserve high time-frequency resolution across all scales by commissioning of multiple wavelets operating at different scales. First, decomposition of simulated ERPs was illustrated using the classical CWT and the aCWT. Next, the two methods were applied to EEG recordings obtained from prefrontal cortex in rats performing a two-tone auditory discrimination task. While only early ERP frequency changes between responses to target and non-target tones were detected by the CWT, both early and late changes were successfully described with strong accuracy by the aCWT in rat ERPs. Increased frontal gamma power and phase synchrony was observed particularly within theta and gamma frequency bands during deviant tones. The study suggests superior performance of the aCWT over the CWT in terms of detailed quantification of time-frequency properties of ERPs. Our methodological investigation indicates that accurate and complete assessment of time-frequency components of short-time neural signals is feasible with the novel analysis approach which may be advantageous for characterisation of several types of evoked potentials in particularly rodents.

Time-frequency analysis of phonocardiogram signals using wavelet transform: a comparative study.

PubMed

Ergen, Burhan; Tatar, Yetkin; Gulcur, Halil Ozcan

2012-01-01

Analysis of phonocardiogram (PCG) signals provides a non-invasive means to determine the abnormalities caused by cardiovascular system pathology. In general, time-frequency representation (TFR) methods are used to study the PCG signal because it is one of the non-stationary bio-signals. The continuous wavelet transform (CWT) is especially suitable for the analysis of non-stationary signals and to obtain the TFR, due to its high resolution, both in time and in frequency and has recently become a favourite tool. It decomposes a signal in terms of elementary contributions called wavelets, which are shifted and dilated copies of a fixed mother wavelet function, and yields a joint TFR. Although the basic characteristics of the wavelets are similar, each type of the wavelets produces a different TFR. In this study, eight real types of the most known wavelets are examined on typical PCG signals indicating heart abnormalities in order to determine the best wavelet to obtain a reliable TFR. For this purpose, the wavelet energy and frequency spectrum estimations based on the CWT and the spectra of the chosen wavelets were compared with the energy distribution and the autoregressive frequency spectra in order to determine the most suitable wavelet. The results show that Morlet wavelet is the most reliable wavelet for the time-frequency analysis of PCG signals.

Neural representation of the self-heard biosonar click in bottlenose dolphins (Tursiops truncatus).

PubMed

Finneran, James J; Mulsow, Jason; Houser, Dorian S; Schlundt, Carolyn E

2017-05-01

The neural representation of the dolphin broadband biosonar click was investigated by measuring auditory brainstem responses (ABRs) to "self-heard" clicks masked with noise bursts having various high-pass cutoff frequencies. Narrowband ABRs were obtained by sequentially subtracting responses obtained with noise having lower high-pass cutoff frequencies from those obtained with noise having higher cutoff frequencies. For comparison to the biosonar data, ABRs were also measured in a passive listening experiment, where external clicks and masking noise were presented to the dolphins and narrowband ABRs were again derived using the subtractive high-pass noise technique. The results showed little change in the peak latencies of the ABR to the self-heard click from 28 to 113 kHz; i.e., the high-frequency neural responses to the self-heard click were delayed relative to those of an external, spectrally "pink" click. The neural representation of the self-heard click is thus highly synchronous across the echolocation frequencies and does not strongly resemble that of a frequency modulated downsweep (i.e., decreasing-frequency chirp). Longer ABR latencies at higher frequencies are hypothesized to arise from spectral differences between self-heard clicks and external clicks, forward masking from previously emitted biosonar clicks, or neural inhibition accompanying the emission of clicks.

Neural representation of the self-heard biosonar click in bottlenose dolphins (Tursiops truncatus)

PubMed Central

Finneran, James J.; Mulsow, Jason; Houser, Dorian S.; Schlundt, Carolyn E.

2017-01-01

The neural representation of the dolphin broadband biosonar click was investigated by measuring auditory brainstem responses (ABRs) to “self-heard” clicks masked with noise bursts having various high-pass cutoff frequencies. Narrowband ABRs were obtained by sequentially subtracting responses obtained with noise having lower high-pass cutoff frequencies from those obtained with noise having higher cutoff frequencies. For comparison to the biosonar data, ABRs were also measured in a passive listening experiment, where external clicks and masking noise were presented to the dolphins and narrowband ABRs were again derived using the subtractive high-pass noise technique. The results showed little change in the peak latencies of the ABR to the self-heard click from 28 to 113 kHz; i.e., the high-frequency neural responses to the self-heard click were delayed relative to those of an external, spectrally “pink” click. The neural representation of the self-heard click is thus highly synchronous across the echolocation frequencies and does not strongly resemble that of a frequency modulated downsweep (i.e., decreasing-frequency chirp). Longer ABR latencies at higher frequencies are hypothesized to arise from spectral differences between self-heard clicks and external clicks, forward masking from previously emitted biosonar clicks, or neural inhibition accompanying the emission of clicks. PMID:28599518

Crack Detection with Lamb Wave Wavenumber Analysis

NASA Technical Reports Server (NTRS)

Tian, Zhenhua; Leckey, Cara; Rogge, Matt; Yu, Lingyu

2013-01-01

In this work, we present our study of Lamb wave crack detection using wavenumber analysis. The aim is to demonstrate the application of wavenumber analysis to 3D Lamb wave data to enable damage detection. The 3D wavefields (including vx, vy and vz components) in time-space domain contain a wealth of information regarding the propagating waves in a damaged plate. For crack detection, three wavenumber analysis techniques are used: (i) two dimensional Fourier transform (2D-FT) which can transform the time-space wavefield into frequency-wavenumber representation while losing the spatial information; (ii) short space 2D-FT which can obtain the frequency-wavenumber spectra at various spatial locations, resulting in a space-frequency-wavenumber representation; (iii) local wavenumber analysis which can provide the distribution of the effective wavenumbers at different locations. All of these concepts are demonstrated through a numerical simulation example of an aluminum plate with a crack. The 3D elastodynamic finite integration technique (EFIT) was used to obtain the 3D wavefields, of which the vz (out-of-plane) wave component is compared with the experimental measurement obtained from a scanning laser Doppler vibrometer (SLDV) for verification purposes. The experimental and simulated results are found to be in close agreement. The application of wavenumber analysis on 3D EFIT simulation data shows the effectiveness of the analysis for crack detection. Keywords: : Lamb wave, crack detection, wavenumber analysis, EFIT modeling

On the maximum-entropy/autoregressive modeling of time series

NASA Technical Reports Server (NTRS)

Chao, B. F.

1984-01-01

The autoregressive (AR) model of a random process is interpreted in the light of the Prony's relation which relates a complex conjugate pair of poles of the AR process in the z-plane (or the z domain) on the one hand, to the complex frequency of one complex harmonic function in the time domain on the other. Thus the AR model of a time series is one that models the time series as a linear combination of complex harmonic functions, which include pure sinusoids and real exponentials as special cases. An AR model is completely determined by its z-domain pole configuration. The maximum-entropy/autogressive (ME/AR) spectrum, defined on the unit circle of the z-plane (or the frequency domain), is nothing but a convenient, but ambiguous visual representation. It is asserted that the position and shape of a spectral peak is determined by the corresponding complex frequency, and the height of the spectral peak contains little information about the complex amplitude of the complex harmonic functions.

Brain-computer interface using wavelet transformation and naïve bayes classifier.

PubMed

Bassani, Thiago; Nievola, Julio Cesar

2010-01-01

The main purpose of this work is to establish an exploratory approach using electroencephalographic (EEG) signal, analyzing the patterns in the time-frequency plane. This work also aims to optimize the EEG signal analysis through the improvement of classifiers and, eventually, of the BCI performance. In this paper a novel exploratory approach for data mining of EEG signal based on continuous wavelet transformation (CWT) and wavelet coherence (WC) statistical analysis is introduced and applied. The CWT allows the representation of time-frequency patterns of the signal's information content by WC qualiatative analysis. Results suggest that the proposed methodology is capable of identifying regions in time-frequency spectrum during the specified task of BCI. Furthermore, an example of a region is identified, and the patterns are classified using a Naïve Bayes Classifier (NBC). This innovative characteristic of the process justifies the feasibility of the proposed approach to other data mining applications. It can open new physiologic researches in this field and on non stationary time series analysis.

Application of 2D graphic representation of protein sequence based on Huffman tree method.

PubMed

Qi, Zhao-Hui; Feng, Jun; Qi, Xiao-Qin; Li, Ling

2012-05-01

Based on Huffman tree method, we propose a new 2D graphic representation of protein sequence. This representation can completely avoid loss of information in the transfer of data from a protein sequence to its graphic representation. The method consists of two parts. One is about the 0-1 codes of 20 amino acids by Huffman tree with amino acid frequency. The amino acid frequency is defined as the statistical number of an amino acid in the analyzed protein sequences. The other is about the 2D graphic representation of protein sequence based on the 0-1 codes. Then the applications of the method on ten ND5 genes and seven Escherichia coli strains are presented in detail. The results show that the proposed model may provide us with some new sights to understand the evolution patterns determined from protein sequences and complete genomes. Copyright © 2012 Elsevier Ltd. All rights reserved.

Nonnegative matrix factorization and sparse representation for the automated detection of periodic limb movements in sleep.

PubMed

Shokrollahi, Mehrnaz; Krishnan, Sridhar; Dopsa, Dustin D; Muir, Ryan T; Black, Sandra E; Swartz, Richard H; Murray, Brian J; Boulos, Mark I

2016-11-01

Stroke is a leading cause of death and disability in adults, and incurs a significant economic burden to society. Periodic limb movements (PLMs) in sleep are repetitive movements involving the great toe, ankle, and hip. Evolving evidence suggests that PLMs may be associated with high blood pressure and stroke, but this relationship remains underexplored. Several issues limit the study of PLMs including the need to manually score them, which is time-consuming and costly. For this reason, we developed a novel automated method for nocturnal PLM detection, which was shown to be correlated with (a) the manually scored PLM index on polysomnography, and (b) white matter hyperintensities on brain imaging, which have been demonstrated to be associated with PLMs. Our proposed algorithm consists of three main stages: (1) representing the signal in the time-frequency plane using time-frequency matrices (TFM), (2) applying K-nonnegative matrix factorization technique to decompose the TFM matrix into its significant components, and (3) applying kernel sparse representation for classification (KSRC) to the decomposed signal. Our approach was applied to a dataset that consisted of 65 subjects who underwent polysomnography. An overall classification of 97 % was achieved for discrimination of the aforementioned signals, demonstrating the potential of the presented method.

Time-frequency peak filtering for random noise attenuation of magnetic resonance sounding signal

NASA Astrophysics Data System (ADS)

Lin, Tingting; Zhang, Yang; Yi, Xiaofeng; Fan, Tiehu; Wan, Ling

2018-05-01

When measuring in a geomagnetic field, the method of magnetic resonance sounding (MRS) is often limited because of the notably low signal-to-noise ratio (SNR). Most current studies focus on discarding spiky noise and power-line harmonic noise cancellation. However, the effects of random noise should not be underestimated. The common method for random noise attenuation is stacking, but collecting multiple recordings merely to suppress random noise is time-consuming. Moreover, stacking is insufficient to suppress high-level random noise. Here, we propose the use of time-frequency peak filtering for random noise attenuation, which is performed after the traditional de-spiking and power-line harmonic removal method. By encoding the noisy signal with frequency modulation and estimating the instantaneous frequency using the peak of the time-frequency representation of the encoded signal, the desired MRS signal can be acquired from only one stack. The performance of the proposed method is tested on synthetic envelope signals and field data from different surveys. Good estimations of the signal parameters are obtained at different SNRs. Moreover, an attempt to use the proposed method to handle a single recording provides better results compared to 16 stacks. Our results suggest that the number of stacks can be appropriately reduced to shorten the measurement time and improve the measurement efficiency.

Heart energy signature spectrogram for cardiovascular diagnosis

PubMed Central

Kudriavtsev, Vladimir; Polyshchuk, Vladimir; Roy, Douglas L

2007-01-01

A new method and application is proposed to characterize intensity and pitch of human heart sounds and murmurs. Using recorded heart sounds from the library of one of the authors, a visual map of heart sound energy was established. Both normal and abnormal heart sound recordings were studied. Representation is based on Wigner-Ville joint time-frequency transformations. The proposed methodology separates acoustic contributions of cardiac events simultaneously in pitch, time and energy. The resolution accuracy is superior to any other existing spectrogram method. The characteristic energy signature of the innocent heart murmur in a child with the S3 sound is presented. It allows clear detection of S1, S2 and S3 sounds, S2 split, systolic murmur, and intensity of these components. The original signal, heart sound power change with time, time-averaged frequency, energy density spectra and instantaneous variations of power and frequency/pitch with time, are presented. These data allow full quantitative characterization of heart sounds and murmurs. High accuracy in both time and pitch resolution is demonstrated. Resulting visual images have self-referencing quality, whereby individual features and their changes become immediately obvious. PMID:17480232

Quantization of Motor Activity into Primitives and Time-Frequency Atoms Using Independent Component Analysis and Matching Pursuit Algorithms

DTIC Science & Technology

2001-10-25

form: (1) A is a scaling factor, t is time and r a coordinate vector describing the limb configuration. We...combination of limb state and EMG. In our early examination of EMG we detected underlying groups of muscles and phases of activity by inspection and...representations of EEG or other biological signals has been thoroughly explored. Such components might be used as a basis for neuroprosthetic control

Standardizing clinical trials workflow representation in UML for international site comparison.

PubMed

de Carvalho, Elias Cesar Araujo; Jayanti, Madhav Kishore; Batilana, Adelia Portero; Kozan, Andreia M O; Rodrigues, Maria J; Shah, Jatin; Loures, Marco R; Patil, Sunita; Payne, Philip; Pietrobon, Ricardo

2010-11-09

With the globalization of clinical trials, a growing emphasis has been placed on the standardization of the workflow in order to ensure the reproducibility and reliability of the overall trial. Despite the importance of workflow evaluation, to our knowledge no previous studies have attempted to adapt existing modeling languages to standardize the representation of clinical trials. Unified Modeling Language (UML) is a computational language that can be used to model operational workflow, and a UML profile can be developed to standardize UML models within a given domain. This paper's objective is to develop a UML profile to extend the UML Activity Diagram schema into the clinical trials domain, defining a standard representation for clinical trial workflow diagrams in UML. Two Brazilian clinical trial sites in rheumatology and oncology were examined to model their workflow and collect time-motion data. UML modeling was conducted in Eclipse, and a UML profile was developed to incorporate information used in discrete event simulation software. Ethnographic observation revealed bottlenecks in workflow: these included tasks requiring full commitment of CRCs, transferring notes from paper to computers, deviations from standard operating procedures, and conflicts between different IT systems. Time-motion analysis revealed that nurses' activities took up the most time in the workflow and contained a high frequency of shorter duration activities. Administrative assistants performed more activities near the beginning and end of the workflow. Overall, clinical trial tasks had a greater frequency than clinic routines or other general activities. This paper describes a method for modeling clinical trial workflow in UML and standardizing these workflow diagrams through a UML profile. In the increasingly global environment of clinical trials, the standardization of workflow modeling is a necessary precursor to conducting a comparative analysis of international clinical trials workflows.

Standardizing Clinical Trials Workflow Representation in UML for International Site Comparison

PubMed Central

de Carvalho, Elias Cesar Araujo; Jayanti, Madhav Kishore; Batilana, Adelia Portero; Kozan, Andreia M. O.; Rodrigues, Maria J.; Shah, Jatin; Loures, Marco R.; Patil, Sunita; Payne, Philip; Pietrobon, Ricardo

2010-01-01

Background With the globalization of clinical trials, a growing emphasis has been placed on the standardization of the workflow in order to ensure the reproducibility and reliability of the overall trial. Despite the importance of workflow evaluation, to our knowledge no previous studies have attempted to adapt existing modeling languages to standardize the representation of clinical trials. Unified Modeling Language (UML) is a computational language that can be used to model operational workflow, and a UML profile can be developed to standardize UML models within a given domain. This paper's objective is to develop a UML profile to extend the UML Activity Diagram schema into the clinical trials domain, defining a standard representation for clinical trial workflow diagrams in UML. Methods Two Brazilian clinical trial sites in rheumatology and oncology were examined to model their workflow and collect time-motion data. UML modeling was conducted in Eclipse, and a UML profile was developed to incorporate information used in discrete event simulation software. Results Ethnographic observation revealed bottlenecks in workflow: these included tasks requiring full commitment of CRCs, transferring notes from paper to computers, deviations from standard operating procedures, and conflicts between different IT systems. Time-motion analysis revealed that nurses' activities took up the most time in the workflow and contained a high frequency of shorter duration activities. Administrative assistants performed more activities near the beginning and end of the workflow. Overall, clinical trial tasks had a greater frequency than clinic routines or other general activities. Conclusions This paper describes a method for modeling clinical trial workflow in UML and standardizing these workflow diagrams through a UML profile. In the increasingly global environment of clinical trials, the standardization of workflow modeling is a necessary precursor to conducting a comparative analysis of international clinical trials workflows. PMID:21085484

Matching Pursuit with Asymmetric Functions for Signal Decomposition and Parameterization

PubMed Central

Spustek, Tomasz; Jedrzejczak, Wiesław Wiktor; Blinowska, Katarzyna Joanna

2015-01-01

The method of adaptive approximations by Matching Pursuit makes it possible to decompose signals into basic components (called atoms). The approach relies on fitting, in an iterative way, functions from a large predefined set (called dictionary) to an analyzed signal. Usually, symmetric functions coming from the Gabor family (sine modulated Gaussian) are used. However Gabor functions may not be optimal in describing waveforms present in physiological and medical signals. Many biomedical signals contain asymmetric components, usually with a steep rise and slower decay. For the decomposition of this kind of signal we introduce a dictionary of functions of various degrees of asymmetry – from symmetric Gabor atoms to highly asymmetric waveforms. The application of this enriched dictionary to Otoacoustic Emissions and Steady-State Visually Evoked Potentials demonstrated the advantages of the proposed method. The approach provides more sparse representation, allows for correct determination of the latencies of the components and removes the "energy leakage" effect generated by symmetric waveforms that do not sufficiently match the structures of the analyzed signal. Additionally, we introduced a time-frequency-amplitude distribution that is more adequate for representation of asymmetric atoms than the conventional time-frequency-energy distribution. PMID:26115480

Robust Real-Time Music Transcription with a Compositional Hierarchical Model.

PubMed

Pesek, Matevž; Leonardis, Aleš; Marolt, Matija

2017-01-01

The paper presents a new compositional hierarchical model for robust music transcription. Its main features are unsupervised learning of a hierarchical representation of input data, transparency, which enables insights into the learned representation, as well as robustness and speed which make it suitable for real-world and real-time use. The model consists of multiple layers, each composed of a number of parts. The hierarchical nature of the model corresponds well to hierarchical structures in music. The parts in lower layers correspond to low-level concepts (e.g. tone partials), while the parts in higher layers combine lower-level representations into more complex concepts (tones, chords). The layers are learned in an unsupervised manner from music signals. Parts in each layer are compositions of parts from previous layers based on statistical co-occurrences as the driving force of the learning process. In the paper, we present the model's structure and compare it to other hierarchical approaches in the field of music information retrieval. We evaluate the model's performance for the multiple fundamental frequency estimation. Finally, we elaborate on extensions of the model towards other music information retrieval tasks.

Frequency spirals.

PubMed

Ottino-Löffler, Bertrand; Strogatz, Steven H

2016-09-01

We study the dynamics of coupled phase oscillators on a two-dimensional Kuramoto lattice with periodic boundary conditions. For coupling strengths just below the transition to global phase-locking, we find localized spatiotemporal patterns that we call "frequency spirals." These patterns cannot be seen under time averaging; they become visible only when we examine the spatial variation of the oscillators' instantaneous frequencies, where they manifest themselves as two-armed rotating spirals. In the more familiar phase representation, they appear as wobbly periodic patterns surrounding a phase vortex. Unlike the stationary phase vortices seen in magnetic spin systems, or the rotating spiral waves seen in reaction-diffusion systems, frequency spirals librate: the phases of the oscillators surrounding the central vortex move forward and then backward, executing a periodic motion with zero winding number. We construct the simplest frequency spiral and characterize its properties using analytical and numerical methods. Simulations show that frequency spirals in large lattices behave much like this simple prototype.

Frequency-domain method for discrete frequency noise prediction of rotors in arbitrary steady motion

NASA Astrophysics Data System (ADS)

Gennaretti, M.; Testa, C.; Bernardini, G.

2012-12-01

A novel frequency-domain formulation for the prediction of the tonal noise emitted by rotors in arbitrary steady motion is presented. It is derived from Farassat's 'Formulation 1A', that is a time-domain boundary integral representation for the solution of the Ffowcs-Williams and Hawkings equation, and represents noise as harmonic response to body kinematics and aerodynamic loads via frequency-response-function matrices. The proposed frequency-domain solver is applicable to rotor configurations for which sound pressure levels of discrete tones are much higher than those of broadband noise. The numerical investigation concerns the analysis of noise produced by an advancing helicopter rotor in blade-vortex interaction conditions, as well as the examination of pressure disturbances radiated by the interaction of a marine propeller with a non-uniform inflow.

Unified Formulation of the Aeroelasticity of Swept Lifting Surfaces

NASA Technical Reports Server (NTRS)

Silva, Walter; Marzocca, Piergiovanni; Librescu, Liviu

2001-01-01

An unified approach for dealing with stability and aeroelastic response to time-dependent pressure pulses of swept wings in an incompressible flow is developed. To this end the indicial function concept in time and frequency domains, enabling one to derive the proper unsteady aerodynamic loads is used. Results regarding stability in the frequency and time domains, and subcritical aeroelastic response to arbitrary time-dependent external excitation obtained via the direct use of the unsteady aerodynamic derivatives for 3-D wings are supplied. Closed form expressions for unsteady aerodynamic derivatives using this unified approach have been derived and used to illustrate their application to flutter and aeroelastic response to blast and sonic-boom signatures. In this context, an original representation of the aeroelastic response in the phase space was presented and pertinent conclusions on the implications of some basic parameters have been outlined.

A clock steering method: using a third-order type 3 DPLL equivalent to a Kalman filter with a delay

NASA Astrophysics Data System (ADS)

Wu, Yiwei; Gong, Hang; Zhu, Xiangwei; Ou, Gang

2015-12-01

In this paper we propose a new clock steering method, which uses a third-order type 3 digital phase locked loop (DPLL) which is equivalent to a Kalman filter with a delay. A general overview of the theoretical framework is described in detail including the transfer functions, the structure and control values, the specifications, and the approach to choosing a parameter. Simulations show that the performance of the time and frequency steering errors and the frequency stability are quite desirable. Comparing with traditional clock steering methods, it is easier to work with just one parameter. The DPLL method satisfies the requirements of generating a local representation of universal time coordinated and the system time of a global navigation satellite system.

Analysis of spike-wave discharges in rats using discrete wavelet transform.

PubMed

Ubeyli, Elif Derya; Ilbay, Gül; Sahin, Deniz; Ateş, Nurbay

2009-03-01

A feature is a distinctive or characteristic measurement, transform, structural component extracted from a segment of a pattern. Features are used to represent patterns with the goal of minimizing the loss of important information. The discrete wavelet transform (DWT) as a feature extraction method was used in representing the spike-wave discharges (SWDs) records of Wistar Albino Glaxo/Rijswijk (WAG/Rij) rats. The SWD records of WAG/Rij rats were decomposed into time-frequency representations using the DWT and the statistical features were calculated to depict their distribution. The obtained wavelet coefficients were used to identify characteristics of the signal that were not apparent from the original time domain signal. The present study demonstrates that the wavelet coefficients are useful in determining the dynamics in the time-frequency domain of SWD records.

Spectral analysis of temporal non-stationary rainfall-runoff processes

NASA Astrophysics Data System (ADS)

Chang, Ching-Min; Yeh, Hund-Der

2018-04-01

This study treats the catchment as a block box system with considering the rainfall input and runoff output being a stochastic process. The temporal rainfall-runoff relationship at the catchment scale is described by a convolution integral on a continuous time scale. Using the Fourier-Stieltjes representation approach, a frequency domain solution to the convolution integral is developed to the spectral analysis of runoff processes generated by temporal non-stationary rainfall events. It is shown that the characteristic time scale of rainfall process increases the runoff discharge variability, while the catchment mean travel time constant plays the role in reducing the variability of runoff discharge. Similar to the behavior of groundwater aquifers, catchments act as a low-pass filter in the frequency domain for the rainfall input signal.

Are Chinese Correlative Conjunctions Psychologically Real? An Investigation of the Combination Frequency Effect.

PubMed

Kong, Lingyue; Zhang, John X; Zhang, Yongwei

2016-08-01

The present study used an online grammaticality judgment task to examine whether Chinese discontinuous correlative conjunctions are psychologically real in mental lexicon. High- and low-frequency discontinuous correlative conjunctions were compared with random combinations differing in combination frequencies but matched for constituent word frequency. Forty graduate students participated in the study. Results showed that responses were faster and more accurate for high-frequency correlative conjunctions than low-frequency ones, but the effects were absent for random combinations. The results indicate that Chinese discontinuous correlative conjunctions have psychological reality in mental lexicon in addition to the representation of their constituent words, and that grammatical functions of correlative conjunctions may be a critical factor for the formation of such holistic representations. © The Author(s) 2016.

Towards automated human gait disease classification using phase space representation of intrinsic mode functions

NASA Astrophysics Data System (ADS)

Pratiher, Sawon; Patra, Sayantani; Pratiher, Souvik

2017-06-01

A novel analytical methodology for segregating healthy and neurological disorders from gait patterns is proposed by employing a set of oscillating components called intrinsic mode functions (IMF's). These IMF's are generated by the Empirical Mode Decomposition of the gait time series and the Hilbert transformed analytic signal representation forms the complex plane trace of the elliptical shaped analytic IMFs. The area measure and the relative change in the centroid position of the polygon formed by the Convex Hull of these analytic IMF's are taken as the discriminative features. Classification accuracy of 79.31% with Ensemble learning based Adaboost classifier validates the adequacy of the proposed methodology for a computer aided diagnostic (CAD) system for gait pattern identification. Also, the efficacy of several potential biomarkers like Bandwidth of Amplitude Modulation and Frequency Modulation IMF's and it's Mean Frequency from the Fourier-Bessel expansion from each of these analytic IMF's has been discussed for its potency in diagnosis of gait pattern identification and classification.

Spectrum response estimation for deep-water floating platforms via retardation function representation

NASA Astrophysics Data System (ADS)

Liu, Fushun; Liu, Chengcheng; Chen, Jiefeng; Wang, Bin

2017-08-01

The key concept of spectrum response estimation with commercial software, such as the SESAM software tool, typically includes two main steps: finding a suitable loading spectrum and computing the response amplitude operators (RAOs) subjected to a frequency-specified wave component. In this paper, we propose a nontraditional spectrum response estimation method that uses a numerical representation of the retardation functions. Based on estimated added mass and damping matrices of the structure, we decompose and replace the convolution terms with a series of poles and corresponding residues in the Laplace domain. Then, we estimate the power density corresponding to each frequency component using the improved periodogram method. The advantage of this approach is that the frequency-dependent motion equations in the time domain can be transformed into the Laplace domain without requiring Laplace-domain expressions for the added mass and damping. To validate the proposed method, we use a numerical semi-submerged pontoon from the SESAM. The numerical results show that the responses of the proposed method match well with those obtained from the traditional method. Furthermore, the estimated spectrum also matches well, which indicates its potential application to deep-water floating structures.

An Application of Reassigned Time-Frequency Representations for Seismic Noise/Signal Decomposition

NASA Astrophysics Data System (ADS)

Mousavi, S. M.; Langston, C. A.

2016-12-01

Seismic data recorded by surface arrays are often strongly contaminated by unwanted noise. This background noise makes the detection of small magnitude events difficult. An automatic method for seismic noise/signal decomposition is presented based upon an enhanced time-frequency representation. Synchrosqueezing is a time-frequency reassignment method aimed at sharpening a time-frequency picture. Noise can be distinguished from the signal and suppressed more easily in this reassigned domain. The threshold level is estimated using a general cross validation approach that does not rely on any prior knowledge about the noise level. Efficiency of thresholding has been improved by adding a pre-processing step based on higher order statistics and a post-processing step based on adaptive hard-thresholding. In doing so, both accuracy and speed of the denoising have been improved compared to our previous algorithms (Mousavi and Langston, 2016a, 2016b; Mousavi et al., 2016). The proposed algorithm can either kill the noise (either white or colored) and keep the signal or kill the signal and keep the noise. Hence, It can be used in either normal denoising applications or in ambient noise studies. Application of the proposed method on synthetic and real seismic data shows the effectiveness of the method for denoising/designaling of local microseismic, and ocean bottom seismic data. References: Mousavi, S.M., C. A. Langston., and S. P. Horton (2016), Automatic Microseismic Denoising and Onset Detection Using the Synchrosqueezed-Continuous Wavelet Transform. Geophysics. 81, V341-V355, doi: 10.1190/GEO2015-0598.1. Mousavi, S.M., and C. A. Langston (2016a), Hybrid Seismic Denoising Using Higher-Order Statistics and Improved Wavelet Block Thresholding. Bull. Seismol. Soc. Am., 106, doi: 10.1785/0120150345. Mousavi, S.M., and C.A. Langston (2016b), Adaptive noise estimation and suppression for improving microseismic event detection, Journal of Applied Geophysics., doi: http://dx.doi.org/10.1016/j.jappgeo.2016.06.008.

Phase-amplitude coupling supports phase coding in human ECoG

PubMed Central

Watrous, Andrew J; Deuker, Lorena; Fell, Juergen; Axmacher, Nikolai

2015-01-01

Prior studies have shown that high-frequency activity (HFA) is modulated by the phase of low-frequency activity. This phenomenon of phase-amplitude coupling (PAC) is often interpreted as reflecting phase coding of neural representations, although evidence for this link is still lacking in humans. Here, we show that PAC indeed supports phase-dependent stimulus representations for categories. Six patients with medication-resistant epilepsy viewed images of faces, tools, houses, and scenes during simultaneous acquisition of intracranial recordings. Analyzing 167 electrodes, we observed PAC at 43% of electrodes. Further inspection of PAC revealed that category specific HFA modulations occurred at different phases and frequencies of the underlying low-frequency rhythm, permitting decoding of categorical information using the phase at which HFA events occurred. These results provide evidence for categorical phase-coded neural representations and are the first to show that PAC coincides with phase-dependent coding in the human brain. DOI: http://dx.doi.org/10.7554/eLife.07886.001 PMID:26308582

A look at motion in the frequency domain

NASA Technical Reports Server (NTRS)

Watson, A. B.; Ahumada, A. J., Jr.

1983-01-01

A moving image can be specified by a contrast distribution, c(x,y,t), over the dimensions of space x,y, and time t. Alternatively, it can be specified by the distribution C(u,v,w) over spatial frequency u,v and temporal frequency w. The frequency representation of a moving image is shown to have a characteristic form. This permits two useful observations. The first is that the apparent smoothness of time-sampled moving images (apparent motion) can be explained by the filtering action of the human visual system. This leads to the following formula for the required update rate for time-sampled displays. W(c)=W(l)+ru(l) where w(c) is the required update rate in Hz, W(l) is the limit of human temporal resolution in Hz, r is the velocity of the moving image in degrees/sec, and u(l) is the limit of human spatial resolution in cycles/deg. The second observation is that it is possible to construct a linear sensor that responds to images moving in a particular direction. The sensor is derived and its properties are discussed.

The N/Rev phenomenon in simulating a blade-element rotor system

NASA Technical Reports Server (NTRS)

Mcfarland, R. E.

1983-01-01

When a simulation model produces frequencies that are beyond the bandwidth of a discrete implementation, anomalous frequencies appear within the bandwidth. Such is the case with blade element models of rotor systems, which are used in the real time, man in the loop simulation environment. Steady state, high frequency harmonics generated by these models, whether aliased or not, obscure piloted helicopter simulation responses. Since these harmonics are attenuated in actual rotorcraft (e.g., because of structural damping), a faithful environment representation for handling qualities purposes may be created from the original model by using certain filtering techniques, as outlined here. These include harmonic consideration, conventional filtering, and decontamination. The process of decontamination is of special interest because frequencies of importance to simulation operation are not attenuated, whereas superimposed aliased harmonics are.

Yield Scaling of Frequency Domain Moment Tensors from Contained Chemical Explosions Detonated in Granite

NASA Astrophysics Data System (ADS)

MacPhail, M. D.; Stump, B. W.; Zhou, R.

2017-12-01

The Source Phenomenology Experiment (SPE - Arizona) was a series of nine, contained and partially contained chemical explosions within the porphyry granite at the Morenci Copper mine in Arizona. Its purpose was to detonate, record and analyze seismic waveforms from these single-fired explosions. Ground motion data from the SPE is analyzed in this study to assess the uniqueness of the time domain moment tensor source representation and its ability to quantify containment and yield scaling. Green's functions were computed for each of the explosions based on a 1D velocity model developed for the SPE. The Green's functions for the sixteen, near-source stations focused on observations from 37 to 680 m. This study analyzes the three deepest, fully contained explosions with a depth of burial of 30 m and yields of 0.77e-3, 3.08e-3 and 6.17e-3 kt. Inversions are conducted within the frequency domain and moment tensors are decomposed into deviatoric and isotropic components to evaluate the effects of containment and yield on the resulting source representation. Isotropic moments are compared to those for other contained explosions as reported by Denny and Johnson, 1991, and are in good agreement with their scaling results. The explosions in this study have isotropic moments of 1.2e12, 3.1e12 and 6.1e13 n*m. Isotropic and Mzz moment tensor spectra are compared to Mueller-Murphy, Denny-Johnson and revised Heard-Ackerman (HA) models and suggest that the larger explosions fit the HA model better. Secondary source effects resulting from free surface interactions including the effects of spallation contribute to the resulting moment tensors which include a CLVD component. Hudson diagrams, using frequency domain moment tensor data, are computed as a tool to assess how these containment scenarios affect the source representation. Our analysis suggests that, within our band of interest (2-20 Hz), as the frequency increases, the source representation becomes more explosion like, peaking at around 20 Hz. These results guide additional analysis of the observational data and the practical resolution of physical phenomenology accompanying underground explosions.

ISAC - A tool for aeroservoelastic modeling and analysis. [Interaction of Structures, Aerodynamics, and Control

NASA Technical Reports Server (NTRS)

Adams, William M., Jr.; Hoadley, Sherwood T.

1993-01-01

This paper discusses the capabilities of the Interaction of Structures, Aerodynamics, and Controls (ISAC) system of program modules. The major modeling, analysis, and data management components of ISAC are identified. Equations of motion are displayed for a Laplace-domain representation of the unsteady aerodynamic forces. Options for approximating a frequency-domain representation of unsteady aerodynamic forces with rational functions of the Laplace variable are shown. Linear time invariant state-space equations of motion that result are discussed. Model generation and analyses of stability and dynamic response characteristics are shown for an aeroelastic vehicle which illustrate some of the capabilities of ISAC as a modeling and analysis tool for aeroelastic applications.

Communication theory of quantum systems. Ph.D. Thesis, 1970

NASA Technical Reports Server (NTRS)

Yuen, H. P. H.

1971-01-01

Communication theory problems incorporating quantum effects for optical-frequency applications are discussed. Under suitable conditions, a unique quantum channel model corresponding to a given classical space-time varying linear random channel is established. A procedure is described by which a proper density-operator representation applicable to any receiver configuration can be constructed directly from the channel output field. Some examples illustrating the application of our methods to the development of optical quantum channel representations are given. Optimizations of communication system performance under different criteria are considered. In particular, certain necessary and sufficient conditions on the optimal detector in M-ary quantum signal detection are derived. Some examples are presented. Parameter estimation and channel capacity are discussed briefly.

Biologically Inspired Model for Inference of 3D Shape from Texture

PubMed Central

Gomez, Olman; Neumann, Heiko

2016-01-01

A biologically inspired model architecture for inferring 3D shape from texture is proposed. The model is hierarchically organized into modules roughly corresponding to visual cortical areas in the ventral stream. Initial orientation selective filtering decomposes the input into low-level orientation and spatial frequency representations. Grouping of spatially anisotropic orientation responses builds sketch-like representations of surface shape. Gradients in orientation fields and subsequent integration infers local surface geometry and globally consistent 3D depth. From the distributions in orientation responses summed in frequency, an estimate of the tilt and slant of the local surface can be obtained. The model suggests how 3D shape can be inferred from texture patterns and their image appearance in a hierarchically organized processing cascade along the cortical ventral stream. The proposed model integrates oriented texture gradient information that is encoded in distributed maps of orientation-frequency representations. The texture energy gradient information is defined by changes in the grouped summed normalized orientation-frequency response activity extracted from the textured object image. This activity is integrated by directed fields to generate a 3D shape representation of a complex object with depth ordering proportional to the fields output, with higher activity denoting larger distance in relative depth away from the viewer. PMID:27649387

Multi-component separation and analysis of bat echolocation calls.

PubMed

DiCecco, John; Gaudette, Jason E; Simmons, James A

2013-01-01

The vast majority of animal vocalizations contain multiple frequency modulated (FM) components with varying amounts of non-linear modulation and harmonic instability. This is especially true of biosonar sounds where precise time-frequency templates are essential for neural information processing of echoes. Understanding the dynamic waveform design by bats and other echolocating animals may help to improve the efficacy of man-made sonar through biomimetic design. Bats are known to adapt their call structure based on the echolocation task, proximity to nearby objects, and density of acoustic clutter. To interpret the significance of these changes, a method was developed for component separation and analysis of biosonar waveforms. Techniques for imaging in the time-frequency plane are typically limited due to the uncertainty principle and interference cross terms. This problem is addressed by extending the use of the fractional Fourier transform to isolate each non-linear component for separate analysis. Once separated, empirical mode decomposition can be used to further examine each component. The Hilbert transform may then successfully extract detailed time-frequency information from each isolated component. This multi-component analysis method is applied to the sonar signals of four species of bats recorded in-flight by radiotelemetry along with a comparison of other common time-frequency representations.

Turbulence and Solar p-Mode Oscillations

NASA Astrophysics Data System (ADS)

Bi, S. L.; Xu, H. Y.

The discrepancy between observed and theoretical mode frequencies can be used to examine the reliability of the standard solar model as a faithful representation of solar real situation. With the help of an improved time-dependent convective model that takes into account contribution of the full spatial and temporal turbulent energy spectrum, we study the influence of turbulent pressure on structure and solar p-mode frequencies. For the radial modes we find that the Reynolds stress produces signification modifications in structure and p-mode spectrum. Compared with an adiabatic approximation, the discrepancy is largely removed by the turbulent correction.

Equivalent circuit consideration of frequency-shift-type acceleration sensor

NASA Astrophysics Data System (ADS)

Sasaki, Yoshifumi; Sugawara, Sumio; Kudo, Subaru

2018-07-01

In this paper, an electrical equivalent circuit for the piezoelectrically driven frequency-shift-type acceleration sensor model is represented, and the equivalent circuit constants including the effect of the axial force are clarified for the first time. The results calculated by the finite element method are compared with the experimentally measured ones of the one-axis sensor of trial production. The result shows that the analyzed values almost agree with the measured ones, and that the equivalent circuit representation of the sensor is useful for electrical engineers in order to easily analyze the characteristics of the sensors.

Visual Speech-Training Aid for the Deaf

NASA Technical Reports Server (NTRS)

Miller, Robert J.

1987-01-01

Teaching deaf to speak aided by electronic system provides striking colored, pictorial representation of sound; energy at different frequencies as function of time. Other modalities, such as nasality, intra-oral pressure, and lip-muscle contraction, pictorialized simultaneously. Use of standard components, including personal microcomputer, helps reduce cost below prior voice-training systems. Speech-training system, microphone output separated by filters into narrow frequency bands, changed into digital signals, formatted by computer, and displayed on television screen. Output from other sensors displayed simultaneously or screen split to allow sound produced by student to be compared with that of teacher.

The pitch of vibrato tones: a model based on instantaneous frequency decomposition.

PubMed

Mesz, Bruno A; Eguia, Manuel C

2009-07-01

We study vibrato as the more ubiquitous manifestation of a nonstationary tone that can evoke a single overall pitch. Some recent results using nonsymmetrical vibrato tones suggest that the perceived pitch could be governed by some stability-sensitive mechanism. For nonstationary sounds the adequate tools are time-frequency representations (TFRs). We show that a recently proposed TFR could be the simplest framework to explain this hypothetical stability-sensitive mechanism. We propose a one-parameter model within this framework that is able to predict previously reported results and we present new results obtained from psychophysical experiments performed in our laboratory.

[Time perceptions and representations].

PubMed

Tordjman, S

2015-09-01

Representations of time and time measurements depend on subjective constructs that vary according to changes in our concepts, beliefs, societal needs and technical advances. Similarly, the past, the future and the present are subjective representations that depend on each individual's psychic time and biological time. Therefore, there is no single, one-size-fits-all time for everyone, but rather a different, subjective time for each individual. We need to acknowledge the existence of different inter-individual times but also intra-individual times, to which different functions and different rhythms are attached, depending on the system of reference. However, the construction of these time perceptions and representations is influenced by objective factors (physiological, physical and cognitive) related to neuroscience which will be presented and discussed in this article. Thus, studying representation and perception of time lies at the crossroads between neuroscience, human sciences and philosophy. Furthermore, it is possible to identify several constants among the many and various representations of time and their corresponding measures, regardless of the system of time reference. These include the notion of movements repeated in a stable rhythmic pattern involving the recurrence of the same interval of time, which enables us to define units of time of equal and invariable duration. This rhythmicity is also found at a physiological level and contributes through circadian rhythms, in particular the melatonin rhythm, to the existence of a biological time. Alterations of temporality in mental disorders will be also discussed in this article illustrated by certain developmental disorders such as autism spectrum disorders. In particular, the hypothesis will be developed that children with autism would need to create discontinuity out of continuity through stereotyped behaviors and/or interests. This discontinuity repeated at regular intervals could have been fundamentally lacking in their physiological development due to possibly altered circadian rhythms, including arhythmy and asynchrony. Time measurement, based on the repetition of discontinuity at regular intervals, involves also a spatial representation. It is our own trajectory through space-time, and thus our own motion, including the physiological process of aging, that affords us a representation of the passing of time, just as the countryside seems to be moving past us when we travel in a vehicle. Chinese and Indian societies actually have circular representations of time, and linear representations of time and its trajectory through space-time are currently a feature of Western societies. Circular time is collective time, and its metaphysical representations go beyond the life of a single individual, referring to the cyclical, or at least nonlinear, nature of time. Linear time is individual time, in that it refers to the scale of a person's lifetime, and it is physically represented by an arrow flying ineluctably from the past to the future. An intermediate concept can be proposed that acknowledges the existence of linear time involving various arrows of time corresponding to different lifespans (human, animal, plant, planet lifespans, etc.). In fact, the very notion of time would depend on the trajectory of each arrow of time, like shooting stars in the sky with different trajectory lengths which would define different time scales. The time scale of these various lifespans are very different (for example, a few decades for humans and a few days or hours for insects). It would not make sense to try to understand the passage of time experienced by an insect which may live only a few hours based on a human time scale. One hour in an insect's life cannot be compared to one experienced by a human. Yet again, it appears that there is a coexistence of different clocks based here on different lifespans. Finally, the evolution of our society focused on the present moment and choosing the cesium atom as the international reference unit of time measurement (cesium has a transition frequency of 9.192.631.77000 oscillations per second), will be questioned. We can consider that focusing on the present moment, in particular on instantaneity rather than infinity, prevents us from facing our own finitude. In conclusion, the question is raised that the current representation of time might be a means of managing our fear of death, giving us the illusion of controlling the uncontrollable, in particular the passage of time, and a means of avoiding to represent what many regard as non-representable, namely our own demise. Copyright © 2015 L’Encéphale. Published by Elsevier Masson SAS.. All rights reserved.

Wind Turbine Diagnosis under Variable Speed Conditions Using a Single Sensor Based on the Synchrosqueezing Transform Method.

PubMed

Guo, Yanjie; Chen, Xuefeng; Wang, Shibin; Sun, Ruobin; Zhao, Zhibin

2017-05-18

The gearbox is one of the key components in wind turbines. Gearbox fault signals are usually nonstationary and highly contaminated with noise. The presence of amplitude-modulated and frequency-modulated (AM-FM) characteristics compound the difficulty of precise fault diagnosis of wind turbines, therefore, it is crucial to develop an effective fault diagnosis method for such equipment. This paper presents an improved diagnosis method for wind turbines via the combination of synchrosqueezing transform and local mean decomposition. Compared to the conventional time-frequency analysis techniques, the improved method which is performed in non-real-time can effectively reduce the noise pollution of the signals and preserve the signal characteristics, and hence is suitable for the analysis of nonstationary signals with high noise. This method is further validated by simulated signals and practical vibration data measured from a 1.5 MW wind turbine. The results confirm that the proposed method can simultaneously control the noise and increase the accuracy of time-frequency representation.

Wind Turbine Diagnosis under Variable Speed Conditions Using a Single Sensor Based on the Synchrosqueezing Transform Method

PubMed Central

Guo, Yanjie; Chen, Xuefeng; Wang, Shibin; Sun, Ruobin; Zhao, Zhibin

2017-01-01

The gearbox is one of the key components in wind turbines. Gearbox fault signals are usually nonstationary and highly contaminated with noise. The presence of amplitude-modulated and frequency-modulated (AM-FM) characteristics compound the difficulty of precise fault diagnosis of wind turbines, therefore, it is crucial to develop an effective fault diagnosis method for such equipment. This paper presents an improved diagnosis method for wind turbines via the combination of synchrosqueezing transform and local mean decomposition. Compared to the conventional time-frequency analysis techniques, the improved method which is performed in non-real-time can effectively reduce the noise pollution of the signals and preserve the signal characteristics, and hence is suitable for the analysis of nonstationary signals with high noise. This method is further validated by simulated signals and practical vibration data measured from a 1.5 MW wind turbine. The results confirm that the proposed method can simultaneously control the noise and increase the accuracy of time-frequency representation. PMID:28524090

Instrument-independent analysis of music by means of the continuous wavelet transform

NASA Astrophysics Data System (ADS)

Olmo, Gabriella; Dovis, Fabio; Benotto, Paolo; Calosso, Claudio; Passaro, Pierluigi

1999-10-01

This paper deals with the problem of automatic recognition of music. Segments of digitized music are processed by means of a Continuous Wavelet Transform, properly chosen so as to match the spectral characteristics of the signal. In order to achieve a good time-scale representation of the signal components a novel wavelet has been designed suited to the musical signal features. particular care has been devoted towards an efficient implementation, which operates in the frequency domain, and includes proper segmentation and aliasing reduction techniques to make the analysis of long signals feasible. The method achieves very good performance in terms of both time and frequency selectivity, and can yield the estimate and the localization in time of both the fundamental frequency and the main harmonics of each tone. The analysis is used as a preprocessing step for a recognition algorithm, which we show to be almost independent on the instrument reproducing the sounds. Simulations are provided to demonstrate the effectiveness of the proposed method.

The Application of Time-Frequency Methods to HUMS

NASA Technical Reports Server (NTRS)

Pryor, Anna H.; Mosher, Marianne; Lewicki, David G.; Norvig, Peter (Technical Monitor)

2001-01-01

This paper reports the study of four time-frequency transforms applied to vibration signals and presents a new metric for comparing them for fault detection. The four methods to be described and compared are the Short Time Frequency Transform (STFT), the Choi-Williams Distribution (WV-CW), the Continuous Wavelet Transform (CWT) and the Discrete Wavelet Transform (DWT). Vibration data of bevel gear tooth fatigue cracks, under a variety of operating load levels, are analyzed using these methods. The new metric for automatic fault detection is developed and can be produced from any systematic numerical representation of the vibration signals. This new metric reveals indications of gear damage with all of the methods on this data set. Analysis with the CWT detects mechanical problems with the test rig not found with the other transforms. The WV-CW and CWT use considerably more resources than the STFT and the DWT. More testing of the new metric is needed to determine its value for automatic fault detection and to develop methods of setting the threshold for the metric.

Human cortical responses to slow and fast binaural beats reveal multiple mechanisms of binaural hearing.

PubMed

Ross, Bernhard; Miyazaki, Takahiro; Thompson, Jessica; Jamali, Shahab; Fujioka, Takako

2014-10-15

When two tones with slightly different frequencies are presented to both ears, they interact in the central auditory system and induce the sensation of a beating sound. At low difference frequencies, we perceive a single sound, which is moving across the head between the left and right ears. The percept changes to loudness fluctuation, roughness, and pitch with increasing beat rate. To examine the neural representations underlying these different perceptions, we recorded neuromagnetic cortical responses while participants listened to binaural beats at a continuously varying rate between 3 Hz and 60 Hz. Binaural beat responses were analyzed as neuromagnetic oscillations following the trajectory of the stimulus rate. Responses were largest in the 40-Hz gamma range and at low frequencies. Binaural beat responses at 3 Hz showed opposite polarity in the left and right auditory cortices. We suggest that this difference in polarity reflects the opponent neural population code for representing sound location. Binaural beats at any rate induced gamma oscillations. However, the responses were largest at 40-Hz stimulation. We propose that the neuromagnetic gamma oscillations reflect postsynaptic modulation that allows for precise timing of cortical neural firing. Systematic phase differences between bilateral responses suggest that separate sound representations of a sound object exist in the left and right auditory cortices. We conclude that binaural processing at the cortical level occurs with the same temporal acuity as monaural processing whereas the identification of sound location requires further interpretation and is limited by the rate of object representations. Copyright © 2014 the American Physiological Society.

Changing word usage predicts changing word durations in New Zealand English.

PubMed

Sóskuthy, Márton; Hay, Jennifer

2017-09-01

This paper investigates the emergence of lexicalized effects of word usage on word duration by looking at parallel changes in usage and duration over 130years in New Zealand English. Previous research has found that frequent words are shorter, informative words are longer, and words in utterance-final position are also longer. It has also been argued that some of these patterns are not simply online adjustments, but are incorporated into lexical representations. While these studies tend to focus on the synchronic aspects of such patterns, our corpus shows that word-usage patterns and word durations are not static over time. Many words change in duration and also change with respect to frequency, informativity and likelihood of occurring utterance-finally. Analysis of changing word durations over this time period shows substantial patterns of co-adaptation between word usage and word durations. Words that are increasing in frequency are becoming shorter. Words that are increasing/decreasing in informativity show a change in the same direction in duration (e.g. increasing informativity is associated with increasing duration). And words that are increasingly appearing utterance-finally are lengthening. These effects exist independently of the local effects of the predictors. For example, words that are increasing utterance-finally lengthen in all positions, including utterance-medially. We show that these results are compatible with a number of different views about lexical representations, but they cannot be explained without reference to a production-perception loop that allows speakers to update their representations dynamically on the basis of their experience. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

A coupled-oscillator model of olfactory bulb gamma oscillations

PubMed Central

2017-01-01

The olfactory bulb transforms not only the information content of the primary sensory representation, but also its underlying coding metric. High-variance, slow-timescale primary odor representations are transformed by bulbar circuitry into secondary representations based on principal neuron spike patterns that are tightly regulated in time. This emergent fast timescale for signaling is reflected in gamma-band local field potentials, presumably serving to efficiently integrate olfactory sensory information into the temporally regulated information networks of the central nervous system. To understand this transformation and its integration with interareal coordination mechanisms requires that we understand its fundamental dynamical principles. Using a biophysically explicit, multiscale model of olfactory bulb circuitry, we here demonstrate that an inhibition-coupled intrinsic oscillator framework, pyramidal resonance interneuron network gamma (PRING), best captures the diversity of physiological properties exhibited by the olfactory bulb. Most importantly, these properties include global zero-phase synchronization in the gamma band, the phase-restriction of informative spikes in principal neurons with respect to this common clock, and the robustness of this synchronous oscillatory regime to multiple challenging conditions observed in the biological system. These conditions include substantial heterogeneities in afferent activation levels and excitatory synaptic weights, high levels of uncorrelated background activity among principal neurons, and spike frequencies in both principal neurons and interneurons that are irregular in time and much lower than the gamma frequency. This coupled cellular oscillator architecture permits stable and replicable ensemble responses to diverse sensory stimuli under various external conditions as well as to changes in network parameters arising from learning-dependent synaptic plasticity. PMID:29140973

Development of models simulating operation of elements of radio devices, for solving problems of ensuring electromagnetic compatibility of radio electronic means

NASA Astrophysics Data System (ADS)

Glotov, V. V.; Ostroumov, I. V.; Romashchenko, M. A.

2018-05-01

To study the effect of phase-shift signals parameters on EMC of REM, a generalized signal generation model in a radio transmitter was developed which allows obtaining digital representations of phase-shift signals, which are a continuous pulse in the time domain and on the frequency axis with different signal element envelope shapes.

Early Bimodal Stimulation Benefits Language Acquisition for Children With Cochlear Implants.

PubMed

Moberly, Aaron C; Lowenstein, Joanna H; Nittrouer, Susan

2016-01-01

Adding a low-frequency acoustic signal to the cochlear implant (CI) signal (i.e., bimodal stimulation) for a period of time early in life improves language acquisition. Children must acquire sensitivity to the phonemic units of language to develop most language-related skills, including expressive vocabulary, working memory, and reading. Acquiring sensitivity to phonemic structure depends largely on having refined spectral (frequency) representations available in the signal, which does not happen with CIs alone. Combining the low-frequency acoustic signal available through hearing aids with the CI signal can enhance signal quality. A period with this bimodal stimulation has been shown to improve language skills in very young children. This study examined whether these benefits persist into childhood. Data were examined for 48 children with CIs implanted under age 3 years, participating in a longitudinal study. All children wore hearing aids before receiving a CI, but upon receiving a first CI, 24 children had at least 1 year of bimodal stimulation (Bimodal group), and 24 children had only electric stimulation subsequent to implantation (CI-only group). Measures of phonemic awareness were obtained at second and fourth grades, along with measures of expressive vocabulary, working memory, and reading. Children in the Bimodal group generally performed better on measures of phonemic awareness, and that advantage was reflected in other language measures. Having even a brief period of time early in life with combined electric-acoustic input provides benefits to language learning into childhood, likely because of the enhancement in spectral representations provided.

Representational dynamics of object recognition: Feedforward and feedback information flows.

PubMed

Goddard, Erin; Carlson, Thomas A; Dermody, Nadene; Woolgar, Alexandra

2016-03-01

Object perception involves a range of visual and cognitive processes, and is known to include both a feedfoward flow of information from early visual cortical areas to higher cortical areas, along with feedback from areas such as prefrontal cortex. Previous studies have found that low and high spatial frequency information regarding object identity may be processed over different timescales. Here we used the high temporal resolution of magnetoencephalography (MEG) combined with multivariate pattern analysis to measure information specifically related to object identity in peri-frontal and peri-occipital areas. Using stimuli closely matched in their low-level visual content, we found that activity in peri-occipital cortex could be used to decode object identity from ~80ms post stimulus onset, and activity in peri-frontal cortex could also be used to decode object identity from a later time (~265ms post stimulus onset). Low spatial frequency information related to object identity was present in the MEG signal at an earlier time than high spatial frequency information for peri-occipital cortex, but not for peri-frontal cortex. We additionally used Granger causality analysis to compare feedforward and feedback influences on representational content, and found evidence of both an early feedfoward flow and later feedback flow of information related to object identity. We discuss our findings in relation to existing theories of object processing and propose how the methods we use here could be used to address further questions of the neural substrates underlying object perception. Copyright © 2016 Elsevier Inc. All rights reserved.

Frequency Representation: Visualization and Clustering of Acoustic Data Using Self-Organizing Maps.

PubMed

Guo, Xinhua; Sun, Song; Yu, Xiantao; Wang, Pan; Nakamura, Kentaro

2017-11-01

Extraction and display of frequency information in three-dimensional (3D) acoustic data are important steps to analyze object characteristics, because the characteristics, such as profiles, sizes, surface structures, and material properties, may show frequency dependence. In this study, frequency representation (FR) based on phase information in multispectral acoustic imaging (MSAI) is proposed to overcome the limit of intensity or amplitude information in image display. Experiments are performed on 3D acoustic data collected from a rigid surface engraved with five different letters. The results show that the proposed FR technique can not only identify the depth of the five letters by the colors representing frequency characteristics but also demonstrate the 3D image of the five letters, providing more detailed characteristics that are unavailable by conventional acoustic imaging.

Time-frequency analysis of pediatric murmurs

NASA Astrophysics Data System (ADS)

Lombardo, Joseph S.; Blodgett, Lisa A.; Rosen, Ron S.; Najmi, Amir-Homayoon; Thompson, W. Reid

1998-05-01

Technology has provided many new tools to assist in the diagnosis of pathologic conditions of the heart. Echocardiography, Ultrafast CT, and MRI are just a few. While these tools are a valuable resource, they are typically too expensive, large and complex in operation for use in rural, homecare, and physician's office settings. Recent advances in computer performance, miniaturization, and acoustic signal processing, have yielded new technologies that when applied to heart sounds can provide low cost screening for pathologic conditions. The short duration and transient nature of these signals requires processing techniques that provide high resolution in both time and frequency. Short-time Fourier transforms, Wigner distributions, and wavelet transforms have been applied to signals form hearts with various pathologic conditions. While no single technique provides the ideal solution, the combination of tools provides a good representation of the acoustic features of the pathologies selected.

Simplified approach to the mixed time-averaging semiclassical initial value representation for the calculation of dense vibrational spectra

NASA Astrophysics Data System (ADS)

Buchholz, Max; Grossmann, Frank; Ceotto, Michele

2018-03-01

We present and test an approximate method for the semiclassical calculation of vibrational spectra. The approach is based on the mixed time-averaging semiclassical initial value representation method, which is simplified to a form that contains a filter to remove contributions from approximately harmonic environmental degrees of freedom. This filter comes at no additional numerical cost, and it has no negative effect on the accuracy of peaks from the anharmonic system of interest. The method is successfully tested for a model Hamiltonian and then applied to the study of the frequency shift of iodine in a krypton matrix. Using a hierarchic model with up to 108 normal modes included in the calculation, we show how the dynamical interaction between iodine and krypton yields results for the lowest excited iodine peaks that reproduce experimental findings to a high degree of accuracy.

Assessment of Homomorphic Analysis for Human Activity Recognition from Acceleration Signals.

PubMed

Vanrell, Sebastian Rodrigo; Milone, Diego Humberto; Rufiner, Hugo Leonardo

2017-07-03

Unobtrusive activity monitoring can provide valuable information for medical and sports applications. In recent years, human activity recognition has moved to wearable sensors to deal with unconstrained scenarios. Accelerometers are the preferred sensors due to their simplicity and availability. Previous studies have examined several \\azul{classic} techniques for extracting features from acceleration signals, including time-domain, time-frequency, frequency-domain, and other heuristic features. Spectral and temporal features are the preferred ones and they are generally computed from acceleration components, leaving the acceleration magnitude potential unexplored. In this study, based on homomorphic analysis, a new type of feature extraction stage is proposed in order to exploit discriminative activity information present in acceleration signals. Homomorphic analysis can isolate the information about whole body dynamics and translate it into a compact representation, called cepstral coefficients. Experiments have explored several configurations of the proposed features, including size of representation, signals to be used, and fusion with other features. Cepstral features computed from acceleration magnitude obtained one of the highest recognition rates. In addition, a beneficial contribution was found when time-domain and moving pace information was included in the feature vector. Overall, the proposed system achieved a recognition rate of 91.21% on the publicly available SCUT-NAA dataset. To the best of our knowledge, this is the highest recognition rate on this dataset.

High-resolution time-frequency representation of EEG data using multi-scale wavelets

NASA Astrophysics Data System (ADS)

Li, Yang; Cui, Wei-Gang; Luo, Mei-Lin; Li, Ke; Wang, Lina

2017-09-01

An efficient time-varying autoregressive (TVAR) modelling scheme that expands the time-varying parameters onto the multi-scale wavelet basis functions is presented for modelling nonstationary signals and with applications to time-frequency analysis (TFA) of electroencephalogram (EEG) signals. In the new parametric modelling framework, the time-dependent parameters of the TVAR model are locally represented by using a novel multi-scale wavelet decomposition scheme, which can allow the capability to capture the smooth trends as well as track the abrupt changes of time-varying parameters simultaneously. A forward orthogonal least square (FOLS) algorithm aided by mutual information criteria are then applied for sparse model term selection and parameter estimation. Two simulation examples illustrate that the performance of the proposed multi-scale wavelet basis functions outperforms the only single-scale wavelet basis functions or Kalman filter algorithm for many nonstationary processes. Furthermore, an application of the proposed method to a real EEG signal demonstrates the new approach can provide highly time-dependent spectral resolution capability.

Adapted wavelet transform improves time-frequency representations: a study of auditory elicited P300-like event-related potentials in rats

NASA Astrophysics Data System (ADS)

Richard, Nelly; Laursen, Bettina; Grupe, Morten; Drewes, Asbjørn M.; Graversen, Carina; Sørensen, Helge B. D.; Bastlund, Jesper F.

2017-04-01

Objective. Active auditory oddball paradigms are simple tone discrimination tasks used to study the P300 deflection of event-related potentials (ERPs). These ERPs may be quantified by time-frequency analysis. As auditory stimuli cause early high frequency and late low frequency ERP oscillations, the continuous wavelet transform (CWT) is often chosen for decomposition due to its multi-resolution properties. However, as the conventional CWT traditionally applies only one mother wavelet to represent the entire spectrum, the time-frequency resolution is not optimal across all scales. To account for this, we developed and validated a novel method specifically refined to analyse P300-like ERPs in rats. Approach. An adapted CWT (aCWT) was implemented to preserve high time-frequency resolution across all scales by commissioning of multiple wavelets operating at different scales. First, decomposition of simulated ERPs was illustrated using the classical CWT and the aCWT. Next, the two methods were applied to EEG recordings obtained from prefrontal cortex in rats performing a two-tone auditory discrimination task. Main results. While only early ERP frequency changes between responses to target and non-target tones were detected by the CWT, both early and late changes were successfully described with strong accuracy by the aCWT in rat ERPs. Increased frontal gamma power and phase synchrony was observed particularly within theta and gamma frequency bands during deviant tones. Significance. The study suggests superior performance of the aCWT over the CWT in terms of detailed quantification of time-frequency properties of ERPs. Our methodological investigation indicates that accurate and complete assessment of time-frequency components of short-time neural signals is feasible with the novel analysis approach which may be advantageous for characterisation of several types of evoked potentials in particularly rodents.

High-resolution Temporal Representations of Alcohol and Tobacco Behaviors from Social Media Data

PubMed Central

Huang, Tom; Elghafari, Anas; Relia, Kunal; Chunara, Rumi

2017-01-01

Understanding tobacco- and alcohol-related behavioral patterns is critical for uncovering risk factors and potentially designing targeted social computing intervention systems. Given that we make choices multiple times per day, hourly and daily patterns are critical for better understanding behaviors. Here, we combine natural language processing, machine learning and time series analyses to assess Twitter activity specifically related to alcohol and tobacco consumption and their sub-daily, daily and weekly cycles. Twitter self-reports of alcohol and tobacco use are compared to other data streams available at similar temporal resolution. We assess if discussion of drinking by inferred underage versus legal age people or discussion of use of different types of tobacco products can be differentiated using these temporal patterns. We find that time and frequency domain representations of behaviors on social media can provide meaningful and unique insights, and we discuss the types of behaviors for which the approach may be most useful. PMID:29264592

Wavelet-frequency analysis for the detection of discontinuities in switched system models of human balance.

PubMed

Nema, Salam; Kowalczyk, Piotr; Loram, Ian

2017-01-01

This paper is concerned with detecting the presence of switching behavior in experimentally obtained posturographic data sets by means of a novel algorithm that is based on a combination of wavelet analysis and Hilbert transform. As a test-bed for the algorithm, we first use a switched model of human balance control during quiet standing with known switching behavior in four distinct configurations. We obtain a time-frequency representation of a signal generated by our model system. We are then able to detect manifestations of discontinuities (switchings) in the signal as spiking behavior. The frequency of switchings, measured by means of our algorithm and detected in our models systems, agrees with the frequency of spiking behavior found in the experimentally obtained posturographic data. Copyright © 2016. Published by Elsevier B.V.

Image Quality Assessment Using the Joint Spatial/Spatial-Frequency Representation

NASA Astrophysics Data System (ADS)

Beghdadi, Azeddine; Iordache, Răzvan

2006-12-01

This paper demonstrates the usefulness of spatial/spatial-frequency representations in image quality assessment by introducing a new image dissimilarity measure based on 2D Wigner-Ville distribution (WVD). The properties of 2D WVD are shortly reviewed, and the important issue of choosing the analytic image is emphasized. The WVD-based measure is shown to be correlated with subjective human evaluation, which is the premise towards an image quality assessor developed on this principle.

Correspondence Search Mitigation Using Feature Space Anti-Aliasing

DTIC Science & Technology

2007-01-01

trackers are widely used in astro -inertial nav- igation systems for long-range aircraft, space navigation, and ICBM guidance. When ground images are to be...frequency domain representation of the point spread function, H( fx , fy), is called the optical transfer function. Applying the Fourier transform to the...frequency domain representation of the image: I( fx , fy, t) = O( fx , fy, t)H( fx , fy) (4) In most conditions, the projected scene can be treated as a

Discrimination of Dynamic Tactile Contact by Temporally Precise Event Sensing in Spiking Neuromorphic Networks

PubMed Central

Lee, Wang Wei; Kukreja, Sunil L.; Thakor, Nitish V.

2017-01-01

This paper presents a neuromorphic tactile encoding methodology that utilizes a temporally precise event-based representation of sensory signals. We introduce a novel concept where touch signals are characterized as patterns of millisecond precise binary events to denote pressure changes. This approach is amenable to a sparse signal representation and enables the extraction of relevant features from thousands of sensing elements with sub-millisecond temporal precision. We also proposed measures adopted from computational neuroscience to study the information content within the spiking representations of artificial tactile signals. Implemented on a state-of-the-art 4096 element tactile sensor array with 5.2 kHz sampling frequency, we demonstrate the classification of transient impact events while utilizing 20 times less communication bandwidth compared to frame based representations. Spiking sensor responses to a large library of contact conditions were also synthesized using finite element simulations, illustrating an 8-fold improvement in information content and a 4-fold reduction in classification latency when millisecond-precise temporal structures are available. Our research represents a significant advance, demonstrating that a neuromorphic spatiotemporal representation of touch is well suited to rapid identification of critical contact events, making it suitable for dynamic tactile sensing in robotic and prosthetic applications. PMID:28197065

Enhanced representations of lithium-ion batteries in power systems models and their effect on the valuation of energy arbitrage applications

NASA Astrophysics Data System (ADS)

Sakti, Apurba; Gallagher, Kevin G.; Sepulveda, Nestor; Uckun, Canan; Vergara, Claudio; de Sisternes, Fernando J.; Dees, Dennis W.; Botterud, Audun

2017-02-01

We develop three novel enhanced mixed integer-linear representations of the power limit of the battery and its efficiency as a function of the charge and discharge power and the state of charge of the battery, which can be directly implemented in large-scale power systems models and solved with commercial optimization solvers. Using these battery representations, we conduct a techno-economic analysis of the performance of a 10 MWh lithium-ion battery system testing the effect of a 5-min vs. a 60-min price signal on profits using real time prices from a selected node in the MISO electricity market. Results show that models of lithium-ion batteries where the power limits and efficiency are held constant overestimate profits by 10% compared to those obtained from an enhanced representation that more closely matches the real behavior of the battery. When the battery system is exposed to a 5-min price signal, the energy arbitrage profitability improves by 60% compared to that from hourly price exposure. These results indicate that a more accurate representation of li-ion batteries as well as the market rules that govern the frequency of electricity prices can play a major role on the estimation of the value of battery technologies for power grid applications.

Running wavelet archetype aids the determination of heart rate from the video photoplethysmogram during motion.

PubMed

Addison, Paul S; Foo, David M H; Jacquel, Dominique

2017-07-01

The extraction of heart rate from a video-based biosignal during motion using a novel wavelet-based ensemble averaging method is described. Running Wavelet Archetyping (RWA) allows for the enhanced extraction of pulse information from the time-frequency representation, from which a video-based heart rate (HRvid) can be derived. This compares favorably to a reference heart rate derived from a pulse oximeter.

Better Decision Making Through Representation and Reduction of Uncertainty in C3I Information Systems

DTIC Science & Technology

2007-11-01

preparatory experiments 61 Research objectives 61 Researchers roles 61 Experimental methods 62 The Battle Lab experiment 62 The Field experiment 63...2004). Previous stages of research were based on observations by the research team in a company-level simulation experiment and a brigade-level field ...times , ,.." , , ,.. 26 III Request for infonnation 26 Frequencies ofinformation requests 27 Effects ofadditional information on decision quality 28

Estimating the Volterra Series Transfer Function over coherent optical OFDM for efficient monitoring of the fiber channel nonlinearity.

PubMed

Shulkind, Gal; Nazarathy, Moshe

2012-12-17

We present an efficient method for system identification (nonlinear channel estimation) of third order nonlinear Volterra Series Transfer Function (VSTF) characterizing the four-wave-mixing nonlinear process over a coherent OFDM fiber link. Despite the seemingly large number of degrees of freedom in the VSTF (cubic in the number of frequency points) we identified a compressed VSTF representation which does not entail loss of information. Additional slightly lossy compression may be obtained by discarding very low power VSTF coefficients associated with regions of destructive interference in the FWM phased array effect. Based on this two-staged VSTF compressed representation, we develop a robust and efficient algorithm of nonlinear system identification (optical performance monitoring) estimating the VSTF by transmission of an extended training sequence over the OFDM link, performing just a matrix-vector multiplication at the receiver by a pseudo-inverse matrix which is pre-evaluated offline. For 512 (1024) frequency samples per channel, the VSTF measurement takes less than 1 (10) msec to complete with computational complexity of one real-valued multiply-add operation per time sample. Relative to a naïve exhaustive three-tone-test, our algorithm is far more tolerant of ASE additive noise and its acquisition time is orders of magnitude faster.

Heart rate variability analysis based on time-frequency representation and entropies in hypertrophic cardiomyopathy patients.

PubMed

Clariá, F; Vallverdú, M; Baranowski, R; Chojnowska, L; Caminal, P

2008-03-01

In hypertrophic cardiomyopathy (HCM) patients there is an increased risk of premature death, which can occur with little or no warning. Furthermore, classification for sudden cardiac death on patients with HCM is very difficult. The aim of our study was to improve the prognostic value of heart rate variability (HRV) in HCM patients, giving insight into changes of the autonomic nervous system. In this way, the suitability of linear and nonlinear measures was studied to assess the HRV. These measures were based on time-frequency representation (TFR) and on Shannon and Rényi entropies, and compared with traditional HRV measures. Holter recordings of 64 patients with HCM and 55 healthy subjects were analyzed. The HCM patients consisted of two groups: 13 high risk patients, after aborted sudden cardiac death (SCD); 51 low risk patients, without SCD. Five-hour RR signals, corresponding to the sleep period of the subjects, were considered for the analysis as a comparable standard situation. These RR signals were filtered in the three frequency bands: very low frequency band (VLF, 0-0.04 Hz), low frequency band (LF, 0.04-0.15 Hz) and high frequency band (HF, 0.15-0.45 Hz). TFR variables based on instantaneous frequency and energy functions were able to classify HCM patients and healthy subjects (control group). Results revealed that measures obtained from TFR analysis of the HRV better classified the groups of subjects than traditional HRV parameters. However, results showed that nonlinear measures improved group classification. It was observed that entropies calculated in the HF band showed the highest statistically significant levels comparing the HCM group and the control group, p-value < 0.0005. The values of entropy measures calculated in the HCM group presented lower values, indicating a decreasing of complexity, than those calculated from the control group. Moreover, similar behavior was observed comparing high and low risk of premature death, the values of the entropy being lower in high risk patients, p-value < 0.05, indicating an increase of predictability. Furthermore, measures from information entropy, but not from TFR, seem to be useful for enhanced risk stratification in HCM patients with an increased risk of sudden cardiac death.

Color-motion feature-binding errors are mediated by a higher-order chromatic representation

PubMed Central

Shevell, Steven K.; Wang, Wei

2017-01-01

Peripheral and central moving objects of the same color may be perceived to move in the same direction even though peripheral objects have a different true direction of motion [Nature 429, 262 (2004)]. The perceived, illusory direction of peripheral motion is a color-motion feature-binding error. Recent work shows that such binding errors occur even without an exact color match between central and peripheral objects, and, moreover, the frequency of the binding errors in the periphery declines as the chromatic difference increases between the central and peripheral objects [J. Opt. Soc. Am. A 31, A60 (2014)]. This change in the frequency of binding errors with the chromatic difference raises the general question of the chromatic representation from which the difference is determined. Here, basic properties of the chromatic representation are tested to discover whether it depends on independent chromatic differences on the l and the s cardinal axes or, alternatively, on a more specific higher-order chromatic representation. Experimental tests compared the rate of feature-binding errors when the central and peripheral colors had the identical s chromaticity (so zero difference in s) and a fixed magnitude of l difference, while varying the identical s level in center and periphery (thus always keeping the s difference at zero). A chromatic representation based on independent l and s differences would result in the same frequency of color-motion binding errors at every s level. The results are contrary to this prediction, thus showing that the chromatic representation at the level of color-motion feature binding depends on a higherorder chromatic mechanism. PMID:26974945

Automated Diagnosis Coding with Combined Text Representations.

PubMed

Berndorfer, Stefan; Henriksson, Aron

2017-01-01

Automated diagnosis coding can be provided efficiently by learning predictive models from historical data; however, discriminating between thousands of codes while allowing a variable number of codes to be assigned is extremely difficult. Here, we explore various text representations and classification models for assigning ICD-9 codes to discharge summaries in MIMIC-III. It is shown that the relative effectiveness of the investigated representations depends on the frequency of the diagnosis code under consideration and that the best performance is obtained by combining models built using different representations.

Frequency spirals

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ottino-Löffler, Bertrand; Strogatz, Steven H., E-mail: strogatz@cornell.edu

2016-09-15

We study the dynamics of coupled phase oscillators on a two-dimensional Kuramoto lattice with periodic boundary conditions. For coupling strengths just below the transition to global phase-locking, we find localized spatiotemporal patterns that we call “frequency spirals.” These patterns cannot be seen under time averaging; they become visible only when we examine the spatial variation of the oscillators' instantaneous frequencies, where they manifest themselves as two-armed rotating spirals. In the more familiar phase representation, they appear as wobbly periodic patterns surrounding a phase vortex. Unlike the stationary phase vortices seen in magnetic spin systems, or the rotating spiral waves seenmore » in reaction-diffusion systems, frequency spirals librate: the phases of the oscillators surrounding the central vortex move forward and then backward, executing a periodic motion with zero winding number. We construct the simplest frequency spiral and characterize its properties using analytical and numerical methods. Simulations show that frequency spirals in large lattices behave much like this simple prototype.« less

The contribution of stimulus frequency and recency to set-size effects.

PubMed

van 't Wout, Félice

2018-06-01

Hick's law describes the increase in choice reaction time (RT) with the number of stimulus-response (S-R) mappings. However, in choice RT experiments, set-size is typically confounded with stimulus recency and frequency: With a smaller set-size, each stimulus occurs on average more frequently and more recently than with a larger set-size. To determine to what extent stimulus recency and frequency contribute to the set-size effect, stimulus set-size was manipulated independently of stimulus recency and frequency, by keeping recency and frequency constant for a subset of the stimuli. Although this substantially reduced the set-size effect (by approximately two-thirds for these stimuli), it did not eliminate it. Thus, the time required to retrieve an S-R mapping from memory is (at least in part) determined by the number of alternatives. In contrast, a recent task switching study (Van 't Wout et al. in Journal of Experimental Psychology: Learning, Memory & Cognition., 41, 363-376, 2015) using the same manipulation found that the time required to retrieve a task-set from memory is not influenced by the number of alternatives per se. Hence, this experiment further supports a distinction between two levels of representation in task-set control: The level of task-sets, and the level of S-R mappings.

Statistical Frequency-Dependent Analysis of Trial-to-Trial Variability in Single Time Series by Recurrence Plots.

PubMed

Tošić, Tamara; Sellers, Kristin K; Fröhlich, Flavio; Fedotenkova, Mariia; Beim Graben, Peter; Hutt, Axel

2015-01-01

For decades, research in neuroscience has supported the hypothesis that brain dynamics exhibits recurrent metastable states connected by transients, which together encode fundamental neural information processing. To understand the system's dynamics it is important to detect such recurrence domains, but it is challenging to extract them from experimental neuroscience datasets due to the large trial-to-trial variability. The proposed methodology extracts recurrent metastable states in univariate time series by transforming datasets into their time-frequency representations and computing recurrence plots based on instantaneous spectral power values in various frequency bands. Additionally, a new statistical inference analysis compares different trial recurrence plots with corresponding surrogates to obtain statistically significant recurrent structures. This combination of methods is validated by applying it to two artificial datasets. In a final study of visually-evoked Local Field Potentials in partially anesthetized ferrets, the methodology is able to reveal recurrence structures of neural responses with trial-to-trial variability. Focusing on different frequency bands, the δ-band activity is much less recurrent than α-band activity. Moreover, α-activity is susceptible to pre-stimuli, while δ-activity is much less sensitive to pre-stimuli. This difference in recurrence structures in different frequency bands indicates diverse underlying information processing steps in the brain.

Statistical Frequency-Dependent Analysis of Trial-to-Trial Variability in Single Time Series by Recurrence Plots

PubMed Central

Tošić, Tamara; Sellers, Kristin K.; Fröhlich, Flavio; Fedotenkova, Mariia; beim Graben, Peter; Hutt, Axel

2016-01-01

For decades, research in neuroscience has supported the hypothesis that brain dynamics exhibits recurrent metastable states connected by transients, which together encode fundamental neural information processing. To understand the system's dynamics it is important to detect such recurrence domains, but it is challenging to extract them from experimental neuroscience datasets due to the large trial-to-trial variability. The proposed methodology extracts recurrent metastable states in univariate time series by transforming datasets into their time-frequency representations and computing recurrence plots based on instantaneous spectral power values in various frequency bands. Additionally, a new statistical inference analysis compares different trial recurrence plots with corresponding surrogates to obtain statistically significant recurrent structures. This combination of methods is validated by applying it to two artificial datasets. In a final study of visually-evoked Local Field Potentials in partially anesthetized ferrets, the methodology is able to reveal recurrence structures of neural responses with trial-to-trial variability. Focusing on different frequency bands, the δ-band activity is much less recurrent than α-band activity. Moreover, α-activity is susceptible to pre-stimuli, while δ-activity is much less sensitive to pre-stimuli. This difference in recurrence structures in different frequency bands indicates diverse underlying information processing steps in the brain. PMID:26834580

Optical digital chaos cryptography

NASA Astrophysics Data System (ADS)

Arenas-Pingarrón, Álvaro; González-Marcos, Ana P.; Rivas-Moscoso, José M.; Martín-Pereda, José A.

2007-10-01

In this work we present a new way to mask the data in a one-user communication system when direct sequence - code division multiple access (DS-CDMA) techniques are used. The code is generated by a digital chaotic generator, originally proposed by us and previously reported for a chaos cryptographic system. It is demonstrated that if the user's data signal is encoded with a bipolar phase-shift keying (BPSK) technique, usual in DS-CDMA, it can be easily recovered from a time-frequency domain representation. To avoid this situation, a new system is presented in which a previous dispersive stage is applied to the data signal. A time-frequency domain analysis is performed, and the devices required at the transmitter and receiver end, both user-independent, are presented for the optical domain.

A generalized time-frequency subtraction method for robust speech enhancement based on wavelet filter banks modeling of human auditory system.

PubMed

Shao, Yu; Chang, Chip-Hong

2007-08-01

We present a new speech enhancement scheme for a single-microphone system to meet the demand for quality noise reduction algorithms capable of operating at a very low signal-to-noise ratio. A psychoacoustic model is incorporated into the generalized perceptual wavelet denoising method to reduce the residual noise and improve the intelligibility of speech. The proposed method is a generalized time-frequency subtraction algorithm, which advantageously exploits the wavelet multirate signal representation to preserve the critical transient information. Simultaneous masking and temporal masking of the human auditory system are modeled by the perceptual wavelet packet transform via the frequency and temporal localization of speech components. The wavelet coefficients are used to calculate the Bark spreading energy and temporal spreading energy, from which a time-frequency masking threshold is deduced to adaptively adjust the subtraction parameters of the proposed method. An unvoiced speech enhancement algorithm is also integrated into the system to improve the intelligibility of speech. Through rigorous objective and subjective evaluations, it is shown that the proposed speech enhancement system is capable of reducing noise with little speech degradation in adverse noise environments and the overall performance is superior to several competitive methods.

Adaptive multimode signal reconstruction from time–frequency representations

PubMed Central

Meignen, Sylvain; Oberlin, Thomas; Depalle, Philippe; Flandrin, Patrick

2016-01-01

This paper discusses methods for the adaptive reconstruction of the modes of multicomponent AM–FM signals by their time–frequency (TF) representation derived from their short-time Fourier transform (STFT). The STFT of an AM–FM component or mode spreads the information relative to that mode in the TF plane around curves commonly called ridges. An alternative view is to consider a mode as a particular TF domain termed a basin of attraction. Here we discuss two new approaches to mode reconstruction. The first determines the ridge associated with a mode by considering the location where the direction of the reassignment vector sharply changes, the technique used to determine the basin of attraction being directly derived from that used for ridge extraction. A second uses the fact that the STFT of a signal is fully characterized by its zeros (and then the particular distribution of these zeros for Gaussian noise) to deduce an algorithm to compute the mode domains. For both techniques, mode reconstruction is then carried out by simply integrating the information inside these basins of attraction or domains. PMID:26953184

Textural timbre

PubMed Central

Hollins, Mark

2009-01-01

During haptic exploration of surfaces, complex mechanical oscillations—of surface displacement and air pressure—are generated, which are then transduced by receptors in the skin and in the inner ear. Tactile and auditory signals thus convey redundant information about texture, partially carried in the spectral content of these signals. It is no surprise, then, that the representation of temporal frequency is linked in the auditory and somatosensory systems. An emergent hypothesis is that there exists a supramodal representation of temporal frequency, and by extension texture. PMID:19721886

Optical frequency selective surface design using a GPU accelerated finite element boundary integral method

NASA Astrophysics Data System (ADS)

Ashbach, Jason A.

Periodic metallodielectric frequency selective surface (FSS) designs have historically seen widespread use in the microwave and radio frequency spectra. By scaling the dimensions of an FSS unit cell for use in a nano-fabrication process, these concepts have recently been adapted for use in optical applications as well. While early optical designs have been limited to wellunderstood geometries or optimized pixelated screens, nano-fabrication, lithographic and interconnect technology has progressed to a point where it is possible to fabricate metallic screens of arbitrary geometries featuring curvilinear or even three-dimensional characteristics that are only tens of nanometers wide. In order to design an FSS featuring such characteristics, it is important to have a robust numerical solver that features triangular elements in purely two-dimensional geometries and prismatic or tetrahedral elements in three-dimensional geometries. In this dissertation, a periodic finite element method code has been developed which features prismatic elements whose top and bottom boundaries are truncated by numerical integration of the boundary integral as opposed to an approximate representation found in a perfectly matched layer. However, since no exact solution exists for the calculation of triangular elements in a boundary integral, this process can be time consuming. To address this, these calculations were optimized for parallelization such that they may be done on a graphics processor, which provides a large increase in computational speed. Additionally, a simple geometrical representation using a Bezier surface is presented which provides generality with few variables. With a fast numerical solver coupled with a lowvariable geometric representation, a heuristic optimization algorithm has been used to develop several optical designs such as an absorber, a circular polarization filter, a transparent conductive surface and an enhanced, optical modulator.

Factors controlling high-frequency radiation from extended ruptures

NASA Astrophysics Data System (ADS)

Beresnev, Igor A.

2017-09-01

Small-scale slip heterogeneity or variations in rupture velocity on the fault plane are often invoked to explain the high-frequency radiation from earthquakes. This view has no theoretical basis, which follows, for example, from the representation integral of elasticity, an exact solution for the radiated wave field. The Fourier transform, applied to the integral, shows that the seismic spectrum is fully controlled by that of the source time function, while the distribution of final slip and rupture acceleration/deceleration only contribute to directivity. This inference is corroborated by the precise numerical computation of the full radiated field from the representation integral. We compare calculated radiation from four finite-fault models: (1) uniform slip function with low slip velocity, (2) slip function spatially modulated by a sinusoidal function, (3) slip function spatially modulated by a sinusoidal function with random roughness added, and (4) uniform slip function with high slip velocity. The addition of "asperities," both regular and irregular, does not cause any systematic increase in the spectral level of high-frequency radiation, except for the creation of maxima due to constructive interference. On the other hand, an increase in the maximum rate of slip on the fault leads to highly amplified high frequencies, in accordance with the prediction on the basis of a simple point-source treatment of the fault. Hence, computations show that the temporal rate of slip, not the spatial heterogeneity on faults, is the predominant factor forming the high-frequency radiation and thus controlling the velocity and acceleration of the resulting ground motions.

Extracting surface waves, hum and normal modes: time-scale phase-weighted stack and beyond

NASA Astrophysics Data System (ADS)

Ventosa, Sergi; Schimmel, Martin; Stutzmann, Eleonore

2017-10-01

Stacks of ambient noise correlations are routinely used to extract empirical Green's functions (EGFs) between station pairs. The time-frequency phase-weighted stack (tf-PWS) is a physically intuitive nonlinear denoising method that uses the phase coherence to improve EGF convergence when the performance of conventional linear averaging methods is not sufficient. The high computational cost of a continuous approach to the time-frequency transformation is currently a main limitation in ambient noise studies. We introduce the time-scale phase-weighted stack (ts-PWS) as an alternative extension of the phase-weighted stack that uses complex frames of wavelets to build a time-frequency representation that is much more efficient and fast to compute and that preserve the performance and flexibility of the tf-PWS. In addition, we propose two strategies: the unbiased phase coherence and the two-stage ts-PWS methods to further improve noise attenuation, quality of the extracted signals and convergence speed. We demonstrate that these approaches enable to extract minor- and major-arc Rayleigh waves (up to the sixth Rayleigh wave train) from many years of data from the GEOSCOPE global network. Finally we also show that fundamental spheroidal modes can be extracted from these EGF.

Ventricular Fibrillation and Tachycardia detection from surface ECG using time-frequency representation images as input dataset for machine learning.

PubMed

Mjahad, A; Rosado-Muñoz, A; Bataller-Mompeán, M; Francés-Víllora, J V; Guerrero-Martínez, J F

2017-04-01

To safely select the proper therapy for Ventricullar Fibrillation (VF) is essential to distinct it correctly from Ventricular Tachycardia (VT) and other rhythms. Provided that the required therapy would not be the same, an erroneous detection might lead to serious injuries to the patient or even cause Ventricular Fibrillation (VF). The main novelty of this paper is the use of time-frequency (t-f) representation images as the direct input to the classifier. We hypothesize that this method allow to improve classification results as it allows to eliminate the typical feature selection and extraction stage, and its corresponding loss of information. The standard AHA and MIT-BIH databases were used for evaluation and comparison with other authors. Previous to t-f Pseudo Wigner-Ville (PWV) calculation, only a basic preprocessing for denoising and signal alignment is necessary. In order to check the validity of the method independently of the classifier, four different classifiers are used: Logistic Regression with L2 Regularization (L2 RLR), Adaptive Neural Network Classifier (ANNC), Support Vector Machine (SSVM), and Bagging classifier (BAGG). The main classification results for VF detection (including flutter episodes) are 95.56% sensitivity and 98.8% specificity, 88.80% sensitivity and 99.5% specificity for ventricular tachycardia (VT), 98.98% sensitivity and 97.7% specificity for normal sinus, and 96.87% sensitivity and 99.55% specificity for other rhythms. Results shows that using t-f data representations to feed classifiers provide superior performance values than the feature selection strategies used in previous works. It opens the door to be used in any other detection applications. Copyright © 2017 Elsevier B.V. All rights reserved.

Bearing fault diagnosis using a whale optimization algorithm-optimized orthogonal matching pursuit with a combined time-frequency atom dictionary

NASA Astrophysics Data System (ADS)

Zhang, Xin; Liu, Zhiwen; Miao, Qiang; Wang, Lei

2018-07-01

Condition monitoring and fault diagnosis of rolling element bearings are significant to guarantee the reliability and functionality of a mechanical system, production efficiency, and plant safety. However, this is almost invariably a formidable challenge because the fault features are often buried by strong background noises and other unstable interference components. To satisfactorily extract the bearing fault features, a whale optimization algorithm (WOA)-optimized orthogonal matching pursuit (OMP) with a combined time-frequency atom dictionary is proposed in this paper. Firstly, a combined time-frequency atom dictionary whose atom is a combination of Fourier dictionary atom and impact time-frequency dictionary atom is designed according to the properties of bearing fault vibration signal. Furthermore, to improve the efficiency and accuracy of signal sparse representation, the WOA is introduced into the OMP algorithm to optimize the atom parameters for best approximating the original signal with the dictionary atoms. The proposed method is validated through analyzing the bearing fault simulation signal and the real vibration signals collected from an experimental bearing and a wheelset bearing of high-speed trains. The comparisons with the respect to the state of the art in the field are illustrated in detail, which highlight the advantages of the proposed method.

Identification of bearing faults using time domain zero-crossings

NASA Astrophysics Data System (ADS)

William, P. E.; Hoffman, M. W.

2011-11-01

In this paper, zero-crossing characteristic features are employed for early detection and identification of single point bearing defects in rotating machinery. As a result of bearing defects, characteristic defect frequencies appear in the machine vibration signal, normally requiring spectral analysis or envelope analysis to identify the defect type. Zero-crossing features are extracted directly from the time domain vibration signal using only the duration between successive zero-crossing intervals and do not require estimation of the rotational frequency. The features are a time domain representation of the composite vibration signature in the spectral domain. Features are normalized by the length of the observation window and classification is performed using a multilayer feedforward neural network. The model was evaluated on vibration data recorded using an accelerometer mounted on an induction motor housing subjected to a number of single point defects with different severity levels.

Digital signal processing techniques for pitch shifting and time scaling of audio signals

NASA Astrophysics Data System (ADS)

Buś, Szymon; Jedrzejewski, Konrad

2016-09-01

In this paper, we present the techniques used for modifying the spectral content (pitch shifting) and for changing the time duration (time scaling) of an audio signal. A short introduction gives a necessary background for understanding the discussed issues and contains explanations of the terms used in the paper. In subsequent sections we present three different techniques appropriate both for pitch shifting and for time scaling. These techniques use three different time-frequency representations of a signal, namely short-time Fourier transform (STFT), continuous wavelet transform (CWT) and constant-Q transform (CQT). The results of simulation studies devoted to comparison of the properties of these methods are presented and discussed in the paper.

Compensating Level-Dependent Frequency Representation in Auditory Cortex by Synaptic Integration of Corticocortical Input

PubMed Central

Happel, Max F. K.; Ohl, Frank W.

2017-01-01

Robust perception of auditory objects over a large range of sound intensities is a fundamental feature of the auditory system. However, firing characteristics of single neurons across the entire auditory system, like the frequency tuning, can change significantly with stimulus intensity. Physiological correlates of level-constancy of auditory representations hence should be manifested on the level of larger neuronal assemblies or population patterns. In this study we have investigated how information of frequency and sound level is integrated on the circuit-level in the primary auditory cortex (AI) of the Mongolian gerbil. We used a combination of pharmacological silencing of corticocortically relayed activity and laminar current source density (CSD) analysis. Our data demonstrate that with increasing stimulus intensities progressively lower frequencies lead to the maximal impulse response within cortical input layers at a given cortical site inherited from thalamocortical synaptic inputs. We further identified a temporally precise intercolumnar synaptic convergence of early thalamocortical and horizontal corticocortical inputs. Later tone-evoked activity in upper layers showed a preservation of broad tonotopic tuning across sound levels without shifts towards lower frequencies. Synaptic integration within corticocortical circuits may hence contribute to a level-robust representation of auditory information on a neuronal population level in the auditory cortex. PMID:28046062

Perceptual Simulations and Linguistic Representations Have Differential Effects on Speeded Relatedness Judgments and Recognition Memory

PubMed Central

Tse, Chi-Shing; Kurby, Christopher A.; Du, Feng

2010-01-01

We examined the effect of spatial iconicity (a perceptual simulation of canonical locations of objects) and word-order frequency on language processing and episodic memory of orientation. Participants made speeded relatedness judgments to pairs of words presented in locations typical to their real world arrangements (e.g., ceiling on top and floor on bottom). They then engaged in a surprise orientation recognition task for the word pairs. We replicated Louwerse’s finding (2008) that word-order frequency has a stronger effect on semantic relatedness judgments than spatial iconicity. This is consistent with recent suggestions that linguistic representations have a stronger impact on immediate decisions about verbal materials than perceptual simulations. In contrast, spatial iconicity enhanced episodic memory of orientation to a greater extent than word-order frequency did. This new finding indicates that perceptual simulations have an important role in episodic memory. Results are discussed with respect to theories of perceptual representation and linguistic processing. PMID:19742388

Impact during equine locomotion: techniques for measurement and analysis.

PubMed

Burn, J F; Wilson, A; Nason, G P

1997-05-01

Impact is implicated in the development of several types of musculoskeletal injury in the horse. Characterisation of impact experienced during strenuous exercise is an important first step towards understanding the mechanism for injury. Measurement and analysis of large, short duration impacts is difficult. The measurement system must be able to record transient peaks and high frequencies accurately. The analysis technique must be able to characterise the impact signal in time and frequency. This paper presents a measurement system and analysis technique for the characterisation of large impacts. A piezo-electric accelerometer was securely mounted on the dorsal surface of the horses hoof. Saddle mounted charge amplifiers and a 20 m coaxial cable transferred these data to a PC based logging system. Data were down-loaded onto a UNIX workstation and analysed using a proprietary statistics package. The values of parameters calculated from the time series data were comparable to those of other authors. A wavelet decomposition showed that the frequency profile of the signal changed with time. While most spectral energy was seen at impact, a significant amount of energy was contained in the signal immediately following impact. Over 99% of this energy was contained in frequencies less than 1250 Hz. The sampling rate and the frequency response of a measurement system for recording impact should be chosen carefully to prevent loss or corruption of data. Time scale analysis using a wavelet decomposition is a powerful technique which can be used to characterise impact data. The use of contour plots provides a highly visual representation of the time and frequency localisation of power during impact.

Mutual Information in Frequency and Its Application to Measure Cross-Frequency Coupling in Epilepsy

NASA Astrophysics Data System (ADS)

Malladi, Rakesh; Johnson, Don H.; Kalamangalam, Giridhar P.; Tandon, Nitin; Aazhang, Behnaam

2018-06-01

We define a metric, mutual information in frequency (MI-in-frequency), to detect and quantify the statistical dependence between different frequency components in the data, referred to as cross-frequency coupling and apply it to electrophysiological recordings from the brain to infer cross-frequency coupling. The current metrics used to quantify the cross-frequency coupling in neuroscience cannot detect if two frequency components in non-Gaussian brain recordings are statistically independent or not. Our MI-in-frequency metric, based on Shannon's mutual information between the Cramer's representation of stochastic processes, overcomes this shortcoming and can detect statistical dependence in frequency between non-Gaussian signals. We then describe two data-driven estimators of MI-in-frequency: one based on kernel density estimation and the other based on the nearest neighbor algorithm and validate their performance on simulated data. We then use MI-in-frequency to estimate mutual information between two data streams that are dependent across time, without making any parametric model assumptions. Finally, we use the MI-in- frequency metric to investigate the cross-frequency coupling in seizure onset zone from electrocorticographic recordings during seizures. The inferred cross-frequency coupling characteristics are essential to optimize the spatial and spectral parameters of electrical stimulation based treatments of epilepsy.

Rough parameter dependence in climate models and the role of Ruelle-Pollicott resonances.

PubMed

Chekroun, Mickaël David; Neelin, J David; Kondrashov, Dmitri; McWilliams, James C; Ghil, Michael

2014-02-04

Despite the importance of uncertainties encountered in climate model simulations, the fundamental mechanisms at the origin of sensitive behavior of long-term model statistics remain unclear. Variability of turbulent flows in the atmosphere and oceans exhibits recurrent large-scale patterns. These patterns, while evolving irregularly in time, manifest characteristic frequencies across a large range of time scales, from intraseasonal through interdecadal. Based on modern spectral theory of chaotic and dissipative dynamical systems, the associated low-frequency variability may be formulated in terms of Ruelle-Pollicott (RP) resonances. RP resonances encode information on the nonlinear dynamics of the system, and an approach for estimating them--as filtered through an observable of the system--is proposed. This approach relies on an appropriate Markov representation of the dynamics associated with a given observable. It is shown that, within this representation, the spectral gap--defined as the distance between the subdominant RP resonance and the unit circle--plays a major role in the roughness of parameter dependences. The model statistics are the most sensitive for the smallest spectral gaps; such small gaps turn out to correspond to regimes where the low-frequency variability is more pronounced, whereas autocorrelations decay more slowly. The present approach is applied to analyze the rough parameter dependence encountered in key statistics of an El-Niño-Southern Oscillation model of intermediate complexity. Theoretical arguments, however, strongly suggest that such links between model sensitivity and the decay of correlation properties are not limited to this particular model and could hold much more generally.

Rough parameter dependence in climate models and the role of Ruelle-Pollicott resonances

PubMed Central

Chekroun, Mickaël David; Neelin, J. David; Kondrashov, Dmitri; McWilliams, James C.; Ghil, Michael

2014-01-01

Despite the importance of uncertainties encountered in climate model simulations, the fundamental mechanisms at the origin of sensitive behavior of long-term model statistics remain unclear. Variability of turbulent flows in the atmosphere and oceans exhibits recurrent large-scale patterns. These patterns, while evolving irregularly in time, manifest characteristic frequencies across a large range of time scales, from intraseasonal through interdecadal. Based on modern spectral theory of chaotic and dissipative dynamical systems, the associated low-frequency variability may be formulated in terms of Ruelle-Pollicott (RP) resonances. RP resonances encode information on the nonlinear dynamics of the system, and an approach for estimating them—as filtered through an observable of the system—is proposed. This approach relies on an appropriate Markov representation of the dynamics associated with a given observable. It is shown that, within this representation, the spectral gap—defined as the distance between the subdominant RP resonance and the unit circle—plays a major role in the roughness of parameter dependences. The model statistics are the most sensitive for the smallest spectral gaps; such small gaps turn out to correspond to regimes where the low-frequency variability is more pronounced, whereas autocorrelations decay more slowly. The present approach is applied to analyze the rough parameter dependence encountered in key statistics of an El-Niño–Southern Oscillation model of intermediate complexity. Theoretical arguments, however, strongly suggest that such links between model sensitivity and the decay of correlation properties are not limited to this particular model and could hold much more generally. PMID:24443553

ConceFT for Time-Varying Heart Rate Variability Analysis as a Measure of Noxious Stimulation During General Anesthesia.

PubMed

Lin, Yu-Ting; Wu, Hau-Tieng

2017-01-01

Heart rate variability (HRV) offers a noninvasive way to peek into the physiological status of the human body. When this physiological status is dynamic, traditional HRV indices calculated from power spectrum do not resolve the dynamic situation due to the issue of nonstationarity. Clinical anesthesia is a typically dynamic situation that calls for time-varying HRV analysis. Concentration of frequency and time (ConceFT) is a nonlinear time-frequency (TF) analysis generalizing the multitaper technique and the synchrosqueezing transform. The result is a sharp TF representation capturing the dynamics inside HRV. Companion indices of the commonly applied HRV indices, including time-varying low-frequency power (tvLF), time-varying high-frequency power, and time-varying low-high ratio, are considered as measures of noxious stimulation. To evaluate the feasibility of the proposed indices, we apply these indices to study two different types of noxious stimulation, the endotracheal intubation and surgical skin incision, under general anesthesia. The performance was compared with traditional HRV indices, the heart rate reading, and indices from electroencephalography. The results indicate that the tvLF index performs best and outperforms not only the traditional HRV index, but also the commonly used heart rate reading. With the help of ConceFT, the proposed HRV indices are potential to provide a better quantification of the dynamic change of the autonomic nerve system. Our proposed scheme of time-varying HRV analysis could contribute to the clinical assessment of analgesia under general anesthesia.

Unconventional Signal Processing Using the Cone Kernel Time-Frequency Representation.

DTIC Science & Technology

1992-10-30

Wigner - Ville distribution ( WVD ), the Choi- Williams distribution , and the cone kernel distribution were compared with the spectrograms. Results were...ambiguity function. Figures A-18(c) and (d) are the Wigner - Ville Distribution ( WVD ) and CK-TFR Doppler maps. In this noiseless case all three exhibit...kernel is the basis for the well known Wigner - Ville distribution . In A-9(2), the cone kernel defined by Zhao, Atlas and Marks [21 is described

Sonar Detection and Classification of Underwater UXO and Environmental Parameters

DTIC Science & Technology

2012-07-09

For these targets, representations like those in Figs. 10 and 11 may be more useful because they focus on properties of the isolated target signal ... using time-frequency phenomena extracted from strong ROIs in target scattering data. In general, backscattered signals contain specular as well as...database of sonar target signals useful for developing and evaluating C/ID algorithms that separate UXO from bottom clutter and to look for and

Rapid Transient Pressure Field Computations in the Nearfield of Circular Transducers using Frequency Domain Time-Space Decomposition

PubMed Central

Alles, E. J.; Zhu, Y.; van Dongen, K. W. A.; McGough, R. J.

2013-01-01

The fast nearfield method, when combined with time-space decomposition, is a rapid and accurate approach for calculating transient nearfield pressures generated by ultrasound transducers. However, the standard time-space decomposition approach is only applicable to certain analytical representations of the temporal transducer surface velocity that, when applied to the fast nearfield method, are expressed as a finite sum of products of separate temporal and spatial terms. To extend time-space decomposition such that accelerated transient field simulations are enabled in the nearfield for an arbitrary transducer surface velocity, a new transient simulation method, frequency domain time-space decomposition (FDTSD), is derived. With this method, the temporal transducer surface velocity is transformed into the frequency domain, and then each complex-valued term is processed separately. Further improvements are achieved by spectral clipping, which reduces the number of terms and the computation time. Trade-offs between speed and accuracy are established for FDTSD calculations, and pressure fields obtained with the FDTSD method for a circular transducer are compared to those obtained with Field II and the impulse response method. The FDTSD approach, when combined with the fast nearfield method and spectral clipping, consistently achieves smaller errors in less time and requires less memory than Field II or the impulse response method. PMID:23160476

Laser Welding Process Monitoring Systems: Advanced Signal Analysis for Quality Assurance

NASA Astrophysics Data System (ADS)

D'Angelo, Giuseppe

Laser material processing today is widely used in industry. Especially laser welding became one of the key-technologies, e. g., for the automotive sector. This is due to the improvement and development of new laser sources and the increasing knowledge gained at countless scientific research projects. Nevertheless, it is still not possible to use the full potential of this technology. Therefore, the introduction and application of quality-assuring systems is required. For a long time, the statement "the best sensor is no sensor" was often heard. Today, a change of paradigm can be observed. On the one hand, ISO 9000 and other by law enforced regulations have led to the understanding that quality monitoring is an essential tool in modern manufacturing and necessary in order to keep production results in deterministic boundaries. On the other hand, rising quality requirements not only set higher and higher requirements for the process technology but also demand qualityassurance measures which ensure the reliable recognition of process faults. As a result, there is a need for reliable online detection and correction of welding faults by means of an in-process monitoring. The chapter describes an advanced signals analysis technique to extract information from signals detected, during the laser welding process, by optical sensors. The technique is based on the method of reassignment which was first applied to the spectrogram by Kodera, Gendrin and de Villedary22,23 and later generalized to any bilinear time-frequency representation by Auger and Flandrin.24 Key to the method is a nonlinear convolution where the value of the convolution is not placed at the center of the convolution kernel but rather reassigned to the center of mass of the function within the kernel. The resulting reassigned representation yields significantly improved components localization. We compare the proposed time-frequency distributions by analyzing signals detected during the laser welding of tailored blanks, demonstrating the advantages of the reassigned representation, giving practical applicability to the proposed method.

Evidence in Support of the Independent Channel Model Describing the Sensorimotor Control of Human Stance Using a Humanoid Robot

PubMed Central

Pasma, Jantsje H.; Assländer, Lorenz; van Kordelaar, Joost; de Kam, Digna; Mergner, Thomas; Schouten, Alfred C.

2018-01-01

The Independent Channel (IC) model is a commonly used linear balance control model in the frequency domain to analyze human balance control using system identification and parameter estimation. The IC model is a rudimentary and noise-free description of balance behavior in the frequency domain, where a stable model representation is not guaranteed. In this study, we conducted firstly time-domain simulations with added noise, and secondly robot experiments by implementing the IC model in a real-world robot (PostuRob II) to test the validity and stability of the model in the time domain and for real world situations. Balance behavior of seven healthy participants was measured during upright stance by applying pseudorandom continuous support surface rotations. System identification and parameter estimation were used to describe the balance behavior with the IC model in the frequency domain. The IC model with the estimated parameters from human experiments was implemented in Simulink for computer simulations including noise in the time domain and robot experiments using the humanoid robot PostuRob II. Again, system identification and parameter estimation were used to describe the simulated balance behavior. Time series, Frequency Response Functions, and estimated parameters from human experiments, computer simulations, and robot experiments were compared with each other. The computer simulations showed similar balance behavior and estimated control parameters compared to the human experiments, in the time and frequency domain. Also, the IC model was able to control the humanoid robot by keeping it upright, but showed small differences compared to the human experiments in the time and frequency domain, especially at high frequencies. We conclude that the IC model, a descriptive model in the frequency domain, can imitate human balance behavior also in the time domain, both in computer simulations with added noise and real world situations with a humanoid robot. This provides further evidence that the IC model is a valid description of human balance control. PMID:29615886

Evidence in Support of the Independent Channel Model Describing the Sensorimotor Control of Human Stance Using a Humanoid Robot.

PubMed

Pasma, Jantsje H; Assländer, Lorenz; van Kordelaar, Joost; de Kam, Digna; Mergner, Thomas; Schouten, Alfred C

2018-01-01

The Independent Channel (IC) model is a commonly used linear balance control model in the frequency domain to analyze human balance control using system identification and parameter estimation. The IC model is a rudimentary and noise-free description of balance behavior in the frequency domain, where a stable model representation is not guaranteed. In this study, we conducted firstly time-domain simulations with added noise, and secondly robot experiments by implementing the IC model in a real-world robot (PostuRob II) to test the validity and stability of the model in the time domain and for real world situations. Balance behavior of seven healthy participants was measured during upright stance by applying pseudorandom continuous support surface rotations. System identification and parameter estimation were used to describe the balance behavior with the IC model in the frequency domain. The IC model with the estimated parameters from human experiments was implemented in Simulink for computer simulations including noise in the time domain and robot experiments using the humanoid robot PostuRob II. Again, system identification and parameter estimation were used to describe the simulated balance behavior. Time series, Frequency Response Functions, and estimated parameters from human experiments, computer simulations, and robot experiments were compared with each other. The computer simulations showed similar balance behavior and estimated control parameters compared to the human experiments, in the time and frequency domain. Also, the IC model was able to control the humanoid robot by keeping it upright, but showed small differences compared to the human experiments in the time and frequency domain, especially at high frequencies. We conclude that the IC model, a descriptive model in the frequency domain, can imitate human balance behavior also in the time domain, both in computer simulations with added noise and real world situations with a humanoid robot. This provides further evidence that the IC model is a valid description of human balance control.

Observed Hierarchy of Student Proficiency with Period, Frequency, and Angular Frequency

ERIC Educational Resources Information Center

Young, Nicholas T.; Heckler, Andrew F.

2018-01-01

In the context of a generic harmonic oscillator, we investigated students' accuracy in determining the period, frequency, and angular frequency from mathematical and graphical representations. In a series of studies including interviews, free response tests, and multiple-choice tests developed in an iterative process, we assessed students in both…

Derivational Morphology and Base Morpheme Frequency

ERIC Educational Resources Information Center

Ford, M. A.; Davis, M. H.; Marslen-Wilson, W. D.

2010-01-01

Morpheme frequency effects for derived words (e.g. an influence of the frequency of the base "dark" on responses to "darkness") have been interpreted as evidence of morphemic representation. However, it has been suggested that most derived words would not show these effects if family size (a type frequency count claimed to reflect semantic…

Color-motion feature-binding errors are mediated by a higher-order chromatic representation.

PubMed

Shevell, Steven K; Wang, Wei

2016-03-01

Peripheral and central moving objects of the same color may be perceived to move in the same direction even though peripheral objects have a different true direction of motion [Nature429, 262 (2004)10.1038/429262a]. The perceived, illusory direction of peripheral motion is a color-motion feature-binding error. Recent work shows that such binding errors occur even without an exact color match between central and peripheral objects, and, moreover, the frequency of the binding errors in the periphery declines as the chromatic difference increases between the central and peripheral objects [J. Opt. Soc. Am. A31, A60 (2014)JOAOD60740-323210.1364/JOSAA.31.000A60]. This change in the frequency of binding errors with the chromatic difference raises the general question of the chromatic representation from which the difference is determined. Here, basic properties of the chromatic representation are tested to discover whether it depends on independent chromatic differences on the l and the s cardinal axes or, alternatively, on a more specific higher-order chromatic representation. Experimental tests compared the rate of feature-binding errors when the central and peripheral colors had the identical s chromaticity (so zero difference in s) and a fixed magnitude of l difference, while varying the identical s level in center and periphery (thus always keeping the s difference at zero). A chromatic representation based on independent l and s differences would result in the same frequency of color-motion binding errors at everyslevel. The results are contrary to this prediction, thus showing that the chromatic representation at the level of color-motion feature binding depends on a higher-order chromatic mechanism.

Vessel classification in overhead satellite imagery using weighted "bag of visual words"

NASA Astrophysics Data System (ADS)

Parameswaran, Shibin; Rainey, Katie

2015-05-01

Vessel type classification in maritime imagery is a challenging problem and has applications to many military and surveillance applications. The ability to classify a vessel correctly varies significantly depending on its appearance which in turn is affected by external factors such as lighting or weather conditions, viewing geometry and sea state. The difficulty in classifying vessels also varies among different ship types as some types of vessels show more within-class variation than others. In our previous work, we showed that the bag of visual words" (V-BoW) was an effective feature representation for this classification task in the maritime domain. The V-BoW feature representation is analogous to the bag of words" (BoW) representation used in information retrieval (IR) application in text or natural language processing (NLP) domain. It has been shown in the textual IR applications that the performance of the BoW feature representation can be improved significantly by applying appropriate term-weighting such as log term frequency, inverse document frequency etc. Given the close correspondence between textual BoW (T-BoW) and V-BoW feature representations, we propose to apply several well-known term weighting schemes from the text IR domain on V-BoW feature representation to increase its ability to discriminate between ship types.

EEG biometric identification: a thorough exploration of the time-frequency domain

NASA Astrophysics Data System (ADS)

DelPozo-Banos, Marcos; Travieso, Carlos M.; Weidemann, Christoph T.; Alonso, Jesús B.

2015-10-01

Objective. Although interest in using electroencephalogram (EEG) activity for subject identification has grown in recent years, the state of the art still lacks a comprehensive exploration of the discriminant information within it. This work aims to fill this gap, and in particular, it focuses on the time-frequency representation of the EEG. Approach. We executed qualitative and quantitative analyses of six publicly available data sets following a sequential experimentation approach. This approach was divided in three blocks analysing the configuration of the power spectrum density, the representation of the data and the properties of the discriminant information. A total of ten experiments were applied. Main results. Results show that EEG information below 40 Hz is unique enough to discriminate across subjects (a maximum of 100 subjects were evaluated here), regardless of the recorded cognitive task or the sensor location. Moreover, the discriminative power of rhythms follows a W-like shape between 1 and 40 Hz, with the central peak located at the posterior rhythm (around 10 Hz). This information is maximized with segments of around 2 s, and it proved to be moderately constant across montages and time. Significance. Therefore, we characterize how EEG activity differs across individuals and detail the optimal conditions to detect subject-specific information. This work helps to clarify the results of previous studies and to solve some unanswered questions. Ultimately, it will serve as guide for the design of future biometric systems.

The many places of frequency: evidence for a novel locus of the lexical frequency effect in word production.

PubMed

Knobel, Mark; Finkbeiner, Matthew; Caramazza, Alfonso

2008-03-01

The effect of lexical frequency on language-processing tasks is exceptionally reliable. For example, pictures with higher frequency names are named faster and more accurately than those with lower frequency names. Experiments with normal participants and patients strongly suggest that this production effect arises at the level of lexical access. Further work has suggested that within lexical access this effect arises at the level of lexical representations. Here we present patient E.C. who shows an effect of lexical frequency on his nonword error rate. The best explanation of his performance is that there is an additional locus of frequency at the interface of lexical and segmental representational levels. We confirm this hypothesis by showing that only computational models with frequency at this new locus can produce a similar error pattern to that of patient E.C. Finally, in an analysis of a large group of Italian patients, we show that there exist patients who replicate E.C.'s pattern of results and others who show the complementary pattern of frequency effects on semantic error rates. Our results combined with previous findings suggest that frequency plays a role throughout the process of lexical access.

Methodology for fault detection in induction motors via sound and vibration signals

NASA Astrophysics Data System (ADS)

Delgado-Arredondo, Paulo Antonio; Morinigo-Sotelo, Daniel; Osornio-Rios, Roque Alfredo; Avina-Cervantes, Juan Gabriel; Rostro-Gonzalez, Horacio; Romero-Troncoso, Rene de Jesus

2017-01-01

Nowadays, timely maintenance of electric motors is vital to keep up the complex processes of industrial production. There are currently a variety of methodologies for fault diagnosis. Usually, the diagnosis is performed by analyzing current signals at a steady-state motor operation or during a start-up transient. This method is known as motor current signature analysis, which identifies frequencies associated with faults in the frequency domain or by the time-frequency decomposition of the current signals. Fault identification may also be possible by analyzing acoustic sound and vibration signals, which is useful because sometimes this information is the only available. The contribution of this work is a methodology for detecting faults in induction motors in steady-state operation based on the analysis of acoustic sound and vibration signals. This proposed approach uses the Complete Ensemble Empirical Mode Decomposition for decomposing the signal into several intrinsic mode functions. Subsequently, the frequency marginal of the Gabor representation is calculated to obtain the spectral content of the IMF in the frequency domain. This proposal provides good fault detectability results compared to other published works in addition to the identification of more frequencies associated with the faults. The faults diagnosed in this work are two broken rotor bars, mechanical unbalance and bearing defects.

Sparse Representation Based Frequency Detection and Uncertainty Reduction in Blade Tip Timing Measurement for Multi-Mode Blade Vibration Monitoring

PubMed Central

Pan, Minghao; Yang, Yongmin; Guan, Fengjiao; Hu, Haifeng; Xu, Hailong

2017-01-01

The accurate monitoring of blade vibration under operating conditions is essential in turbo-machinery testing. Blade tip timing (BTT) is a promising non-contact technique for the measurement of blade vibrations. However, the BTT sampling data are inherently under-sampled and contaminated with several measurement uncertainties. How to recover frequency spectra of blade vibrations though processing these under-sampled biased signals is a bottleneck problem. A novel method of BTT signal processing for alleviating measurement uncertainties in recovery of multi-mode blade vibration frequency spectrum is proposed in this paper. The method can be divided into four phases. First, a single measurement vector model is built by exploiting that the blade vibration signals are sparse in frequency spectra. Secondly, the uniqueness of the nonnegative sparse solution is studied to achieve the vibration frequency spectrum. Thirdly, typical sources of BTT measurement uncertainties are quantitatively analyzed. Finally, an improved vibration frequency spectra recovery method is proposed to get a guaranteed level of sparse solution when measurement results are biased. Simulations and experiments are performed to prove the feasibility of the proposed method. The most outstanding advantage is that this method can prevent the recovered multi-mode vibration spectra from being affected by BTT measurement uncertainties without increasing the probe number. PMID:28758952

Joint Acoustic and Modulation Frequency

NASA Astrophysics Data System (ADS)

Atlas, Les; Shamma, Shihab A.

2003-12-01

There is a considerable evidence that our perception of sound uses important features which is related to underlying signal modulations. This topic has been studied extensively via perceptual experiments, yet there are few, if any, well-developed signal processing methods which capitalize on or model these effects. We begin by summarizing evidence of the importance of modulation representations from psychophysical, physiological, and other sources. The concept of a two-dimensional joint acoustic and modulation frequency representation is proposed. A simple single sinusoidal amplitude modulator of a sinusoidal carrier is then used to illustrate properties of an unconstrained and ideal joint representation. Added constraints are required to remove or reduce undesired interference terms and to provide invertibility. It is then noted that the constraints would also apply to more general and complex cases of broader modulation and carriers. Applications in single-channel speaker separation and in audio coding are used to illustrate the applicability of this joint representation. Other applications in signal analysis and filtering are suggested.

Chirplet Wigner-Ville distribution for time-frequency representation and its application

NASA Astrophysics Data System (ADS)

Chen, G.; Chen, J.; Dong, G. M.

2013-12-01

This paper presents a Chirplet Wigner-Ville Distribution (CWVD) that is free for cross-term that usually occurs in Wigner-Ville distribution (WVD). By transforming the signal with frequency rotating operators, several mono-frequency signals without intermittent are obtained, WVD is applied to the rotated signals that is cross-term free, then some frequency shift operators corresponding to the rotating operator are utilized to relocate the signal‧s instantaneous frequencies (IFs). The operators‧ parameters come from the estimation of the IFs which are approached with a polynomial functions or spline functions. What is more, by analysis of error, the main factors for the performance of the novel method have been discovered and an effective signal extending method based on the IFs estimation has been developed to improve the energy concentration of WVD. The excellent performance of the novel method was manifested by applying it to estimate the IFs of some numerical signals and the echolocation signal emitted by the Large Brown Bat.

Automated In Vivo Platform for the Discovery of Functional Food Treatments of Hypercholesterolemia

PubMed Central

Littleton, Robert M.; Haworth, Kevin J.; Tang, Hong; Setchell, Kenneth D. R.; Nelson, Sandra; Hove, Jay R.

2013-01-01

The zebrafish is becoming an increasingly popular model system for both automated drug discovery and investigating hypercholesterolemia. Here we combine these aspects and for the first time develop an automated high-content confocal assay for treatments of hypercholesterolemia. We also create two algorithms for automated analysis of cardiodynamic data acquired by high-speed confocal microscopy. The first algorithm computes cardiac parameters solely from the frequency-domain representation of cardiodynamic data while the second uses both frequency- and time-domain data. The combined approach resulted in smaller differences relative to manual measurements. The methods are implemented to test the ability of a methanolic extract of the hawthorn plant (Crataegus laevigata) to treat hypercholesterolemia and its peripheral cardiovascular effects. Results demonstrate the utility of these methods and suggest the extract has both antihypercholesterolemic and postitively inotropic properties. PMID:23349685

Automated in vivo platform for the discovery of functional food treatments of hypercholesterolemia.

PubMed

Littleton, Robert M; Haworth, Kevin J; Tang, Hong; Setchell, Kenneth D R; Nelson, Sandra; Hove, Jay R

2013-01-01

The zebrafish is becoming an increasingly popular model system for both automated drug discovery and investigating hypercholesterolemia. Here we combine these aspects and for the first time develop an automated high-content confocal assay for treatments of hypercholesterolemia. We also create two algorithms for automated analysis of cardiodynamic data acquired by high-speed confocal microscopy. The first algorithm computes cardiac parameters solely from the frequency-domain representation of cardiodynamic data while the second uses both frequency- and time-domain data. The combined approach resulted in smaller differences relative to manual measurements. The methods are implemented to test the ability of a methanolic extract of the hawthorn plant (Crataegus laevigata) to treat hypercholesterolemia and its peripheral cardiovascular effects. Results demonstrate the utility of these methods and suggest the extract has both antihypercholesterolemic and postitively inotropic properties.

Transfer function verification and block diagram simplification of a very high-order distributed pole closed-loop servo by means of non-linear time-response simulation

NASA Technical Reports Server (NTRS)

Mukhopadhyay, A. K.

1975-01-01

Linear frequency domain methods are inadequate in analyzing the 1975 Viking Orbiter (VO75) digital tape recorder servo due to dominant nonlinear effects such as servo signal limiting, unidirectional servo control, and static/dynamic Coulomb friction. The frequency loop (speed control) servo of the VO75 tape recorder is used to illustrate the analytical tools and methodology of system redundancy elimination and high order transfer function verification. The paper compares time-domain performance parameters derived from a series of nonlinear time responses with the available experimental data in order to select the best possible analytical transfer function representation of the tape transport (mechanical segment of the tape recorder) from several possible candidates. The study also shows how an analytical time-response simulation taking into account most system nonlinearities can pinpoint system redundancy and overdesign stemming from a strictly empirical design approach. System order reduction is achieved through truncation of individual transfer functions and elimination of redundant blocks.

Stimulus-specific suppression preserves information in auditory short-term memory.

PubMed

Linke, Annika C; Vicente-Grabovetsky, Alejandro; Cusack, Rhodri

2011-08-02

Philosophers and scientists have puzzled for millennia over how perceptual information is stored in short-term memory. Some have suggested that early sensory representations are involved, but their precise role has remained unclear. The current study asks whether auditory cortex shows sustained frequency-specific activation while sounds are maintained in short-term memory using high-resolution functional MRI (fMRI). Investigating short-term memory representations within regions of human auditory cortex with fMRI has been difficult because of their small size and high anatomical variability between subjects. However, we overcame these constraints by using multivoxel pattern analysis. It clearly revealed frequency-specific activity during the encoding phase of a change detection task, and the degree of this frequency-specific activation was positively related to performance in the task. Although the sounds had to be maintained in memory, activity in auditory cortex was significantly suppressed. Strikingly, patterns of activity in this maintenance period correlated negatively with the patterns evoked by the same frequencies during encoding. Furthermore, individuals who used a rehearsal strategy to remember the sounds showed reduced frequency-specific suppression during the maintenance period. Although negative activations are often disregarded in fMRI research, our findings imply that decreases in blood oxygenation level-dependent response carry important stimulus-specific information and can be related to cognitive processes. We hypothesize that, during auditory change detection, frequency-specific suppression protects short-term memory representations from being overwritten by inhibiting the encoding of interfering sounds.

Functional mixed effects spectral analysis

PubMed Central

KRAFTY, ROBERT T.; HALL, MARTICA; GUO, WENSHENG

2011-01-01

SUMMARY In many experiments, time series data can be collected from multiple units and multiple time series segments can be collected from the same unit. This article introduces a mixed effects Cramér spectral representation which can be used to model the effects of design covariates on the second-order power spectrum while accounting for potential correlations among the time series segments collected from the same unit. The transfer function is composed of a deterministic component to account for the population-average effects and a random component to account for the unit-specific deviations. The resulting log-spectrum has a functional mixed effects representation where both the fixed effects and random effects are functions in the frequency domain. It is shown that, when the replicate-specific spectra are smooth, the log-periodograms converge to a functional mixed effects model. A data-driven iterative estimation procedure is offered for the periodic smoothing spline estimation of the fixed effects, penalized estimation of the functional covariance of the random effects, and unit-specific random effects prediction via the best linear unbiased predictor. PMID:26855437

On the Prony series representation of stretched exponential relaxation

NASA Astrophysics Data System (ADS)

Mauro, John C.; Mauro, Yihong Z.

2018-09-01

Stretched exponential relaxation is a ubiquitous feature of homogeneous glasses. The stretched exponential decay function can be derived from the diffusion-trap model, which predicts certain critical values of the fractional stretching exponent, β. In practical implementations of glass relaxation models, it is computationally convenient to represent the stretched exponential function as a Prony series of simple exponentials. Here, we perform a comprehensive mathematical analysis of the Prony series approximation of the stretched exponential relaxation, including optimized coefficients for certain critical values of β. The fitting quality of the Prony series is analyzed as a function of the number of terms in the series. With a sufficient number of terms, the Prony series can accurately capture the time evolution of the stretched exponential function, including its "fat tail" at long times. However, it is unable to capture the divergence of the first-derivative of the stretched exponential function in the limit of zero time. We also present a frequency-domain analysis of the Prony series representation of the stretched exponential function and discuss its physical implications for the modeling of glass relaxation behavior.

Control of Initialized Fractional-Order Systems. Revised

NASA Technical Reports Server (NTRS)

Hartley, Tom T.; Lorenzo, Carl F.

2002-01-01

Due to the importance of historical effects in fractional-order systems, this paper presents a general fractional-order control theory that includes the time-varying initialization response. Previous studies have not properly accounted for these historical effects. The initialization response, along with the forced response, for fractional-order systems is determined. Stability properties of fractional-order systems are presented in the complex w-plane, which is a transformation of the s-plane. Time responses are discussed with respect to pole positions in the complex w-plane and frequency response behavior is included. A fractional-order vector space representation, which is a generalization of the state space concept, is presented including the initialization response. Control methods for vector representations of initialized fractional-order systems are shown. Nyquist, root-locus, and other input-output control methods are adapted to the control of fractional-order systems. Finally, the fractional-order differintegral is generalized to continuous order-distributions that have the possibility of including a continuum of fractional orders in a system element.

Control of Initialized Fractional-Order Systems

NASA Technical Reports Server (NTRS)

Hartly, Tom T.; Lorenzo, Carl F.

2002-01-01

Due to the importance of historical effects in fractional-order systems, this paper presents a general fractional-order control theory that includes the time-varying initialization response. Previous studies have not properly accounted for these historical effects. The initialization response, along with the forced response, for fractional-order systems is determined. Stability properties of fractional-order systems are presented in the complex Airplane, which is a transformation of the s-plane. Time responses are discussed with respect to pole positions in the complex Airplane and frequency response behavior is included. A fractional-order vector space representation, which is a generalization of the state space concept, is presented including the initialization response. Control methods for vector representations of initialized fractional-order systems are shown. Nyquist, root-locus, and other input-output control methods are adapted to the control of fractional-order systems. Finally, the fractional-order differintegral is generalized to continuous order-distributions that have the possibility of including a continuum of fractional orders in a system element.

Nonlinear Computerized Methodology. A. Angle of Arrival Estimation. B. Data Modeling and Identification

DTIC Science & Technology

1991-06-10

essentially In the Wianer- Ville distribution ( WVD ). A preliminary analysis indicates that the simple operation of autoconvolution can enhance spectral...many troublesome cases as a supplement to MUSIC (and its adaptations) and as a simple alternative (or representation of) the Wigner - Ville ... WVD is a time-frequency distribution which provides an unbiased spectrum estimate by W(t,W) = f H,(u) X (t - u/2) X (t + u/2) e -iwu du , where the

AIC identifies optimal representation of longitudinal dietary variables.

PubMed

VanBuren, John; Cavanaugh, Joseph; Marshall, Teresa; Warren, John; Levy, Steven M

2017-09-01

The Akaike Information Criterion (AIC) is a well-known tool for variable selection in multivariable modeling as well as a tool to help identify the optimal representation of explanatory variables. However, it has been discussed infrequently in the dental literature. The purpose of this paper is to demonstrate the use of AIC in determining the optimal representation of dietary variables in a longitudinal dental study. The Iowa Fluoride Study enrolled children at birth and dental examinations were conducted at ages 5, 9, 13, and 17. Decayed or filled surfaces (DFS) trend clusters were created based on age 13 DFS counts and age 13-17 DFS increments. Dietary intake data (water, milk, 100 percent-juice, and sugar sweetened beverages) were collected semiannually using a food frequency questionnaire. Multinomial logistic regression models were fit to predict DFS cluster membership (n=344). Multiple approaches could be used to represent the dietary data including averaging across all collected surveys or over different shorter time periods to capture age-specific trends or using the individual time points of dietary data. AIC helped identify the optimal representation. Averaging data for all four dietary variables for the whole period from age 9.0 to 17.0 provided a better representation in the multivariable full model (AIC=745.0) compared to other methods assessed in full models (AICs=750.6 for age 9 and 9-13 increment dietary measurements and AIC=762.3 for age 9, 13, and 17 individual measurements). The results illustrate that AIC can help researchers identify the optimal way to summarize information for inclusion in a statistical model. The method presented here can be used by researchers performing statistical modeling in dental research. This method provides an alternative approach for assessing the propriety of variable representation to significance-based procedures, which could potentially lead to improved research in the dental community. © 2017 American Association of Public Health Dentistry.

Frequency-response identification of XV-15 tilt-rotor aircraft dynamics

NASA Technical Reports Server (NTRS)

Tischler, Mark B.

1987-01-01

The timely design and development of the next generation of tilt-rotor aircraft (JVX) depend heavily on the in-depth understanding of existing XV-15 dynamics and the availability of fully validated simulation models. Previous studies have considered aircraft and simulation trim characteristics, but analyses of basic flight vehicle dynamics were limited to qualitative pilot evaluation. The present study has the following objectives: documentation and evaluation of XV-15 bare-airframe dynamics; comparison of aircraft and simulation responses; and development of a validated transfer-function description of the XV-15 needed for future studies. A nonparametric frequency-response approach is used which does not depend on assumed model order or structure. Transfer-function representations are subsequently derived which fit the frequency responses in the bandwidth of greatest concern for piloted handling-qualities and control-system applications.

The CIPM list of recommended frequency standard values: guidelines and procedures

NASA Astrophysics Data System (ADS)

Riehle, Fritz; Gill, Patrick; Arias, Felicitas; Robertsson, Lennart

2018-04-01

A list of standard reference frequency values (LoF) of quantum transitions from the microwave to the optical regime has been recommended by the International Committee for Weights and Measures (Comité international des poids et mesures, CIPM) for use in basic research, technology, and for the metrology of time, frequency and length. The CIPM LoF contains entries that are recommended as secondary representations of the second in the International System of Units, and entries that can be used to serve as realizations of the definition of the metre. The historical perspective that led to the CIPM LoF is outlined. Procedures have been developed for updating existing, and validating new, entries into the CIPM LoF. The CIPM LoF might serve as an entry for a future redefinition of the second by an optical transition.

Embedding Term Similarity and Inverse Document Frequency into a Logical Model of Information Retrieval.

ERIC Educational Resources Information Center

Losada, David E.; Barreiro, Alvaro

2003-01-01

Proposes an approach to incorporate term similarity and inverse document frequency into a logical model of information retrieval. Highlights include document representation and matching; incorporating term similarity into the measure of distance; new algorithms for implementation; inverse document frequency; and logical versus classical models of…

Two-Dimensional Ffowcs Williams/Hawkings Equation Solver

NASA Technical Reports Server (NTRS)

Lockard, David P.

2005-01-01

FWH2D is a Fortran 90 computer program that solves a two-dimensional (2D) version of the equation, derived by J. E. Ffowcs Williams and D. L. Hawkings, for sound generated by turbulent flow. FWH2D was developed especially for estimating noise generated by airflows around such approximately 2D airframe components as slats. The user provides input data on fluctuations of pressure, density, and velocity on some surface. These data are combined with information about the geometry of the surface to calculate histories of thickness and loading terms. These histories are fast-Fourier-transformed into the frequency domain. For each frequency of interest and each observer position specified by the user, kernel functions are integrated over the surface by use of the trapezoidal rule to calculate a pressure signal. The resulting frequency-domain signals are inverse-fast-Fourier-transformed back into the time domain. The output of the code consists of the time- and frequency-domain representations of the pressure signals at the observer positions. Because of its approximate nature, FWH2D overpredicts the noise from a finite-length (3D) component. The advantage of FWH2D is that it requires a fraction of the computation time of a 3D Ffowcs Williams/Hawkings solver.

Gender Representation in EFL Textbooks in Saudi Arabia: A Fair Deal?

ERIC Educational Resources Information Center

Sulaimani, Amjjad

2017-01-01

This study explores gender representation in an international English as a Foreign Language (EFL) textbook that has been specifically adapted for the Saudi Arabian context. It aims to investigate gender frequencies in conversations in three dimensions: gender relations, subject positions, and contents. The quantitative data were analysed using…

Modulation of human time processing by subthalamic deep brain stimulation.

PubMed

Wojtecki, Lars; Elben, Saskia; Timmermann, Lars; Reck, Christiane; Maarouf, Mohammad; Jörgens, Silke; Ploner, Markus; Südmeyer, Martin; Groiss, Stefan Jun; Sturm, Volker; Niedeggen, Michael; Schnitzler, Alfons

2011-01-01

Timing in the range of seconds referred to as interval timing is crucial for cognitive operations and conscious time processing. According to recent models of interval timing basal ganglia (BG) oscillatory loops are involved in time interval recognition. Parkinsońs disease (PD) is a typical disease of the basal ganglia that shows distortions in interval timing. Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is a powerful treatment of PD which modulates motor and cognitive functions depending on stimulation frequency by affecting subcortical-cortical oscillatory loops. Thus, for the understanding of BG-involvement in interval timing it is of interest whether STN-DBS can modulate timing in a frequency dependent manner by interference with oscillatory time recognition processes. We examined production and reproduction of 5 and 15 second intervals and millisecond timing in a double blind, randomised, within-subject repeated-measures design of 12 PD-patients applying no, 10-Hz- and ≥ 130-Hz-STN-DBS compared to healthy controls. We found under(re-)production of the 15-second interval and a significant enhancement of this under(re-)production by 10-Hz-stimulation compared to no stimulation, ≥ 130-Hz-STN-DBS and controls. Milliseconds timing was not affected. We provide first evidence for a frequency-specific modulatory effect of STN-DBS on interval timing. Our results corroborate the involvement of BG in general and of the STN in particular in the cognitive representation of time intervals in the range of multiple seconds.

Modulation of Human Time Processing by Subthalamic Deep Brain Stimulation

PubMed Central

Timmermann, Lars; Reck, Christiane; Maarouf, Mohammad; Jörgens, Silke; Ploner, Markus; Südmeyer, Martin; Groiss, Stefan Jun; Sturm, Volker; Niedeggen, Michael; Schnitzler, Alfons

2011-01-01

Timing in the range of seconds referred to as interval timing is crucial for cognitive operations and conscious time processing. According to recent models of interval timing basal ganglia (BG) oscillatory loops are involved in time interval recognition. Parkinsońs disease (PD) is a typical disease of the basal ganglia that shows distortions in interval timing. Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is a powerful treatment of PD which modulates motor and cognitive functions depending on stimulation frequency by affecting subcortical-cortical oscillatory loops. Thus, for the understanding of BG-involvement in interval timing it is of interest whether STN-DBS can modulate timing in a frequency dependent manner by interference with oscillatory time recognition processes. We examined production and reproduction of 5 and 15 second intervals and millisecond timing in a double blind, randomised, within-subject repeated-measures design of 12 PD-patients applying no, 10-Hz- and ≥130-Hz-STN-DBS compared to healthy controls. We found under(re-)production of the 15-second interval and a significant enhancement of this under(re-)production by 10-Hz-stimulation compared to no stimulation, ≥130-Hz-STN-DBS and controls. Milliseconds timing was not affected. We provide first evidence for a frequency-specific modulatory effect of STN-DBS on interval timing. Our results corroborate the involvement of BG in general and of the STN in particular in the cognitive representation of time intervals in the range of multiple seconds. PMID:21931767

Separation of musical instruments based on amplitude and frequency comodulation

NASA Astrophysics Data System (ADS)

Jacobson, Barry D.; Cauwenberghs, Gert; Quatieri, Thomas F.

2002-05-01

In previous work, amplitude comodulation was investigated as a basis for monaural source separation. Amplitude comodulation refers to similarities in amplitude envelopes of individual spectral components emitted by particular types of sources. In many types of musical instruments, amplitudes of all resonant modes rise/fall, and start/stop together during the course of normal playing. We found that under certain well-defined conditions, a mixture of constant frequency, amplitude comodulated sources can unambiguously be decomposed into its constituents on the basis of these similarities. In this work, system performance was improved by relaxing the constant frequency requirement. String instruments, for example, which are normally played with vibrato, are both amplitude and frequency comodulated sources, and could not be properly tracked under the constant frequency assumption upon which our original algorithm was based. Frequency comodulation refers to similarities in frequency variations of individual harmonics emitted by these types of sources. The analytical difficulty is in defining a representation of the source which properly tracks frequency varying components. A simple, fixed filter bank can only track an individual spectral component for the duration in which it is within the passband of one of the filters. Alternatives are therefore explored which are amenable to real-time implementation.

Wavelet-based localization of oscillatory sources from magnetoencephalography data.

PubMed

Lina, J M; Chowdhury, R; Lemay, E; Kobayashi, E; Grova, C

2014-08-01

Transient brain oscillatory activities recorded with Eelectroencephalography (EEG) or magnetoencephalography (MEG) are characteristic features in physiological and pathological processes. This study is aimed at describing, evaluating, and illustrating with clinical data a new method for localizing the sources of oscillatory cortical activity recorded by MEG. The method combines time-frequency representation and an entropic regularization technique in a common framework, assuming that brain activity is sparse in time and space. Spatial sparsity relies on the assumption that brain activity is organized among cortical parcels. Sparsity in time is achieved by transposing the inverse problem in the wavelet representation, for both data and sources. We propose an estimator of the wavelet coefficients of the sources based on the maximum entropy on the mean (MEM) principle. The full dynamics of the sources is obtained from the inverse wavelet transform, and principal component analysis of the reconstructed time courses is applied to extract oscillatory components. This methodology is evaluated using realistic simulations of single-trial signals, combining fast and sudden discharges (spike) along with bursts of oscillating activity. The method is finally illustrated with a clinical application using MEG data acquired on a patient with a right orbitofrontal epilepsy.

Extended output phasor representation of multi-spectral fluorescence lifetime imaging microscopy

PubMed Central

Campos-Delgado, Daniel U.; Navarro, O. Gutiérrez; Arce-Santana, E. R.; Jo, Javier A.

2015-01-01

In this paper, we investigate novel low-dimensional and model-free representations for multi-spectral fluorescence lifetime imaging microscopy (m-FLIM) data. We depart from the classical definition of the phasor in the complex plane to propose the extended output phasor (EOP) and extended phasor (EP) for multi-spectral information. The frequency domain properties of the EOP and EP are analytically studied based on a multiexponential model for the impulse response of the imaged tissue. For practical implementations, the EOP is more appealing since there is no need to perform deconvolution of the instrument response from the measured m-FLIM data, as in the case of EP. Our synthetic and experimental evaluations with m-FLIM datasets of human coronary atherosclerotic plaques show that low frequency indexes have to be employed for a distinctive representation of the EOP and EP, and to reduce noise distortion. The tissue classification of the m-FLIM datasets by EOP and EP also improves with low frequency indexes, and does not present significant differences by using either phasor. PMID:26114031

Encoding of a spectrally-complex communication sound in the bullfrog's auditory nerve.

PubMed

Schwartz, J J; Simmons, A M

1990-02-01

1. A population study of eighth nerve responses in the bullfrog, Rana catesbeiana, was undertaken to analyze how the eighth nerve codes the complex spectral and temporal structure of the species-specific advertisement call over a biologically-realistic range of intensities. Synthetic advertisement calls were generated by Fourier synthesis and presented to individual eighth nerve fibers of anesthetized bullfrogs. Fiber responses were analyzed by calculating rate responses based on post-stimulus-time (PST) histograms and temporal responses based on Fourier transforms of period histograms. 2. At stimulus intensities of 70 and 80 dB SPL, normalized rate responses provide a fairly good representation of the complex spectral structure of the stimulus, particularly in the low- and mid-frequency range. At higher intensities, rate responses saturate, and very little of the spectral structure of the complex stimulus can be seen in the profile of rate responses of the population. 3. Both AP and BP fibers phase-lock strongly to the fundamental (100 Hz) of the complex stimulus. These effects are relatively resistant to changes in stimulus intensity. Only a small number of fibers synchronize to the low-frequency spectral energy in the stimulus. The underlying spectral complexity of the stimulus is not accurately reflected in the timing of fiber firing, presumably because firing is 'captured' by the fundamental frequency. 4. Plots of average localized synchronized rate (ALSR), which combine both spectral and temporal information, show a similar, low-pass shape at all stimulus intensities. ALSR plots do not generally provide an accurate representation of the structure of the advertisement call. 5. The data suggest that anuran peripheral auditory fibers may be particularly sensitive to the amplitude envelope of sounds.

Modeling Pharmacological Clock and Memory Patterns of Interval Timing in a Striatal Beat-Frequency Model with Realistic, Noisy Neurons

PubMed Central

Oprisan, Sorinel A.; Buhusi, Catalin V.

2011-01-01

In most species, the capability of perceiving and using the passage of time in the seconds-to-minutes range (interval timing) is not only accurate but also scalar: errors in time estimation are linearly related to the estimated duration. The ubiquity of scalar timing extends over behavioral, lesion, and pharmacological manipulations. For example, in mammals, dopaminergic drugs induce an immediate, scalar change in the perceived time (clock pattern), whereas cholinergic drugs induce a gradual, scalar change in perceived time (memory pattern). How do these properties emerge from unreliable, noisy neurons firing in the milliseconds range? Neurobiological information relative to the brain circuits involved in interval timing provide support for an striatal beat frequency (SBF) model, in which time is coded by the coincidental activation of striatal spiny neurons by cortical neural oscillators. While biologically plausible, the impracticality of perfect oscillators, or their lack thereof, questions this mechanism in a brain with noisy neurons. We explored the computational mechanisms required for the clock and memory patterns in an SBF model with biophysically realistic and noisy Morris–Lecar neurons (SBF–ML). Under the assumption that dopaminergic drugs modulate the firing frequency of cortical oscillators, and that cholinergic drugs modulate the memory representation of the criterion time, we show that our SBF–ML model can reproduce the pharmacological clock and memory patterns observed in the literature. Numerical results also indicate that parameter variability (noise) – which is ubiquitous in the form of small fluctuations in the intrinsic frequencies of neural oscillators within and between trials, and in the errors in recording/retrieving stored information related to criterion time – seems to be critical for the time-scale invariance of the clock and memory patterns. PMID:21977014

Learning high-level features for chord recognition using Autoencoder

NASA Astrophysics Data System (ADS)

Phongthongloa, Vilailukkana; Kamonsantiroj, Suwatchai; Pipanmaekaporn, Luepol

2016-07-01

Chord transcription is valuable to do by itself. It is known that the manual transcription of chords is very tiresome, time-consuming. It requires, moreover, musical knowledge. Automatic chord recognition has recently attracted a number of researches in the Music Information Retrieval field. It has known that a pitch class profile (PCP) is the commonly signal representation of musical harmonic analysis. However, the PCP may contain additional non-harmonic noise such as harmonic overtones and transient noise. The problem of non-harmonic might be generating the sound energy in term of frequency more than the actual notes of the respective chord. Autoencoder neural network may be trained to learn a mapping from low level feature to one or more higher-level representation. These high-level representations can explain dependencies of the inputs and reduce the effect of non-harmonic noise. Then these improve features are fed into neural network classifier. The proposed high-level musical features show 80.90% of accuracy. The experimental results have shown that the proposed approach can achieve better performance in comparison with other based method.

An evaluation of space time cube representation of spatiotemporal patterns.

PubMed

Kristensson, Per Ola; Dahlbäck, Nils; Anundi, Daniel; Björnstad, Marius; Gillberg, Hanna; Haraldsson, Jonas; Mårtensson, Ingrid; Nordvall, Mathias; Ståhl, Josefine

2009-01-01

Space time cube representation is an information visualization technique where spatiotemporal data points are mapped into a cube. Information visualization researchers have previously argued that space time cube representation is beneficial in revealing complex spatiotemporal patterns in a data set to users. The argument is based on the fact that both time and spatial information are displayed simultaneously to users, an effect difficult to achieve in other representations. However, to our knowledge the actual usefulness of space time cube representation in conveying complex spatiotemporal patterns to users has not been empirically validated. To fill this gap, we report on a between-subjects experiment comparing novice users' error rates and response times when answering a set of questions using either space time cube or a baseline 2D representation. For some simple questions, the error rates were lower when using the baseline representation. For complex questions where the participants needed an overall understanding of the spatiotemporal structure of the data set, the space time cube representation resulted in on average twice as fast response times with no difference in error rates compared to the baseline. These results provide an empirical foundation for the hypothesis that space time cube representation benefits users analyzing complex spatiotemporal patterns.

Consuming Ecstasy: Representations of Male and Female Orgasm in Mainstream Pornography.

PubMed

Séguin, Léa J; Rodrigue, Carl; Lavigne, Julie

2018-01-01

Social representations, which appear in a variety of media, can influence the way sexual experiences are perceived and understood. While pornography is not the only medium in which orgasm is portrayed, it is the most explicit, and it is widespread and easily accessible. As such, pornography is an ideal medium for examining representations of male and female orgasm. PornHub's 50 most viewed videos of all time were viewed and coded for the frequency of male and female orgasm, orgasm-inducing sex acts (and whether activity inducing female orgasms included some form of clitoral stimulation), and auditory (verbal, vocal) and visual (bodily) indicators of orgasm. Content analysis was used to code and analyze the data. Results were analyzed in light of sexual script theory and previous orgasm research. Only 18.3% of women, compared to 78.0% of men, were shown reaching orgasm. Sex differences in depictions of orgasm, beyond the appearance of semen, were documented. Results support the male performance script as evident in pornographic depictions of orgasm, as well as coital and orgasm imperatives. As a result, representations of male and female orgasm in mainstream pornography may serve to perpetuate unrealistic beliefs and expectations in relation to female orgasm and male sexual performance.

Apples are not the only fruit: the effects of concept typicality on semantic representation in the anterior temporal lobe

PubMed Central

Woollams, Anna M.

2012-01-01

Intuitively, an apple seems a fairly good example of a fruit, whereas an avocado seems less so. The extent to which an exemplar is representative of its category, referred to here as concept typicality, has long been thought to be a key dimension determining semantic representation. Concept typicality is, however, correlated with a number of other variables, in particular age of acquisition (AoA) and name frequency. Consideration of picture naming accuracy from a large case-series of semantic dementia (SD) patients demonstrated strong effects of concept typicality that were maximal in the moderately impaired patients, over and above the impact of AoA and name frequency. Induction of a temporary virtual lesion to the left anterior temporal lobe, the region most commonly affected in SD, via repetitive Transcranial Magnetic Stimulation produced an enhanced effect of concept typicality in the picture naming of normal participants, but did not affect the magnitude of the AoA or name frequency effects. These results indicate that concept typicality exerts its influence on semantic representations themselves, as opposed to the strength of connections outside the semantic system. To date, there has been little direct exploration of the dimension of concept typicality within connectionist models of intact and impaired conceptual representation, and these findings provide a target for future computational simulation. PMID:22529789

Kinematics of the tooth tapping movement.

PubMed

Widmalm, S E; Hedegård, B

1977-07-01

Electrical activity in the masseter muscles and tooth contact vibrations were recorded simultaneously from subjects tapping their teeth slowly into maximal intercuspidation and again with maximal frequency. High speed cinephotography was also used with four of the ten subjects. Three main parts could be distinguished on the obtained graphical representation of the tooth tapping movement: tooth contact phase (TCP), opening phase (OP) and closing phase (CP). Tapping frequency was increased by decreasing the jaw opening degree and the durations of TCP, OP and CP. The jaw velocity immediately before tooth contact, which may be of significance for the reflex response, was however not increased. The average jaw speed was nevertheless increased from 10 to 15 cm/s since the turning from OP to CP was more abrupt in high than in low frequency tapping. The duration of electrical activity after tooth contact was significantly shorter at tapping with high than with low frequency. The teeth maintained contact without detectable rebound between each open-close cycle. The OP started about 100 ms after the cessation of electrical activity both at low and high tapping frequency. The time between end of electrical activity and the start of a new OP was supposed to be dependent upon the relaxation time of the masseter muscles.

Intensity invariance properties of auditory neurons compared to the statistics of relevant natural signals in grasshoppers.

PubMed

Clemens, Jan; Weschke, Gerroth; Vogel, Astrid; Ronacher, Bernhard

2010-04-01

The temporal pattern of amplitude modulations (AM) is often used to recognize acoustic objects. To identify objects reliably, intensity invariant representations have to be formed. We approached this problem within the auditory pathway of grasshoppers. We presented AM patterns modulated at different time scales and intensities. Metric space analysis of neuronal responses allowed us to determine how well, how invariantly, and at which time scales AM frequency is encoded. We find that in some neurons spike-count cues contribute substantially (20-60%) to the decoding of AM frequency at a single intensity. However, such cues are not robust when intensity varies. The general intensity invariance of the system is poor. However, there exists a range of AM frequencies around 83 Hz where intensity invariance of local interneurons is relatively high. In this range, natural communication signals exhibit much variation between species, suggesting an important behavioral role for this frequency band. We hypothesize, just as has been proposed for human speech, that the communication signals might have evolved to match the processing properties of the receivers. This contrasts with optimal coding theory, which postulates that neuronal systems are adapted to the statistics of the relevant signals.

Frequency-Shift Detectors Bind Binaural as Well as Monaural Frequency Representations

ERIC Educational Resources Information Center

Carcagno, Samuele; Semal, Catherine; Demany, Laurent

2011-01-01

Previous psychophysical work provided evidence for the existence of automatic frequency-shift detectors (FSDs) that establish perceptual links between successive sounds. In this study, we investigated the characteristics of the FSDs with respect to the binaural system. Listeners were presented with sound sequences consisting of a chord of pure…

Do Monkeys Think in Metaphors? Representations of Space and Time in Monkeys and Humans

ERIC Educational Resources Information Center

Merritt, Dustin J.; Casasanto, Daniel; Brannon, Elizabeth M.

2010-01-01

Research on the relationship between the representation of space and time has produced two contrasting proposals. ATOM posits that space and time are represented via a common magnitude system, suggesting a symmetrical relationship between space and time. According to metaphor theory, however, representations of time depend on representations of…

On a cost functional for H2/H(infinity) minimization

NASA Technical Reports Server (NTRS)

Macmartin, Douglas G.; Hall, Steven R.; Mustafa, Denis

1990-01-01

A cost functional is proposed and investigated which is motivated by minimizing the energy in a structure using only collocated feedback. Defined for an H(infinity)-norm bounded system, this cost functional also overbounds the H2 cost. Some properties of this cost functional are given, and preliminary results on the procedure for minimizing it are presented. The frequency domain cost functional is shown to have a time domain representation in terms of a Stackelberg non-zero sum differential game.

Model-Based Self-Tuning Multiscale Method for Combustion Control

NASA Technical Reports Server (NTRS)

Le, Dzu, K.; DeLaat, John C.; Chang, Clarence T.; Vrnak, Daniel R.

2006-01-01

A multi-scale representation of the combustor dynamics was used to create a self-tuning, scalable controller to suppress multiple instability modes in a liquid-fueled aero engine-derived combustor operating at engine-like conditions. Its self-tuning features designed to handle the uncertainties in the combustor dynamics and time-delays are essential for control performance and robustness. The controller was implemented to modulate a high-frequency fuel valve with feedback from dynamic pressure sensors. This scalable algorithm suppressed pressure oscillations of different instability modes by as much as 90 percent without the peak-splitting effect. The self-tuning logic guided the adjustment of controller parameters and converged quickly toward phase-lock for optimal suppression of the instabilities. The forced-response characteristics of the control model compare well with those of the test rig on both the frequency-domain and the time-domain.

User's manual SIG: a general-purpose signal processing program

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lager, D.; Azevedo, S.

1983-10-25

SIG is a general-purpose signal processing, analysis, and display program. Its main purpose is to perform manipulations on time- and frequency-domain signals. However, it has been designed to ultimately accommodate other representations for data such as multiplexed signals and complex matrices. Many of the basic operations one would perform on digitized data are contained in the core SIG package. Out of these core commands, more powerful signal processing algorithms may be built. Many different operations on time- and frequency-domain signals can be performed by SIG. They include operations on the samples of a signal, such as adding a scalar tomore » each sample, operations on the entire signal such as digital filtering, and operations on two or more signals such as adding two signals. Signals may be simulated, such as a pulse train or a random waveform. Graphics operations display signals and spectra.« less

Investigation of multidimensional control systems in the state space and wavelet medium

NASA Astrophysics Data System (ADS)

Fedosenkov, D. B.; Simikova, A. A.; Fedosenkov, B. A.

2018-05-01

The notions are introduced of “one-dimensional-point” and “multidimensional-point” automatic control systems. To demonstrate the joint use of approaches based on the concepts of state space and wavelet transforms, a method for optimal control in a state space medium represented in the form of time-frequency representations (maps), is considered. The computer-aided control system is formed on the basis of the similarity transformation method, which makes it possible to exclude the use of reduced state variable observers. 1D-material flow signals formed by primary transducers are converted by means of wavelet transformations into multidimensional concentrated-at-a point variables in the form of time-frequency distributions of Cohen’s class. The algorithm for synthesizing a stationary controller for feeding processes is given here. The conclusion is made that the formation of an optimal control law with time-frequency distributions available contributes to the improvement of transient processes quality in feeding subsystems and the mixing unit. Confirming the efficiency of the method presented is illustrated by an example of the current registration of material flows in the multi-feeding unit. The first section in your paper.

Accumulated source imaging of brain activity with both low and high-frequency neuromagnetic signals

PubMed Central

Xiang, Jing; Luo, Qian; Kotecha, Rupesh; Korman, Abraham; Zhang, Fawen; Luo, Huan; Fujiwara, Hisako; Hemasilpin, Nat; Rose, Douglas F.

2014-01-01

Recent studies have revealed the importance of high-frequency brain signals (>70 Hz). One challenge of high-frequency signal analysis is that the size of time-frequency representation of high-frequency brain signals could be larger than 1 terabytes (TB), which is beyond the upper limits of a typical computer workstation's memory (<196 GB). The aim of the present study is to develop a new method to provide greater sensitivity in detecting high-frequency magnetoencephalography (MEG) signals in a single automated and versatile interface, rather than the more traditional, time-intensive visual inspection methods, which may take up to several days. To address the aim, we developed a new method, accumulated source imaging, defined as the volumetric summation of source activity over a period of time. This method analyzes signals in both low- (1~70 Hz) and high-frequency (70~200 Hz) ranges at source levels. To extract meaningful information from MEG signals at sensor space, the signals were decomposed to channel-cross-channel matrix (CxC) representing the spatiotemporal patterns of every possible sensor-pair. A new algorithm was developed and tested by calculating the optimal CxC and source location-orientation weights for volumetric source imaging, thereby minimizing multi-source interference and reducing computational cost. The new method was implemented in C/C++ and tested with MEG data recorded from clinical epilepsy patients. The results of experimental data demonstrated that accumulated source imaging could effectively summarize and visualize MEG recordings within 12.7 h by using approximately 10 GB of computer memory. In contrast to the conventional method of visually identifying multi-frequency epileptic activities that traditionally took 2–3 days and used 1–2 TB storage, the new approach can quantify epileptic abnormalities in both low- and high-frequency ranges at source levels, using much less time and computer memory. PMID:24904402

Accumulated source imaging of brain activity with both low and high-frequency neuromagnetic signals.

PubMed

Xiang, Jing; Luo, Qian; Kotecha, Rupesh; Korman, Abraham; Zhang, Fawen; Luo, Huan; Fujiwara, Hisako; Hemasilpin, Nat; Rose, Douglas F

2014-01-01

Recent studies have revealed the importance of high-frequency brain signals (>70 Hz). One challenge of high-frequency signal analysis is that the size of time-frequency representation of high-frequency brain signals could be larger than 1 terabytes (TB), which is beyond the upper limits of a typical computer workstation's memory (<196 GB). The aim of the present study is to develop a new method to provide greater sensitivity in detecting high-frequency magnetoencephalography (MEG) signals in a single automated and versatile interface, rather than the more traditional, time-intensive visual inspection methods, which may take up to several days. To address the aim, we developed a new method, accumulated source imaging, defined as the volumetric summation of source activity over a period of time. This method analyzes signals in both low- (1~70 Hz) and high-frequency (70~200 Hz) ranges at source levels. To extract meaningful information from MEG signals at sensor space, the signals were decomposed to channel-cross-channel matrix (CxC) representing the spatiotemporal patterns of every possible sensor-pair. A new algorithm was developed and tested by calculating the optimal CxC and source location-orientation weights for volumetric source imaging, thereby minimizing multi-source interference and reducing computational cost. The new method was implemented in C/C++ and tested with MEG data recorded from clinical epilepsy patients. The results of experimental data demonstrated that accumulated source imaging could effectively summarize and visualize MEG recordings within 12.7 h by using approximately 10 GB of computer memory. In contrast to the conventional method of visually identifying multi-frequency epileptic activities that traditionally took 2-3 days and used 1-2 TB storage, the new approach can quantify epileptic abnormalities in both low- and high-frequency ranges at source levels, using much less time and computer memory.

Asynchronous inputs alter excitability, spike timing, and topography in primary auditory cortex

PubMed Central

Pandya, Pritesh K.; Moucha, Raluca; Engineer, Navzer D.; Rathbun, Daniel L.; Vazquez, Jessica; Kilgard, Michael P.

2010-01-01

Correlation-based synaptic plasticity provides a potential cellular mechanism for learning and memory. Studies in the visual and somatosensory systems have shown that behavioral and surgical manipulation of sensory inputs leads to changes in cortical organization that are consistent with the operation of these learning rules. In this study, we examine how the organization of primary auditory cortex (A1) is altered by tones designed to decrease the average input correlation across the frequency map. After one month of separately pairing nucleus basalis stimulation with 2 and 14 kHz tones, a greater proportion of A1 neurons responded to frequencies below 2 kHz and above 14 kHz. Despite the expanded representation of these tones, cortical excitability was specifically reduced in the high and low frequency regions of A1, as evidenced by increased neural thresholds and decreased response strength. In contrast, in the frequency region between the two paired tones, driven rates were unaffected and spontaneous firing rate was increased. Neural response latencies were increased across the frequency map when nucleus basalis stimulation was associated with asynchronous activation of the high and low frequency regions of A1. This set of changes did not occur when pulsed noise bursts were paired with nucleus basalis stimulation. These results are consistent with earlier observations that sensory input statistics can shape cortical map organization and spike timing. PMID:15855025

Automatic Seismic-Event Classification with Convolutional Neural Networks.

NASA Astrophysics Data System (ADS)

Bueno Rodriguez, A.; Titos Luzón, M.; Garcia Martinez, L.; Benitez, C.; Ibáñez, J. M.

2017-12-01

Active volcanoes exhibit a wide range of seismic signals, providing vast amounts of unlabelled volcano-seismic data that can be analyzed through the lens of artificial intelligence. However, obtaining high-quality labelled data is time-consuming and expensive. Deep neural networks can process data in their raw form, compute high-level features and provide a better representation of the input data distribution. These systems can be deployed to classify seismic data at scale, enhance current early-warning systems and build extensive seismic catalogs. In this research, we aim to classify spectrograms from seven different seismic events registered at "Volcán de Fuego" (Colima, Mexico), during four eruptive periods. Our approach is based on convolutional neural networks (CNNs), a sub-type of deep neural networks that can exploit grid structure from the data. Volcano-seismic signals can be mapped into a grid-like structure using the spectrogram: a representation of the temporal evolution in terms of time and frequency. Spectrograms were computed from the data using Hamming windows with 4 seconds length, 2.5 seconds overlapping and 128 points FFT resolution. Results are compared to deep neural networks, random forest and SVMs. Experiments show that CNNs can exploit temporal and frequency information, attaining a classification accuracy of 93%, similar to deep networks 91% but outperforming SVM and random forest. These results empirically show that CNNs are powerful models to classify a wide range of volcano-seismic signals, and achieve good generalization. Furthermore, volcano-seismic spectrograms contains useful discriminative information for the CNN, as higher layers of the network combine high-level features computed for each frequency band, helping to detect simultaneous events in time. Being at the intersection of deep learning and geophysics, this research enables future studies of how CNNs can be used in volcano monitoring to accurately determine the detection and location of seismic events.

Magnetic Photon Splitting: The S-Matrix Formulation in the Landau Representation

NASA Technical Reports Server (NTRS)

Baring, Matthew G.

1999-01-01

Calculations of reaction rates for the third-order QED process of photon splitting gamma yields gamma.gamma in strong magnetic fields traditionally have employed either the effective Lagrangian method or variants of Schwinger's proper-time technique. Recently, Mentzel, Berg and Wunner [1] presented an alternative derivation via an S-matrix formulation in the Landau representation. Advantages of such a formulation include the ability to compute rates near pair resonances above pair threshold. This paper presents new developments of the Landau representation formalism as applied to photon splitting, providing significant, advances beyond the work of [1] by summing over the spin quantum numbers of the electron propagators, and analytically integrating over the component of momentum of the intermediate states that is parallel to field. The ensuing tractable expressions for the scattering amplitudes are satisfyingly compact, and of an appearance familiar to S-matrix theory applications. Such developments can facilitate numerical computations of splitting considerably both below and above pair threshold. Specializations to two regimes of interest are obtained, namely the limit of highly supercritical fields and the domain where photon energies are far inferior to that for the threshold of single-photon pair creation. In particular, for the first time the low-frequency amplitudes are simply expressed in terms of the Gamma function, its integral and its derivatives. In addition, the equivalence of the asymptotic forms in these two domains to extant results from effective Lagrangian/proper- time formulations is demonstrated.

Spatial cue reliability drives frequency tuning in the barn Owl's midbrain

PubMed Central

Cazettes, Fanny; Fischer, Brian J; Pena, Jose L

2014-01-01

The robust representation of the environment from unreliable sensory cues is vital for the efficient function of the brain. However, how the neural processing captures the most reliable cues is unknown. The interaural time difference (ITD) is the primary cue to localize sound in horizontal space. ITD is encoded in the firing rate of neurons that detect interaural phase difference (IPD). Due to the filtering effect of the head, IPD for a given location varies depending on the environmental context. We found that, in barn owls, at each location there is a frequency range where the head filtering yields the most reliable IPDs across contexts. Remarkably, the frequency tuning of space-specific neurons in the owl's midbrain varies with their preferred sound location, matching the range that carries the most reliable IPD. Thus, frequency tuning in the owl's space-specific neurons reflects a higher-order feature of the code that captures cue reliability. DOI: http://dx.doi.org/10.7554/eLife.04854.001 PMID:25531067

Dynamic Response of a Planetary Gear System Using a Finite Element/Contact Mechanics Model

NASA Technical Reports Server (NTRS)

Parker, Robert G.; Agashe, Vinayak; Vijayakar, Sandeep M.

2000-01-01

The dynamic response of a helicopter planetary gear system is examined over a wide range of operating speeds and torques. The analysis tool is a unique, semianalytical finite element formulation that admits precise representation of the tooth geometry and contact forces that are crucial in gear dynamics. Importantly, no a priori specification of static transmission error excitation or mesh frequency variation is required; the dynamic contact forces are evaluated internally at each time step. The calculated response shows classical resonances when a harmonic of mesh frequency coincides with a natural frequency. However, peculiar behavior occurs where resonances expected to be excited at a given speed are absent. This absence of particular modes is explained by analytical relationships that depend on the planetary configuration and mesh frequency harmonic. The torque sensitivity of the dynamic response is examined and compared to static analyses. Rotation mode response is shown to be more sensitive to input torque than translational mode response.

Symmetric quadratic Hamiltonians with pseudo-Hermitian matrix representation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fernández, Francisco M., E-mail: fernande@quimica.unlp.edu.ar

2016-06-15

We prove that any symmetric Hamiltonian that is a quadratic function of the coordinates and momenta has a pseudo-Hermitian adjoint or regular matrix representation. The eigenvalues of the latter matrix are the natural frequencies of the Hamiltonian operator. When all the eigenvalues of the matrix are real, then the spectrum of the symmetric Hamiltonian is real and the operator is Hermitian. As illustrative examples we choose the quadratic Hamiltonians that model a pair of coupled resonators with balanced gain and loss, the electromagnetic self-force on an oscillating charged particle and an active LRC circuit. -- Highlights: •Symmetric quadratic operators aremore » useful models for many physical applications. •Any such operator exhibits a pseudo-Hermitian matrix representation. •Its eigenvalues are the natural frequencies of the Hamiltonian operator. •The eigenvalues may be real or complex and describe a phase transition.« less

A novel representation for apoptosis protein subcellular localization prediction using support vector machine.

PubMed

Zhang, Li; Liao, Bo; Li, Dachao; Zhu, Wen

2009-07-21

Apoptosis, or programmed cell death, plays an important role in development of an organism. Obtaining information on subcellular location of apoptosis proteins is very helpful to understand the apoptosis mechanism. In this paper, based on the concept that the position distribution information of amino acids is closely related with the structure and function of proteins, we introduce the concept of distance frequency [Matsuda, S., Vert, J.P., Ueda, N., Toh, H., Akutsu, T., 2005. A novel representation of protein sequences for prediction of subcellular location using support vector machines. Protein Sci. 14, 2804-2813] and propose a novel way to calculate distance frequencies. In order to calculate the local features, each protein sequence is separated into p parts with the same length in our paper. Then we use the novel representation of protein sequences and adopt support vector machine to predict subcellular location. The overall prediction accuracy is significantly improved by jackknife test.

Atypical language representation in children with intractable temporal lobe epilepsy.

PubMed

Maulisova, Alice; Korman, Brandon; Rey, Gustavo; Bernal, Byron; Duchowny, Michael; Niederlova, Marketa; Krsek, Pavel; Novak, Vilem

2016-05-01

This study evaluated language organization in children with intractable epilepsy caused by temporal lobe focal cortical dysplasia (FCD) alone or dual pathology (temporal lobe FCD and hippocampal sclerosis, HS). We analyzed clinical, neurological, fMRI, neuropsychological, and histopathologic data in 46 pediatric patients with temporal lobe lesions who underwent excisional epilepsy surgery. The frequency of atypical language representation was similar in both groups, but children with dual pathology were more likely to be left-handed. Atypical receptive language cortex correlated with lower intellectual capacity, verbal abstract conceptualization, receptive language abilities, verbal working memory, and a history of status epilepticus but did not correlate with higher seizure frequency or early seizure onset. Histopathologic substrate had only a minor influence on neuropsychological status. Greater verbal comprehension deficits were noted in children with atypical receptive language representation, a risk factor for cognitive morbidity. Copyright © 2016 Elsevier Inc. All rights reserved.

Input-Specific Gain Modulation by Local Sensory Context Shapes Cortical and Thalamic Responses to Complex Sounds.

PubMed

Williamson, Ross S; Ahrens, Misha B; Linden, Jennifer F; Sahani, Maneesh

2016-07-20

Sensory neurons are customarily characterized by one or more linearly weighted receptive fields describing sensitivity in sensory space and time. We show that in auditory cortical and thalamic neurons, the weight of each receptive field element depends on the pattern of sound falling within a local neighborhood surrounding it in time and frequency. Accounting for this change in effective receptive field with spectrotemporal context improves predictions of both cortical and thalamic responses to stationary complex sounds. Although context dependence varies among neurons and across brain areas, there are strong shared qualitative characteristics. In a spectrotemporally rich soundscape, sound elements modulate neuronal responsiveness more effectively when they coincide with sounds at other frequencies, and less effectively when they are preceded by sounds at similar frequencies. This local-context-driven lability in the representation of complex sounds-a modulation of "input-specific gain" rather than "output gain"-may be a widespread motif in sensory processing. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Lexical restructuring in the absence of literacy.

PubMed

Venturaa, Paulo; Kolinsky, Régine; Fernandesa, Sandra; Queridoa, Luís; Morais, José

2007-11-01

Vocabulary growth was suggested to prompt the implementation of increasingly finer-grained lexical representations of spoken words in children (e.g., [Metsala, J. L., & Walley, A. C. (1998). Spoken vocabulary growth and the segmental restructuring of lexical representations: precursors to phonemic awareness and early reading ability. In J. L. Metsala & L. C. Ehri (Eds.), Word recognition in beginning literacy (pp. 89-120). Hillsdale, NJ: Erlbaum.]). Although literacy was not explicitly mentioned in this lexical restructuring hypothesis, the process of learning to read and spell might also have a significant impact on the specification of lexical representations (e.g., [Carroll, J. M., & Snowling, M. J. (2001). The effects of global similarity between stimuli on children's judgments of rime and alliteration. Applied Psycholinguistics, 22, 327-342.]; [Goswami, U. (2000). Phonological representations, reading development and dyslexia: Towards a cross-linguistic theoretical framework. Dyslexia, 6, 133-151.]). This is what we checked in the present study. We manipulated word frequency and neighborhood density in a gating task (Experiment 1) and a word-identification-in-noise task (Experiment 2) presented to Portuguese literate and illiterate adults. Ex-illiterates were also tested in Experiment 2 in order to disentangle the effects of vocabulary size and literacy. There was an interaction between word frequency and neighborhood density, which was similar in the three groups. These did not differ even for the words that are supposed to undergo lexical restructuring the latest (low frequency words from sparse neighborhoods). Thus, segmental lexical representations seem to develop independently of literacy. While segmental restructuring is not affected by literacy, it constrains the development of phoneme awareness as shown by the fact that, in Experiment 3, neighborhood density modulated the phoneme deletion performance of both illiterates and ex-illiterates.

Neglecting the Left Side of a City Square but Not the Left Side of Its Clock: Prevalence and Characteristics of Representational Neglect

PubMed Central

Guariglia, Cecilia; Palermo, Liana; Piccardi, Laura; Iaria, Giuseppe; Incoccia, Chiara

2013-01-01

Representational neglect, which is characterized by the failure to report left-sided details of a mental image from memory, can occur after a right hemisphere lesion. In this study, we set out to verify the hypothesis that two distinct forms of representational neglect exist, one involving object representation and the other environmental representation. As representational neglect is considered rare, we also evaluated the prevalence and frequency of its association with perceptual neglect. We submitted a group of 96 unselected, consecutive, chronic, right brain-damaged patients to an extensive neuropsychological evaluation that included two representational neglect tests: the Familiar Square Description Test and the O'Clock Test. Representational neglect, as well as perceptual neglect, was present in about one-third of the sample. Most patients neglected the left side of imagined familiar squares but not the left side of imagined clocks. The present data show that representational neglect is not a rare disorder and also support the hypothesis that two different types of mental representations (i.e. topological and non-topological images) may be selectively damaged in representational neglect. PMID:23874416

Joint High-Order Synchrosqueezing Transform and Multi-Taper Empirical Wavelet Transform for Fault Diagnosis of Wind Turbine Planetary Gearbox under Nonstationary Conditions.

PubMed

Hu, Yue; Tu, Xiaotong; Li, Fucai; Meng, Guang

2018-01-07

Wind turbines usually operate under nonstationary conditions, such as wide-range speed fluctuation and time-varying load. Its critical component, the planetary gearbox, is prone to malfunction or failure, which leads to downtime and repair costs. Therefore, fault diagnosis and condition monitoring for the planetary gearbox in wind turbines is a vital research topic. Meanwhile, the signals measured by the vibration sensors mounted in the gearbox exhibit time-varying and nonstationary features. In this study, a novel time-frequency method based on high-order synchrosqueezing transform (SST) and multi-taper empirical wavelet transform (MTEWT) is proposed for the wind turbine planetary gearbox under nonstationary conditions. The high-order SST uses accurate instantaneous frequency approximations to obtain a sharper time-frequency representation (TFR). As the acquired signal consists of many components, like the meshing and rotating components of the gear and bearing, the fault component may be masked by other unrelated components. The MTEWT is used to separate the fault feature from the masking components. A variety of experimental signals of the wind turbine planetary gearbox under nonstationary conditions have been analyzed to demonstrate the effectiveness and robustness of the proposed method. Results show that the proposed method is effective in diagnosing both gear and bearing faults.

Joint High-Order Synchrosqueezing Transform and Multi-Taper Empirical Wavelet Transform for Fault Diagnosis of Wind Turbine Planetary Gearbox under Nonstationary Conditions

PubMed Central

Li, Fucai; Meng, Guang

2018-01-01

Wind turbines usually operate under nonstationary conditions, such as wide-range speed fluctuation and time-varying load. Its critical component, the planetary gearbox, is prone to malfunction or failure, which leads to downtime and repair costs. Therefore, fault diagnosis and condition monitoring for the planetary gearbox in wind turbines is a vital research topic. Meanwhile, the signals measured by the vibration sensors mounted in the gearbox exhibit time-varying and nonstationary features. In this study, a novel time-frequency method based on high-order synchrosqueezing transform (SST) and multi-taper empirical wavelet transform (MTEWT) is proposed for the wind turbine planetary gearbox under nonstationary conditions. The high-order SST uses accurate instantaneous frequency approximations to obtain a sharper time-frequency representation (TFR). As the acquired signal consists of many components, like the meshing and rotating components of the gear and bearing, the fault component may be masked by other unrelated components. The MTEWT is used to separate the fault feature from the masking components. A variety of experimental signals of the wind turbine planetary gearbox under nonstationary conditions have been analyzed to demonstrate the effectiveness and robustness of the proposed method. Results show that the proposed method is effective in diagnosing both gear and bearing faults. PMID:29316668

The effects of nicotine exposure and PFC transection on the time-frequency distribution of VTA DA neurons' firing activities.

PubMed

Chen, Ting Y; Zhang, Die; Dragomir, Andrei; Akay, Yasemin; Akay, Metin

2011-05-01

We investigated the influence of nicotine exposure and prefrontal cortex (PFC) transections on ventral tegmental areas (VTA) dopamine (DA) neurons' firing activities using a time-frequency method based on the continuous wavelet transform (CWT). Extracellular single-unit neural activity was recorded from DA neurons in the VTA area of rats. One group had their PFC inputs to the VTA intact, while the other group had the inputs to VTA bilaterally transected immediate caudal to the PFC. We hypothesized that the systemic nicotine exposure will significantly change the energy distribution in the recorded neural activity. Additionally, we investigated whether the loss of inputs to the VTA caused by the PFC transection resulted in the cancellation of the nicotine' effect on the neurons' firing patterns. The time-frequency representations of VTA DA neurons firing activity were estimated from the reconstructed firing rate histogram. The energy contents were estimated from three frequency bands, which are known to encompass the significant modes of operation of DA neurons. Our results show that systemic nicotine exposure disrupts the energy distribution in PFC-intact rats. Particularly, there is a significant increase in energy contents of the 1-1.5 Hz frequency band. This corresponds to an observed increase in the firing rate of VTA DA neurons following nicotine exposure. Additionally, our results from PFC-transected rats show that there is no change in the energy distribution of the recordings after systemic nicotine exposure. These results indicate that the PFC plays an important role in affecting the activities of VTA DA neurons and that the CWT is a useful method for monitoring the changes in neural activity patterns in both time and frequency domains.

Dynamical density delay maps: simple, new method for visualising the behaviour of complex systems

PubMed Central

2014-01-01

Background Physiologic signals, such as cardiac interbeat intervals, exhibit complex fluctuations. However, capturing important dynamical properties, including nonstationarities may not be feasible from conventional time series graphical representations. Methods We introduce a simple-to-implement visualisation method, termed dynamical density delay mapping (“D3-Map” technique) that provides an animated representation of a system’s dynamics. The method is based on a generalization of conventional two-dimensional (2D) Poincaré plots, which are scatter plots where each data point, x(n), in a time series is plotted against the adjacent one, x(n + 1). First, we divide the original time series, x(n) (n = 1,…, N), into a sequence of segments (windows). Next, for each segment, a three-dimensional (3D) Poincaré surface plot of x(n), x(n + 1), h[x(n),x(n + 1)] is generated, in which the third dimension, h, represents the relative frequency of occurrence of each (x(n),x(n + 1)) point. This 3D Poincaré surface is then chromatised by mapping the relative frequency h values onto a colour scheme. We also generate a colourised 2D contour plot from each time series segment using the same colourmap scheme as for the 3D Poincaré surface. Finally, the original time series graph, the colourised 3D Poincaré surface plot, and its projection as a colourised 2D contour map for each segment, are animated to create the full “D3-Map.” Results We first exemplify the D3-Map method using the cardiac interbeat interval time series from a healthy subject during sleeping hours. The animations uncover complex dynamical changes, such as transitions between states, and the relative amount of time the system spends in each state. We also illustrate the utility of the method in detecting hidden temporal patterns in the heart rate dynamics of a patient with atrial fibrillation. The videos, as well as the source code, are made publicly available. Conclusions Animations based on density delay maps provide a new way of visualising dynamical properties of complex systems not apparent in time series graphs or standard Poincaré plot representations. Trainees in a variety of fields may find the animations useful as illustrations of fundamental but challenging concepts, such as nonstationarity and multistability. For investigators, the method may facilitate data exploration. PMID:24438439

Mean first passage times of Brownian rotators from differential recurrence relations

NASA Astrophysics Data System (ADS)

Coffey, W. T.

1999-11-01

An exact method of calculation of mean first passage times (analogous to that previously used [W. T. Coffey, Yu. P. Kalmykov, E. S. Massawe, and J. T. Waldron, J. Chem. Phys. 99, 4011 (1993)] for the correlation time) is developed in terms of continued fractions from the zero frequency limit of the Laplace transform of the set of differential recurrence relations generated by the Fokker-Planck or Langevin equations. The method because it is based on a Floquet representation avoids the use of quadratures and so may be easily generalized to multidegree of freedom systems by the use of matrix continued fractions. The procedure is illustrated by considering the mean first passage time of a fixed axis rotator with two equivalent sites.

Auditory-motor Mapping for Pitch Control in Singers and Nonsingers

PubMed Central

Jones, Jeffery A.; Keough, Dwayne

2009-01-01

Little is known about the basic processes underlying the behavior of singing. This experiment was designed to examine differences in the representation of the mapping between fundamental frequency (F0) feedback and the vocal production system in singers and nonsingers. Auditory feedback regarding F0 was shifted down in frequency while participants sang the consonant-vowel /ta/. During the initial frequency-altered trials, singers compensated to a lesser degree than nonsingers, but this difference was reduced with continued exposure to frequency-altered feedback. After brief exposure to frequency altered auditory feedback, both singers and nonsingers suddenly heard their F0 unaltered. When participants received this unaltered feedback, only singers' F0 values were found to be significantly higher than their F0 values produced during baseline and control trials. These aftereffects in singers were replicated when participants sang a different note than the note they produced while hearing altered feedback. Together, these results suggest that singers rely more on internal models than nonsingers to regulate vocal productions rather than real time auditory feedback. PMID:18592224

Energy Efficient GNSS Signal Acquisition Using Singular Value Decomposition (SVD).

PubMed

Bermúdez Ordoñez, Juan Carlos; Arnaldo Valdés, Rosa María; Gómez Comendador, Fernando

2018-05-16

A significant challenge in global navigation satellite system (GNSS) signal processing is a requirement for a very high sampling rate. The recently-emerging compressed sensing (CS) theory makes processing GNSS signals at a low sampling rate possible if the signal has a sparse representation in a certain space. Based on CS and SVD theories, an algorithm for sampling GNSS signals at a rate much lower than the Nyquist rate and reconstructing the compressed signal is proposed in this research, which is validated after the output from that process still performs signal detection using the standard fast Fourier transform (FFT) parallel frequency space search acquisition. The sparse representation of the GNSS signal is the most important precondition for CS, by constructing a rectangular Toeplitz matrix (TZ) of the transmitted signal, calculating the left singular vectors using SVD from the TZ, to achieve sparse signal representation. Next, obtaining the M-dimensional observation vectors based on the left singular vectors of the SVD, which are equivalent to the sampler operator in standard compressive sensing theory, the signal can be sampled below the Nyquist rate, and can still be reconstructed via ℓ 1 minimization with accuracy using convex optimization. As an added value, there is a GNSS signal acquisition enhancement effect by retaining the useful signal and filtering out noise by projecting the signal into the most significant proper orthogonal modes (PODs) which are the optimal distributions of signal power. The algorithm is validated with real recorded signals, and the results show that the proposed method is effective for sampling, reconstructing intermediate frequency (IF) GNSS signals in the time discrete domain.

Energy Efficient GNSS Signal Acquisition Using Singular Value Decomposition (SVD)

PubMed Central

Arnaldo Valdés, Rosa María; Gómez Comendador, Fernando

2018-01-01

A significant challenge in global navigation satellite system (GNSS) signal processing is a requirement for a very high sampling rate. The recently-emerging compressed sensing (CS) theory makes processing GNSS signals at a low sampling rate possible if the signal has a sparse representation in a certain space. Based on CS and SVD theories, an algorithm for sampling GNSS signals at a rate much lower than the Nyquist rate and reconstructing the compressed signal is proposed in this research, which is validated after the output from that process still performs signal detection using the standard fast Fourier transform (FFT) parallel frequency space search acquisition. The sparse representation of the GNSS signal is the most important precondition for CS, by constructing a rectangular Toeplitz matrix (TZ) of the transmitted signal, calculating the left singular vectors using SVD from the TZ, to achieve sparse signal representation. Next, obtaining the M-dimensional observation vectors based on the left singular vectors of the SVD, which are equivalent to the sampler operator in standard compressive sensing theory, the signal can be sampled below the Nyquist rate, and can still be reconstructed via ℓ1 minimization with accuracy using convex optimization. As an added value, there is a GNSS signal acquisition enhancement effect by retaining the useful signal and filtering out noise by projecting the signal into the most significant proper orthogonal modes (PODs) which are the optimal distributions of signal power. The algorithm is validated with real recorded signals, and the results show that the proposed method is effective for sampling, reconstructing intermediate frequency (IF) GNSS signals in the time discrete domain. PMID:29772731

The importance of context: evidence that contextual representations increase intrusive memories.

PubMed

Pearson, David G; Ross, Fiona D C; Webster, Victoria L

2012-03-01

Intrusive memories appear to enter consciousness via involuntary rather than deliberate recollection. Some clinical accounts of PTSD seek to explain this phenomenon by making a clear distinction between the encoding of sensory-based and contextual representations. Contextual representations have been claimed to actively reduce intrusions by anchoring encoded perceptual data for an event in memory. The current analogue trauma study examined this hypothesis by manipulating contextual information independently from encoded sensory-perceptual information. Participants' viewed images selected from the International Affective Picture System that depicted scenes of violence and bodily injury. Images were viewed either under neutral conditions or paired with contextual information. Two experiments revealed a significant increase in memory intrusions for images paired with contextual information in comparison to the same images viewed under neutral conditions. In contrast to the observed increase in intrusion frequency there was no effect of contextual representations on voluntary memory for the images. The vividness and emotionality of memory intrusions were also unaffected. The analogue trauma paradigm may fail to replicate the effect of extreme stress on encoding postulated to occur during PTSD. These findings question the assertion that intrusive memories develop from a lack of integration between sensory-based and contextual representations in memory. Instead it is argued contextual representations play a causal role in increasing the frequency of intrusions by increasing the sensitivity of memory to involuntary retrieval by associated internal and external cues. Copyright © 2011 Elsevier Ltd. All rights reserved.

Fixed versus mixed RSA: Explaining visual representations by fixed and mixed feature sets from shallow and deep computational models.

PubMed

Khaligh-Razavi, Seyed-Mahdi; Henriksson, Linda; Kay, Kendrick; Kriegeskorte, Nikolaus

2017-02-01

Studies of the primate visual system have begun to test a wide range of complex computational object-vision models. Realistic models have many parameters, which in practice cannot be fitted using the limited amounts of brain-activity data typically available. Task performance optimization (e.g. using backpropagation to train neural networks) provides major constraints for fitting parameters and discovering nonlinear representational features appropriate for the task (e.g. object classification). Model representations can be compared to brain representations in terms of the representational dissimilarities they predict for an image set. This method, called representational similarity analysis (RSA), enables us to test the representational feature space as is (fixed RSA) or to fit a linear transformation that mixes the nonlinear model features so as to best explain a cortical area's representational space (mixed RSA). Like voxel/population-receptive-field modelling, mixed RSA uses a training set (different stimuli) to fit one weight per model feature and response channel (voxels here), so as to best predict the response profile across images for each response channel. We analysed response patterns elicited by natural images, which were measured with functional magnetic resonance imaging (fMRI). We found that early visual areas were best accounted for by shallow models, such as a Gabor wavelet pyramid (GWP). The GWP model performed similarly with and without mixing, suggesting that the original features already approximated the representational space, obviating the need for mixing. However, a higher ventral-stream visual representation (lateral occipital region) was best explained by the higher layers of a deep convolutional network and mixing of its feature set was essential for this model to explain the representation. We suspect that mixing was essential because the convolutional network had been trained to discriminate a set of 1000 categories, whose frequencies in the training set did not match their frequencies in natural experience or their behavioural importance. The latter factors might determine the representational prominence of semantic dimensions in higher-level ventral-stream areas. Our results demonstrate the benefits of testing both the specific representational hypothesis expressed by a model's original feature space and the hypothesis space generated by linear transformations of that feature space.

Predicting Word Maturity from Frequency and Semantic Diversity: A Computational Study

ERIC Educational Resources Information Center

Jorge-Botana, Guillermo; Olmos, Ricardo; Sanjosé, Vicente

2017-01-01

Semantic word representation changes over different ages of childhood until it reaches its adult form. One method to formally model this change is the word maturity paradigm. This method uses a text sample for each age, including adult age, and transforms the samples into a semantic space by means of Latent Semantic Analysis. The representation of…

Serial recall, word frequency, and mixed lists: the influence of item arrangement.

PubMed

Miller, Leonie M; Roodenrys, Steven

2012-11-01

Studies of the effect of word frequency in the serial recall task show that lists of high-frequency words are better recalled than lists of low-frequency words; however, when high- and low-frequency words are alternated within a list, there is no difference in the level of recall for the two types of words, and recall is intermediate between lists of pure frequency. This pattern has been argued to arise from the development of a network of activated long-term representations of list items that support the redintegration of all list items in a nondirectional and nonspecific way. More recently, it has been proposed that the frequency effect might be a product of the coarticulation of items at word boundaries and their influence on rehearsal rather than a consequence of memory representations. The current work examines recall performance in mixed lists of an equal number of high- and low-frequency items arranged in contiguous segments (i.e., HHHLLL and LLLHHH), under quiet and articulatory suppression conditions, to test whether the effect is (a) nondirectional and (b) dependent on articulatory processes. These experiments demonstrate that neither explanation is satisfactory, although the results suggest that the effect is mnemonic. A language-based approach to short-term memory is favored with emphasis on the role of speech production processes at output.

Accurately Characterizing the Importance of Wave-Particle Interactions in Radiation Belt Dynamics: The Pitfalls of Statistical Wave Representations

NASA Technical Reports Server (NTRS)

Murphy, Kyle R.; Mann, Ian R.; Rae, I. Jonathan; Sibeck, David G.; Watt, Clare E. J.

2016-01-01

Wave-particle interactions play a crucial role in energetic particle dynamics in the Earths radiation belts. However, the relative importance of different wave modes in these dynamics is poorly understood. Typically, this is assessed during geomagnetic storms using statistically averaged empirical wave models as a function of geomagnetic activity in advanced radiation belt simulations. However, statistical averages poorly characterize extreme events such as geomagnetic storms in that storm-time ultralow frequency wave power is typically larger than that derived over a solar cycle and Kp is a poor proxy for storm-time wave power.

A Neuronal Network Model for Pitch Selectivity and Representation

PubMed Central

Huang, Chengcheng; Rinzel, John

2016-01-01

Pitch is a perceptual correlate of periodicity. Sounds with distinct spectra can elicit the same pitch. Despite the importance of pitch perception, understanding the cellular mechanism of pitch perception is still a major challenge and a mechanistic model of pitch is lacking. A multi-stage neuronal network model is developed for pitch frequency estimation using biophysically-based, high-resolution coincidence detector neurons. The neuronal units respond only to highly coincident input among convergent auditory nerve fibers across frequency channels. Their selectivity for only very fast rising slopes of convergent input enables these slope-detectors to distinguish the most prominent coincidences in multi-peaked input time courses. Pitch can then be estimated from the first-order interspike intervals of the slope-detectors. The regular firing pattern of the slope-detector neurons are similar for sounds sharing the same pitch despite the distinct timbres. The decoded pitch strengths also correlate well with the salience of pitch perception as reported by human listeners. Therefore, our model can serve as a neural representation for pitch. Our model performs successfully in estimating the pitch of missing fundamental complexes and reproducing the pitch variation with respect to the frequency shift of inharmonic complexes. It also accounts for the phase sensitivity of pitch perception in the cases of Schroeder phase, alternating phase and random phase relationships. Moreover, our model can also be applied to stochastic sound stimuli, iterated-ripple-noise, and account for their multiple pitch perceptions. PMID:27378900

Neural Representation of Concurrent Vowels in Macaque Primary Auditory Cortex123

PubMed Central

Micheyl, Christophe; Steinschneider, Mitchell

2016-01-01

Abstract Successful speech perception in real-world environments requires that the auditory system segregate competing voices that overlap in frequency and time into separate streams. Vowels are major constituents of speech and are comprised of frequencies (harmonics) that are integer multiples of a common fundamental frequency (F0). The pitch and identity of a vowel are determined by its F0 and spectral envelope (formant structure), respectively. When two spectrally overlapping vowels differing in F0 are presented concurrently, they can be readily perceived as two separate “auditory objects” with pitches at their respective F0s. A difference in pitch between two simultaneous vowels provides a powerful cue for their segregation, which in turn, facilitates their individual identification. The neural mechanisms underlying the segregation of concurrent vowels based on pitch differences are poorly understood. Here, we examine neural population responses in macaque primary auditory cortex (A1) to single and double concurrent vowels (/a/ and /i/) that differ in F0 such that they are heard as two separate auditory objects with distinct pitches. We find that neural population responses in A1 can resolve, via a rate-place code, lower harmonics of both single and double concurrent vowels. Furthermore, we show that the formant structures, and hence the identities, of single vowels can be reliably recovered from the neural representation of double concurrent vowels. We conclude that A1 contains sufficient spectral information to enable concurrent vowel segregation and identification by downstream cortical areas. PMID:27294198

A Neuronal Network Model for Pitch Selectivity and Representation.

PubMed

Huang, Chengcheng; Rinzel, John

2016-01-01

Pitch is a perceptual correlate of periodicity. Sounds with distinct spectra can elicit the same pitch. Despite the importance of pitch perception, understanding the cellular mechanism of pitch perception is still a major challenge and a mechanistic model of pitch is lacking. A multi-stage neuronal network model is developed for pitch frequency estimation using biophysically-based, high-resolution coincidence detector neurons. The neuronal units respond only to highly coincident input among convergent auditory nerve fibers across frequency channels. Their selectivity for only very fast rising slopes of convergent input enables these slope-detectors to distinguish the most prominent coincidences in multi-peaked input time courses. Pitch can then be estimated from the first-order interspike intervals of the slope-detectors. The regular firing pattern of the slope-detector neurons are similar for sounds sharing the same pitch despite the distinct timbres. The decoded pitch strengths also correlate well with the salience of pitch perception as reported by human listeners. Therefore, our model can serve as a neural representation for pitch. Our model performs successfully in estimating the pitch of missing fundamental complexes and reproducing the pitch variation with respect to the frequency shift of inharmonic complexes. It also accounts for the phase sensitivity of pitch perception in the cases of Schroeder phase, alternating phase and random phase relationships. Moreover, our model can also be applied to stochastic sound stimuli, iterated-ripple-noise, and account for their multiple pitch perceptions.

Coarse-grained representation of the quasi adiabatic propagator path integral for the treatment of non-Markovian long-time bath memory

NASA Astrophysics Data System (ADS)

Richter, Martin; Fingerhut, Benjamin P.

2017-06-01

The description of non-Markovian effects imposed by low frequency bath modes poses a persistent challenge for path integral based approaches like the iterative quasi-adiabatic propagator path integral (iQUAPI) method. We present a novel approximate method, termed mask assisted coarse graining of influence coefficients (MACGIC)-iQUAPI, that offers appealing computational savings due to substantial reduction of considered path segments for propagation. The method relies on an efficient path segment merging procedure via an intermediate coarse grained representation of Feynman-Vernon influence coefficients that exploits physical properties of system decoherence. The MACGIC-iQUAPI method allows us to access the regime of biological significant long-time bath memory on the order of hundred propagation time steps while retaining convergence to iQUAPI results. Numerical performance is demonstrated for a set of benchmark problems that cover bath assisted long range electron transfer, the transition from coherent to incoherent dynamics in a prototypical molecular dimer and excitation energy transfer in a 24-state model of the Fenna-Matthews-Olson trimer complex where in all cases excellent agreement with numerically exact reference data is obtained.

Proportional spike-timing precision and firing reliability underlie efficient temporal processing of periodicity and envelope shape cues

PubMed Central

Zheng, Y.

2013-01-01

Temporal sound cues are essential for sound recognition, pitch, rhythm, and timbre perception, yet how auditory neurons encode such cues is subject of ongoing debate. Rate coding theories propose that temporal sound features are represented by rate tuned modulation filters. However, overwhelming evidence also suggests that precise spike timing is an essential attribute of the neural code. Here we demonstrate that single neurons in the auditory midbrain employ a proportional code in which spike-timing precision and firing reliability covary with the sound envelope cues to provide an efficient representation of the stimulus. Spike-timing precision varied systematically with the timescale and shape of the sound envelope and yet was largely independent of the sound modulation frequency, a prominent cue for pitch. In contrast, spike-count reliability was strongly affected by the modulation frequency. Spike-timing precision extends from sub-millisecond for brief transient sounds up to tens of milliseconds for sounds with slow-varying envelope. Information theoretic analysis further confirms that spike-timing precision depends strongly on the sound envelope shape, while firing reliability was strongly affected by the sound modulation frequency. Both the information efficiency and total information were limited by the firing reliability and spike-timing precision in a manner that reflected the sound structure. This result supports a temporal coding strategy in the auditory midbrain where proportional changes in spike-timing precision and firing reliability can efficiently signal shape and periodicity temporal cues. PMID:23636724

Manipulation of BDNF signaling modifies the experience-dependent plasticity induced by pure tone exposure during the critical period in the primary auditory cortex.

PubMed

Anomal, Renata; de Villers-Sidani, Etienne; Merzenich, Michael M; Panizzutti, Rogerio

2013-01-01

Sensory experience powerfully shapes cortical sensory representations during an early developmental "critical period" of plasticity. In the rat primary auditory cortex (A1), the experience-dependent plasticity is exemplified by significant, long-lasting distortions in frequency representation after mere exposure to repetitive frequencies during the second week of life. In the visual system, the normal unfolding of critical period plasticity is strongly dependent on the elaboration of brain-derived neurotrophic factor (BDNF), which promotes the establishment of inhibition. Here, we tested the hypothesis that BDNF signaling plays a role in the experience-dependent plasticity induced by pure tone exposure during the critical period in the primary auditory cortex. Elvax resin implants filled with either a blocking antibody against BDNF or the BDNF protein were placed on the A1 of rat pups throughout the critical period window. These pups were then exposed to 7 kHz pure tone for 7 consecutive days and their frequency representations were mapped. BDNF blockade completely prevented the shaping of cortical tuning by experience and resulted in poor overall frequency tuning in A1. By contrast, BDNF infusion on the developing A1 amplified the effect of 7 kHz tone exposure compared to control. These results indicate that BDNF signaling participates in the experience-dependent plasticity induced by pure tone exposure during the critical period in A1.

Bio-Inspired Asynchronous Pixel Event Tricolor Vision Sensor.

PubMed

Lenero-Bardallo, Juan Antonio; Bryn, D H; Hafliger, Philipp

2014-06-01

This article investigates the potential of the first ever prototype of a vision sensor that combines tricolor stacked photo diodes with the bio-inspired asynchronous pixel event communication protocol known as Address Event Representation (AER). The stacked photo diodes are implemented in a 22 × 22 pixel array in a standard STM 90 nm CMOS process. Dynamic range is larger than 60 dB and pixels fill factor is 28%. The pixels employ either simple pulse frequency modulation (PFM) or a Time-to-First-Spike (TFS) mode. A heuristic linear combination of the chip's inherent pseudo colors serves to approximate RGB color representation. Furthermore, the sensor outputs can be processed to represent the radiation in the near infrared (NIR) band without employing external filters, and to color-encode direction of motion due to an asymmetry in the update rates of the different diode layers.

Comparison of data transformation procedures to enhance topographical accuracy in time-series analysis of the human EEG.

PubMed

Hauk, O; Keil, A; Elbert, T; Müller, M M

2002-01-30

We describe a methodology to apply current source density (CSD) and minimum norm (MN) estimation as pre-processing tools for time-series analysis of single trial EEG data. The performance of these methods is compared for the case of wavelet time-frequency analysis of simulated gamma-band activity. A reasonable comparison of CSD and MN on the single trial level requires regularization such that the corresponding transformed data sets have similar signal-to-noise ratios (SNRs). For region-of-interest approaches, it should be possible to optimize the SNR for single estimates rather than for the whole distributed solution. An effective implementation of the MN method is described. Simulated data sets were created by modulating the strengths of a radial and a tangential test dipole with wavelets in the frequency range of the gamma band, superimposed with simulated spatially uncorrelated noise. The MN and CSD transformed data sets as well as the average reference (AR) representation were subjected to wavelet frequency-domain analysis, and power spectra were mapped for relevant frequency bands. For both CSD and MN, the influence of noise can be sufficiently suppressed by regularization to yield meaningful information, but only MN represents both radial and tangential dipole sources appropriately as single peaks. Therefore, when relating wavelet power spectrum topographies to their neuronal generators, MN should be preferred.

Pre-attentive, context-specific representation of fear memory in the auditory cortex of rat.

PubMed

Funamizu, Akihiro; Kanzaki, Ryohei; Takahashi, Hirokazu

2013-01-01

Neural representation in the auditory cortex is rapidly modulated by both top-down attention and bottom-up stimulus properties, in order to improve perception in a given context. Learning-induced, pre-attentive, map plasticity has been also studied in the anesthetized cortex; however, little attention has been paid to rapid, context-dependent modulation. We hypothesize that context-specific learning leads to pre-attentively modulated, multiplex representation in the auditory cortex. Here, we investigate map plasticity in the auditory cortices of anesthetized rats conditioned in a context-dependent manner, such that a conditioned stimulus (CS) of a 20-kHz tone and an unconditioned stimulus (US) of a mild electrical shock were associated only under a noisy auditory context, but not in silence. After the conditioning, although no distinct plasticity was found in the tonotopic map, tone-evoked responses were more noise-resistive than pre-conditioning. Yet, the conditioned group showed a reduced spread of activation to each tone with noise, but not with silence, associated with a sharpening of frequency tuning. The encoding accuracy index of neurons showed that conditioning deteriorated the accuracy of tone-frequency representations in noisy condition at off-CS regions, but not at CS regions, suggesting that arbitrary tones around the frequency of the CS were more likely perceived as the CS in a specific context, where CS was associated with US. These results together demonstrate that learning-induced plasticity in the auditory cortex occurs in a context-dependent manner.

The Thaayorre think of Time Like They Talk of Space.

PubMed

Gaby, Alice

2012-01-01

Around the world, it is common to both talk and think about time in terms of space. But does our conceptualization of time simply reflect the space/time metaphors of the language we speak? Evidence from the Australian language Kuuk Thaayorre suggests not. Kuuk Thaayorre speakers do not employ active spatial metaphors in describing time. But this is not to say that spatial language is irrelevant to temporal construals: non-linguistic representations of time are shown here to covary with the linguistic system of describing space. This article contrasts two populations of ethnic Thaayorre from Pormpuraaw - one comprising Kuuk Thaayorre/English bilinguals and the other English-monolinguals - in order to distinguish the effects of language from environmental and other factors. Despite their common physical, social, and cultural context, the two groups differ in their representations of time in ways that are congruent with the language of space in Kuuk Thaayorre and English, respectively. Kuuk Thaayorre/English bilinguals represent time along an absolute east-to-west axis, in alignment with the high frequency of absolute frame of reference terms in Kuuk Thaayorre spatial description. The English-monolinguals, in contrast, represent time from left-to-right, aligning with the dominant relative frame of reference in English spatial description. This occurs in the absence of any east-to-west metaphors in Kuuk Thaayorre, or left-to-right metaphors in English. Thus the way these two groups think about time appears to reflect the language of space and not the language of time.

Prediction of cause of death from forensic autopsy reports using text classification techniques: A comparative study.

PubMed

Mujtaba, Ghulam; Shuib, Liyana; Raj, Ram Gopal; Rajandram, Retnagowri; Shaikh, Khairunisa

2018-07-01

Automatic text classification techniques are useful for classifying plaintext medical documents. This study aims to automatically predict the cause of death from free text forensic autopsy reports by comparing various schemes for feature extraction, term weighing or feature value representation, text classification, and feature reduction. For experiments, the autopsy reports belonging to eight different causes of death were collected, preprocessed and converted into 43 master feature vectors using various schemes for feature extraction, representation, and reduction. The six different text classification techniques were applied on these 43 master feature vectors to construct a classification model that can predict the cause of death. Finally, classification model performance was evaluated using four performance measures i.e. overall accuracy, macro precision, macro-F-measure, and macro recall. From experiments, it was found that that unigram features obtained the highest performance compared to bigram, trigram, and hybrid-gram features. Furthermore, in feature representation schemes, term frequency, and term frequency with inverse document frequency obtained similar and better results when compared with binary frequency, and normalized term frequency with inverse document frequency. Furthermore, the chi-square feature reduction approach outperformed Pearson correlation, and information gain approaches. Finally, in text classification algorithms, support vector machine classifier outperforms random forest, Naive Bayes, k-nearest neighbor, decision tree, and ensemble-voted classifier. Our results and comparisons hold practical importance and serve as references for future works. Moreover, the comparison outputs will act as state-of-art techniques to compare future proposals with existing automated text classification techniques. Copyright © 2017 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

Structural, electrical properties and dielectric relaxations in Na+-ion-conducting solid polymer electrolyte.

PubMed

Arya, Anil; Sharma, A L

2018-04-25

In this paper, we have studied the structural, microstructural, electrical, dielectric properties and ion dynamics of a sodium-ion-conducting solid polymer electrolyte film comprising PEO 8 -NaPF 6 +  x wt. % succinonitrile. The structural and surface morphology properties have been investigated, respectively using x-ray diffraction and field emission scanning electron microscopy. The complex formation was examined using Fourier transform infrared spectroscopy, and the fraction of free anions/ion pairs obtained via deconvolution. The complex dielectric permittivity and loss tangent has been analyzed across the whole frequency window, and enables us to estimate the DC conductivity, dielectric strength, double layer capacitance and relaxation time. The presence of relaxing dipoles was determined by the addition of succinonitrile (wt./wt.) and the peak shift towards high frequency indicates the decrease of relaxation time. Further, relations among various relaxation times ([Formula: see text]) have been elucidated. The complex conductivity has been examined across the whole frequency window; it obeys the Universal Power Law, and displays strong dependency on succinonitrile content. The sigma representation ([Formula: see text]) was introduced in order to explore the ion dynamics by highlighting the dispersion region in the Cole-Cole plot ([Formula: see text]) in the lower frequency window; increase in the semicircle radius indicates a decrease of relaxation time. This observation is accompanied by enhancement in ionic conductivity and faster ion transport. A convincing, logical scheme to justify the experimental data has been proposed.

Enhanced phase synchrony in the electroencephalograph γ band for musicians while listening to music

NASA Astrophysics Data System (ADS)

Bhattacharya, Joydeep; Petsche, Hellmuth

2001-07-01

Multichannel electroencephalograph signals from two broad groups, 10 musicians and 10 nonmusicians, recorded in different states (in resting states or no task condition, with eyes opened and eyes closed, and with two musical tasks, listening to two different pieces of music) were studied. Degrees of phase synchrony in various frequency bands were assessed. No differences in the degree of synchronization in any frequency band were found between the two groups in resting conditions. Yet, while listening to music, significant increases of synchronization were found only in the γ-frequency range (>30 Hz) over large cortical areas for the group of musicians. This high degree of synchronization elicited by music in the group of musicians might be due to their ability to host long-term memory representations of music and mediate access to these stored representations.

Perception of stochastically undersampled sound waveforms: a model of auditory deafferentation

PubMed Central

Lopez-Poveda, Enrique A.; Barrios, Pablo

2013-01-01

Auditory deafferentation, or permanent loss of auditory nerve afferent terminals, occurs after noise overexposure and aging and may accompany many forms of hearing loss. It could cause significant auditory impairment but is undetected by regular clinical tests and so its effects on perception are poorly understood. Here, we hypothesize and test a neural mechanism by which deafferentation could deteriorate perception. The basic idea is that the spike train produced by each auditory afferent resembles a stochastically digitized version of the sound waveform and that the quality of the waveform representation in the whole nerve depends on the number of aggregated spike trains or auditory afferents. We reason that because spikes occur stochastically in time with a higher probability for high- than for low-intensity sounds, more afferents would be required for the nerve to faithfully encode high-frequency or low-intensity waveform features than low-frequency or high-intensity features. Deafferentation would thus degrade the encoding of these features. We further reason that due to the stochastic nature of nerve firing, the degradation would be greater in noise than in quiet. This hypothesis is tested using a vocoder. Sounds were filtered through ten adjacent frequency bands. For the signal in each band, multiple stochastically subsampled copies were obtained to roughly mimic different stochastic representations of that signal conveyed by different auditory afferents innervating a given cochlear region. These copies were then aggregated to obtain an acoustic stimulus. Tone detection and speech identification tests were performed by young, normal-hearing listeners using different numbers of stochastic samplers per frequency band in the vocoder. Results support the hypothesis that stochastic undersampling of the sound waveform, inspired by deafferentation, impairs speech perception in noise more than in quiet, consistent with auditory aging effects. PMID:23882176

A spherical model for orientation and spatial-frequency tuning in a cortical hypercolumn.

PubMed Central

Bressloff, Paul C; Cowan, Jack D

2003-01-01

A theory is presented of the way in which the hypercolumns in primary visual cortex (V1) are organized to detect important features of visual images, namely local orientation and spatial-frequency. Given the existence in V1 of dual maps for these features, both organized around orientation pinwheels, we constructed a model of a hypercolumn in which orientation and spatial-frequency preferences are represented by the two angular coordinates of a sphere. The two poles of this sphere are taken to correspond, respectively, to high and low spatial-frequency preferences. In Part I of the paper, we use mean-field methods to derive exact solutions for localized activity states on the sphere. We show how cortical amplification through recurrent interactions generates a sharply tuned, contrast-invariant population response to both local orientation and local spatial frequency, even in the case of a weakly biased input from the lateral geniculate nucleus (LGN). A major prediction of our model is that this response is non-separable with respect to the local orientation and spatial frequency of a stimulus. That is, orientation tuning is weaker around the pinwheels, and there is a shift in spatial-frequency tuning towards that of the closest pinwheel at non-optimal orientations. In Part II of the paper, we demonstrate that a simple feed-forward model of spatial-frequency preference, unlike that for orientation preference, does not generate a faithful representation when amplified by recurrent interactions in V1. We then introduce the idea that cortico-geniculate feedback modulates LGN activity to generate a faithful representation, thus providing a new functional interpretation of the role of this feedback pathway. Using linear filter theory, we show that if the feedback from a cortical cell is taken to be approximately equal to the reciprocal of the corresponding feed-forward receptive field (in the two-dimensional Fourier domain), then the mismatch between the feed-forward and cortical frequency representations is eliminated. We therefore predict that cortico-geniculate feedback connections innervate the LGN in a pattern determined by the orientation and spatial-frequency biases of feed-forward receptive fields. Finally, we show how recurrent cortical interactions can generate cross-orientation suppression. PMID:14561324

Duration estimates within a modality are integrated sub-optimally

PubMed Central

Cai, Ming Bo; Eagleman, David M.

2015-01-01

Perceived duration can be influenced by various properties of sensory stimuli. For example, visual stimuli of higher temporal frequency are perceived to last longer than those of lower temporal frequency. How does the brain form a representation of duration when each of two simultaneously presented stimuli influences perceived duration in different way? To answer this question, we investigated the perceived duration of a pair of dynamic visual stimuli of different temporal frequencies in comparison to that of a single visual stimulus of either low or high temporal frequency. We found that the duration representation of simultaneously occurring visual stimuli is best described by weighting the estimates of duration based on each individual stimulus. However, the weighting performance deviates from the prediction of statistically optimal integration. In addition, we provided a Bayesian account to explain a difference in the apparent sensitivity of the psychometric curves introduced by the order in which the two stimuli are displayed in a two-alternative forced-choice task. PMID:26321965

The neural bases of spatial frequency processing during scene perception

PubMed Central

Kauffmann, Louise; Ramanoël, Stephen; Peyrin, Carole

2014-01-01

Theories on visual perception agree that scenes are processed in terms of spatial frequencies. Low spatial frequencies (LSF) carry coarse information whereas high spatial frequencies (HSF) carry fine details of the scene. However, how and where spatial frequencies are processed within the brain remain unresolved questions. The present review addresses these issues and aims to identify the cerebral regions differentially involved in low and high spatial frequency processing, and to clarify their attributes during scene perception. Results from a number of behavioral and neuroimaging studies suggest that spatial frequency processing is lateralized in both hemispheres, with the right and left hemispheres predominantly involved in the categorization of LSF and HSF scenes, respectively. There is also evidence that spatial frequency processing is retinotopically mapped in the visual cortex. HSF scenes (as opposed to LSF) activate occipital areas in relation to foveal representations, while categorization of LSF scenes (as opposed to HSF) activates occipital areas in relation to more peripheral representations. Concomitantly, a number of studies have demonstrated that LSF information may reach high-order areas rapidly, allowing an initial coarse parsing of the visual scene, which could then be sent back through feedback into the occipito-temporal cortex to guide finer HSF-based analysis. Finally, the review addresses spatial frequency processing within scene-selective regions areas of the occipito-temporal cortex. PMID:24847226

Time Domain Version of the Uniform Geometrical Theory of Diffraction

NASA Astrophysics Data System (ADS)

Rousseau, Paul R.

1995-01-01

A time domain (TD) version of the uniform geometrical theory of diffraction which is referred to as the TD-UTD is developed to analyze the transient electromagnetic scattering from perfectly conducting objects that are large in terms of pulse width. In particular, the scattering from a perfectly conducting arbitrary curved wedge and an arbitrary smooth convex surface are treated in detail. Note that the canonical geometries of a circular cylinder and a sphere are special cases of the arbitrary smooth convex surface. These TD -UTD solutions are obtained in the form of relatively simple analytical expressions valid for early to intermediate times. The geometries treated here can be used to build up a transient solution to more complex radiating objects via space-time localization, in exactly the same way as is done by invoking spatial localization properties in the frequency domain UTD. The TD-UTD provides the response due to an excitation of a general astigmatic impulsive wavefront with any polarization. This generalized impulse response may then be convolved with other excitation time pulses, to find even more general solutions due to other excitation pulses. Since the TD-UTD uses the same rays as the frequency domain UTD, it provides a simple picture for transient radiation or scattering and is therefore just as physically appealing as the frequency domain UTD. The formulation of an analytic time transform (ATT), which produces an analytic time signal given a frequency response function, is given here. This ATT is used because it provides a very efficient method of inverting the asymptotic high frequency UTD representations to obtain the corresponding TD-UTD expressions even when there are special UTD transition functions which may not be well behaved at the low frequencies; also, using the ATT avoids the difficulties associated with the inversion of UTD ray fields that traverse line or smooth caustics. Another useful aspect of the ATT is the ability to perform an efficient convolution with a broad class of excitation pulse functions, where the frequency response of the excitation function must be expressed as a summation of complex exponential functions.

Facilitatory Effects of Multi-Word Units in Lexical Processing and Word Learning: A Computational Investigation.

PubMed

Grimm, Robert; Cassani, Giovanni; Gillis, Steven; Daelemans, Walter

2017-01-01

Previous studies have suggested that children and adults form cognitive representations of co-occurring word sequences. We propose (1) that the formation of such multi-word unit (MWU) representations precedes and facilitates the formation of single-word representations in children and thus benefits word learning, and (2) that MWU representations facilitate adult word recognition and thus benefit lexical processing. Using a modified version of an existing computational model (McCauley and Christiansen, 2014), we extract MWUs from a corpus of child-directed speech (CDS) and a corpus of conversations among adults. We then correlate the number of MWUs within which each word appears with (1) age of first production and (2) adult reaction times on a word recognition task. In doing so, we take care to control for the effect of word frequency, as frequent words will naturally tend to occur in many MWUs. We also compare results to a baseline model which randomly groups words into sequences-and find that MWUs have a unique facilitatory effect on both response variables, suggesting that they benefit word learning in children and word recognition in adults. The effect is strongest on age of first production, implying that MWUs are comparatively more important for word learning than for adult lexical processing. We discuss possible underlying mechanisms and formulate testable predictions.

Facilitatory Effects of Multi-Word Units in Lexical Processing and Word Learning: A Computational Investigation

PubMed Central

Grimm, Robert; Cassani, Giovanni; Gillis, Steven; Daelemans, Walter

2017-01-01

Previous studies have suggested that children and adults form cognitive representations of co-occurring word sequences. We propose (1) that the formation of such multi-word unit (MWU) representations precedes and facilitates the formation of single-word representations in children and thus benefits word learning, and (2) that MWU representations facilitate adult word recognition and thus benefit lexical processing. Using a modified version of an existing computational model (McCauley and Christiansen, 2014), we extract MWUs from a corpus of child-directed speech (CDS) and a corpus of conversations among adults. We then correlate the number of MWUs within which each word appears with (1) age of first production and (2) adult reaction times on a word recognition task. In doing so, we take care to control for the effect of word frequency, as frequent words will naturally tend to occur in many MWUs. We also compare results to a baseline model which randomly groups words into sequences—and find that MWUs have a unique facilitatory effect on both response variables, suggesting that they benefit word learning in children and word recognition in adults. The effect is strongest on age of first production, implying that MWUs are comparatively more important for word learning than for adult lexical processing. We discuss possible underlying mechanisms and formulate testable predictions. PMID:28450842

Polar plot representation of time-resolved fluorescence.

PubMed

Eichorst, John Paul; Wen Teng, Kai; Clegg, Robert M

2014-01-01

Measuring changes in a molecule's fluorescence emission is a common technique to study complex biological systems such as cells and tissues. Although the steady-state fluorescence intensity is frequently used, measuring the average amount of time that a molecule spends in the excited state (the fluorescence lifetime) reveals more detailed information about its local environment. The lifetime is measured in the time domain by detecting directly the decay of fluorescence following excitation by short pulse of light. The lifetime can also be measured in the frequency domain by recording the phase and amplitude of oscillation in the emitted fluorescence of the sample in response to repetitively modulated excitation light. In either the time or frequency domain, the analysis of data to extract lifetimes can be computationally intensive. For example, a variety of iterative fitting algorithms already exist to determine lifetimes from samples that contain multiple fluorescing species. However, recently a method of analysis referred to as the polar plot (or phasor plot) is a graphical tool that projects the time-dependent features of the sample's fluorescence in either the time or frequency domain into the Cartesian plane to characterize the sample's lifetime. The coordinate transformations of the polar plot require only the raw data, and hence, there are no uncertainties from extensive corrections or time-consuming fitting in this analysis. In this chapter, the history and mathematical background of the polar plot will be presented along with examples that highlight how it can be used in both cuvette-based and imaging applications.

The Role of L1 Conceptual and Linguistic Knowledge and Frequency in the Acquisition of L2 Metaphorical Expressions

ERIC Educational Resources Information Center

Türker, Ebru

2016-01-01

This study investigates how figurative language is processed by learners of a second language (L2). With an experiment testing L2 comprehension of figurative expressions in three categories, each combining shared and unshared first language (L1) and L2 lexical representations and conceptual representations in a different way, the study…

Reference frames for spatial frequency in face representation differ in the temporal visual cortex and amygdala.

PubMed

Inagaki, Mikio; Fujita, Ichiro

2011-07-13

Social communication in nonhuman primates and humans is strongly affected by facial information from other individuals. Many cortical and subcortical brain areas are known to be involved in processing facial information. However, how the neural representation of faces differs across different brain areas remains unclear. Here, we demonstrate that the reference frame for spatial frequency (SF) tuning of face-responsive neurons differs in the temporal visual cortex and amygdala in monkeys. Consistent with psychophysical properties for face recognition, temporal cortex neurons were tuned to image-based SFs (cycles/image) and showed viewing distance-invariant representation of face patterns. On the other hand, many amygdala neurons were influenced by retina-based SFs (cycles/degree), a characteristic that is useful for social distance computation. The two brain areas also differed in the luminance contrast sensitivity of face-responsive neurons; amygdala neurons sharply reduced their responses to low luminance contrast images, while temporal cortex neurons maintained the level of their responses. From these results, we conclude that different types of visual processing in the temporal visual cortex and the amygdala contribute to the construction of the neural representations of faces.

Human Frequency Following Response: Neural Representation of Envelope and Temporal Fine Structure in Listeners with Normal Hearing and Sensorineural Hearing Loss

PubMed Central

Ananthakrishnan, Saradha; Krishnan, Ananthanarayan; Bartlett, Edward

2015-01-01

Objective Listeners with sensorineural hearing loss (SNHL) typically experience reduced speech perception, which is not completely restored with amplification. This likely occurs because cochlear damage, in addition to elevating audiometric thresholds, alters the neural representation of speech transmitted to higher centers along the auditory neuroaxis. While the deleterious effects of SNHL on speech perception in humans have been well-documented using behavioral paradigms, our understanding of the neural correlates underlying these perceptual deficits remains limited. Using the scalp-recorded Frequency Following Response (FFR), the authors examine the effects of SNHL and aging on subcortical neural representation of acoustic features important for pitch and speech perception, namely the periodicity envelope (F0) and temporal fine structure (TFS) (formant structure), as reflected in the phase-locked neural activity generating the FFR. Design FFRs were obtained from 10 listeners with normal hearing (NH) and 9 listeners with mild-moderate SNHL in response to a steady-state English back vowel /u/ presented at multiple intensity levels. Use of multiple presentation levels facilitated comparisons at equal sound pressure level (SPL) and equal sensation level (SL). In a second follow-up experiment to address the effect of age on envelope and TFS representation, FFRs were obtained from 25 NH and 19 listeners with mild to moderately-severe SNHL to the same vowel stimulus presented at 80 dB SPL. Temporal waveforms, Fast Fourier Transform (FFT) and spectrograms were used to evaluate the magnitude of the phase-locked activity at F0 (periodicity envelope) and F1 (TFS). Results Neural representation of both envelope (F0) and TFS (F1) at equal SPLs was stronger in NH listeners compared to listeners with SNHL. Also, comparison of neural representation of F0 and F1 across stimulus levels expressed in SPL and SL (accounting for audibility) revealed that level-related changes in F0 and F1 magnitude were different for listeners with SNHL compared to listeners with normal hearing. Further, the degradation in subcortical neural representation was observed to persist in listeners with SNHL even when the effects of age were controlled for. Conclusions Overall, our results suggest a relatively greater degradation in the neural representation of TFS compared to periodicity envelope in individuals with SNHL. This degraded neural representation of TFS in SNHL, as reflected in the brainstem FFR, may reflect a disruption in the temporal pattern of phase-locked neural activity arising from altered tonotopic maps and/or wider filters causing poor frequency selectivity in these listeners. Lastly, while preliminary results indicate that the deleterious effects of SNHL may be greater than age-related degradation in subcortical neural representation, the lack of a balanced age-matched control group in this study does not permit us to completely rule out the effects of age on subcortical neural representation. PMID:26583482

Spatial attention improves reliability of fMRI retinotopic mapping signals in occipital and parietal cortex

PubMed Central

Bressler, David W.; Silver, Michael A.

2010-01-01

Spatial attention improves visual perception and increases the amplitude of neural responses in visual cortex. In addition, spatial attention tasks and fMRI have been used to discover topographic visual field representations in regions outside visual cortex. We therefore hypothesized that requiring subjects to attend to a retinotopic mapping stimulus would facilitate the characterization of visual field representations in a number of cortical areas. In our study, subjects attended either a central fixation point or a wedge-shaped stimulus that rotated about the fixation point. Response reliability was assessed by computing coherence between the fMRI time series and a sinusoid with the same frequency as the rotating wedge stimulus. When subjects attended to the rotating wedge instead of ignoring it, the reliability of retinotopic mapping signals increased by approximately 50% in early visual cortical areas (V1, V2, V3, V3A/B, V4) and ventral occipital cortex (VO1) and by approximately 75% in lateral occipital (LO1, LO2) and posterior parietal (IPS0, IPS1 and IPS2) cortical areas. Additionally, one 5-minute run of retinotopic mapping in the attention-to-wedge condition produced responses as reliable as the average of three to five (early visual cortex) or more than five (lateral occipital, ventral occipital, and posterior parietal cortex) attention-to-fixation runs. These results demonstrate that allocating attention to the retinotopic mapping stimulus substantially reduces the amount of scanning time needed to determine the visual field representations in occipital and parietal topographic cortical areas. Attention significantly increased response reliability in every cortical area we examined and may therefore be a general mechanism for improving the fidelity of neural representations of sensory stimuli at multiple levels of the cortical processing hierarchy. PMID:20600961

Changes in auditory nerve responses across the duration of sinusoidally amplitude-modulated electric pulse-train stimuli.

PubMed

Hu, Ning; Miller, Charles A; Abbas, Paul J; Robinson, Barbara K; Woo, Jihwan

2010-12-01

Response rates of auditory nerve fibers (ANFs) to electric pulse trains change over time, reflecting substantial spike-rate adaptation that depends on stimulus parameters. We hypothesize that adaptation affects the representation of amplitude-modulated pulse trains used by cochlear prostheses to transmit speech information to the auditory system. We recorded cat ANF responses to sinusoidally amplitude-modulated (SAM) trains with 5,000 pulse/s carriers. Stimuli delivered by a monopolar intracochlear electrode had fixed modulation frequency (100 Hz) and depth (10%). ANF responses were assessed by spike-rate measures, while representation of modulation was evaluated by vector strength (VS) and the fundamental component of the fast Fourier transform (F(0) amplitude). These measures were assessed across the 400 ms duration of pulse-train stimuli, a duration relevant to speech stimuli. Different stimulus levels were explored and responses were categorized into four spike-rate groups to assess level effects across ANFs. The temporal pattern of rate adaptation to modulated trains was similar to that of unmodulated trains, but with less rate adaptation. VS to the modulator increased over time and tended to saturate at lower spike rates, while F(0) amplitude typically decreased over time for low driven rates and increased for higher driven rates. VS at moderate and high spike rates and degree of F(0) amplitude temporal changes at low and moderate spike rates were positively correlated with the degree of rate adaptation. Thus, high-rate carriers will modify the ANF representation of the modulator over time. As the VS and F(0) measures were sensitive to adaptation-related changes over different spike-rate ranges, there is value in assessing both measures.

Heating-frequency-dependent thermal conductivity: An analytical solution from diffusive to ballistic regime and its relevance to phonon scattering measurements

NASA Astrophysics Data System (ADS)

Yang, Fan; Dames, Chris

2015-04-01

The heating-frequency dependence of the apparent thermal conductivity in a semi-infinite body with periodic planar surface heating is explained by an analytical solution to the Boltzmann transport equation. This solution is obtained using a two-flux model and gray mean free time approximation and verified numerically with a lattice Boltzmann method and numerical results from the literature. Extending the gray solution to the nongray regime leads to an integral transform and accumulation-function representation of the phonon scattering spectrum, where the natural variable is mean free time rather than mean free path, as often used in previous work. The derivation leads to an approximate cutoff conduction similar in spirit to that of Koh and Cahill [Phys. Rev. B 76, 075207 (2007), 10.1103/PhysRevB.76.075207] except that the most appropriate criterion involves the heater frequency rather than thermal diffusion length. The nongray calculations are consistent with Koh and Cahill's experimental observation that the apparent thermal conductivity shows a stronger heater-frequency dependence in a SiGe alloy than in natural Si. Finally these results are demonstrated using a virtual experiment, which fits the phase lag between surface temperature and heat flux to obtain the apparent thermal conductivity and accumulation function.

A test of the orthographic recoding hypothesis

NASA Astrophysics Data System (ADS)

Gaygen, Daniel E.

2003-04-01

The Orthographic Recoding Hypothesis [D. E. Gaygen and P. A. Luce, Percept. Psychophys. 60, 465-483 (1998)] was tested. According to this hypothesis, listeners recognize spoken words heard for the first time by mapping them onto stored representations of the orthographic forms of the words. Listeners have a stable orthographic representation of words, but no phonological representation, when those words have been read frequently but never heard or spoken. Such may be the case for low frequency words such as jargon. Three experiments using visually and auditorily presented nonword stimuli tested this hypothesis. The first two experiments were explicit tests of memory (old-new tests) for words presented visually. In the first experiment, the recognition of auditorily presented nonwords was facilitated when they previously appeared on a visually presented list. The second experiment was similar, but included a concurrent articulation task during a visual word list presentation, thus preventing covert rehearsal of the nonwords. The results were similar to the first experiment. The third experiment was an indirect test of memory (auditory lexical decision task) for visually presented nonwords. Auditorily presented nonwords were identified as nonwords significantly more slowly if they had previously appeared on the visually presented list accompanied by a concurrent articulation task.

Spacetime representation of topological phononics

NASA Astrophysics Data System (ADS)

Deymier, Pierre A.; Runge, Keith; Lucas, Pierre; Vasseur, Jérôme O.

2018-05-01

Non-conventional topology of elastic waves arises from breaking symmetry of phononic structures either intrinsically through internal resonances or extrinsically via application of external stimuli. We develop a spacetime representation based on twistor theory of an intrinsic topological elastic structure composed of a harmonic chain attached to a rigid substrate. Elastic waves in this structure obey the Klein–Gordon and Dirac equations and possesses spinorial character. We demonstrate the mapping between straight line trajectories of these elastic waves in spacetime and the twistor complex space. The twistor representation of these Dirac phonons is related to their topological and fermion-like properties. The second topological phononic structure is an extrinsic structure composed of a one-dimensional elastic medium subjected to a moving superlattice. We report an analogy between the elastic behavior of this time-dependent superlattice, the scalar quantum field theory and general relativity of two types of exotic particle excitations, namely temporal Dirac phonons and temporal ghost (tachyonic) phonons. These phonons live on separate sides of a two-dimensional frequency space and are delimited by ghost lines reminiscent of the conventional light cone. Both phonon types exhibit spinorial amplitudes that can be measured by mapping the particle behavior to the band structure of elastic waves.

Impact of initial pulse shape on the nonlinear spectral compression in optical fibre

NASA Astrophysics Data System (ADS)

Boscolo, Sonia; Chaussard, Frederic; Andresen, Esben; Rigneault, Hervé; Finot, Christophe

2018-02-01

We theoretically study the effects of the temporal intensity profile of the initial pulse on the nonlinear propagation spectral compression process arising from nonlinear propagation in an optical fibre. Various linearly chirped input pulse profiles are considered, and their dynamics is explained with the aid of time-frequency representations. While initially parabolic-shaped pulses show enhanced spectral compression compared to Gaussian pulses, no significant spectral narrowing occurs when initially super-Gaussian pulses are used. Triangular pulses lead to a spectral interference phenomenon similar to the Fresnel bi-prism experiment.

Scattering of ultrasonic wave by cracks in a plate

NASA Technical Reports Server (NTRS)

Liu, S. W.; Datta, S. K.

1993-01-01

A hybrid numerical method combining finite elements and the boundary integral representation is used to investigate the transient scattering of ultrasonic waves by a crack in a plate. The incident wave models the guided waves generated by a steel ball impact on the plate. Two surface-breaking cracks and one subsurface crack are studied here. The results show that the location and depth of cracks have measurable effects on the surface responses in time and frequency domains. Also, the scattered fields have distinct differences in the three cases.

Visual stimulus eccentricity affects human gamma peak frequency.

PubMed

van Pelt, Stan; Fries, Pascal

2013-09-01

The peak frequency of neuronal gamma-band synchronization has received much attention in recent years. Gamma peak frequency shifts to higher frequency values for higher contrast, faster moving, and attended stimuli. In monkey V1, gamma peak frequency for a drifting grating is higher for a parafoveal as compared to an eccentric stimulus (Lima et al., 2010). This effect might be due to the cortical magnification factor: the higher cortical magnification for parafoveal stimuli increases the velocity with which the cortical representations of the moving grating stripes move across the cortical surface. Since faster moving stimuli lead to higher gamma frequency, a faster moving cortical representation might do the same. This explanation predicts that the eccentricity effect on gamma peak frequency is absent for stationary stimuli. To test this, we investigated the effect of eccentricity on gamma peak frequency by recording magnetoencephalography in human subjects while they viewed moving or stationary gratings. We found that both the moving and the stationary stimuli induced lower peak frequencies for larger eccentricities, arguing against an explanation based on the cortical magnification factor. We further investigated whether this eccentricity effect was explained by differences in the size or the spatial frequency of the expected cortical activation. Neither of those explained the eccentricity effect. We propose that the different stimulus and top-down factors leading to higher gamma peak frequency all result in higher stimulus salience, that salience is translated into gamma peak frequency, and that gamma peak frequency might subserve the preferential processing of neuronal activity induced by salient stimuli. Copyright © 2013 Elsevier Inc. All rights reserved.

Post-amputation pain is associated with the recall of an impaired body representation in dreams-results from a nation-wide survey on limb amputees.

PubMed

Bekrater-Bodmann, Robin; Schredl, Michael; Diers, Martin; Reinhard, Iris; Foell, Jens; Trojan, Jörg; Fuchs, Xaver; Flor, Herta

2015-01-01

The experience of post-amputation pain such as phantom limb pain (PLP) and residual limb pain (RLP), is a common consequence of limb amputation, and its presence has negative effects on a person's well-being. The continuity hypothesis of dreams suggests that the presence of such aversive experiences in the waking state should be reflected in dream content, with the recalled body representation reflecting a cognitive proxy of negative impact. In the present study, we epidemiologically assessed the presence of post-amputation pain and other amputation-related information as well as recalled body representation in dreams in a sample of 3,234 unilateral limb amputees. Data on the site and time of amputation, residual limb length, prosthesis use, lifetime prevalence of mental disorders, presence of post-amputation pain, and presence of non-painful phantom phenomena were included in logistic regression analyses using recalled body representation in dreams (impaired, intact, no memory) as dependent variable. The effects of age, sex, and frequency of dream recall were controlled for. About 22% of the subjects indicated that they were not able to remember their body representation in dreams, another 24% of the amputees recalled themselves as always intact, and only a minority of less than 3% recalled themselves as always impaired. Almost 35% of the amputees dreamed of themselves in a mixed fashion. We found that lower-limb amputation as well as the presence of PLP and RLP was positively associated with the recall of an impaired body representation in dreams. The presence of non-painful phantom phenomena, however, had no influence. These results complement previous findings and indicate complex interactions of physical body appearance and mental body representation, probably modulated by distress in the waking state. The findings are discussed against the background of alterations in cognitive processes after amputation and hypotheses suggesting an innate body model.

Post-Amputation Pain Is Associated with the Recall of an Impaired Body Representation in Dreams—Results from a Nation-Wide Survey on Limb Amputees

PubMed Central

Bekrater-Bodmann, Robin; Schredl, Michael; Diers, Martin; Reinhard, Iris; Foell, Jens; Trojan, Jörg; Fuchs, Xaver; Flor, Herta

2015-01-01

The experience of post-amputation pain such as phantom limb pain (PLP) and residual limb pain (RLP), is a common consequence of limb amputation, and its presence has negative effects on a person’s well-being. The continuity hypothesis of dreams suggests that the presence of such aversive experiences in the waking state should be reflected in dream content, with the recalled body representation reflecting a cognitive proxy of negative impact. In the present study, we epidemiologically assessed the presence of post-amputation pain and other amputation-related information as well as recalled body representation in dreams in a sample of 3,234 unilateral limb amputees. Data on the site and time of amputation, residual limb length, prosthesis use, lifetime prevalence of mental disorders, presence of post-amputation pain, and presence of non-painful phantom phenomena were included in logistic regression analyses using recalled body representation in dreams (impaired, intact, no memory) as dependent variable. The effects of age, sex, and frequency of dream recall were controlled for. About 22% of the subjects indicated that they were not able to remember their body representation in dreams, another 24% of the amputees recalled themselves as always intact, and only a minority of less than 3% recalled themselves as always impaired. Almost 35% of the amputees dreamed of themselves in a mixed fashion. We found that lower-limb amputation as well as the presence of PLP and RLP was positively associated with the recall of an impaired body representation in dreams. The presence of non-painful phantom phenomena, however, had no influence. These results complement previous findings and indicate complex interactions of physical body appearance and mental body representation, probably modulated by distress in the waking state. The findings are discussed against the background of alterations in cognitive processes after amputation and hypotheses suggesting an innate body model. PMID:25742626

Brain reflections: A circuit-based framework for understanding information processing and cognitive control.

PubMed

Gratton, Gabriele

2018-03-01

Here, I propose a view of the architecture of the human information processing system, and of how it can be adapted to changing task demands (which is the hallmark of cognitive control). This view is informed by an interpretation of brain activity as reflecting the excitability level of neural representations, encoding not only stimuli and temporal contexts, but also action plans and task goals. The proposed cognitive architecture includes three types of circuits: open circuits, involved in feed-forward processing such as that connecting stimuli with responses and characterized by brief, transient brain activity; and two types of closed circuits, positive feedback circuits (characterized by sustained, high-frequency oscillatory activity), which help select and maintain representations, and negative feedback circuits (characterized by brief, low-frequency oscillatory bursts), which are instead associated with changes in representations. Feed-forward activity is primarily responsible for the spread of activation along the information processing system. Oscillatory activity, instead, controls this spread. Sustained oscillatory activity due to both local cortical circuits (gamma) and longer corticothalamic circuits (alpha and beta) allows for the selection of individuated representations. Through the interaction of these circuits, it also allows for the preservation of representations across different temporal spans (sensory and working memory) and their spread across the brain. In contrast, brief bursts of oscillatory activity, generated by novel and/or conflicting information, lead to the interruption of sustained oscillatory activity and promote the generation of new representations. I discuss how this framework can account for a number of psychological and behavioral phenomena. © 2017 Society for Psychophysiological Research.

Time-dependent local-to-normal mode transition in triatomic molecules

NASA Astrophysics Data System (ADS)

Cruz, Hans; Bermúdez-Montaña, Marisol; Lemus, Renato

2018-01-01

Time-evolution of the vibrational states of two interacting harmonic oscillators in the local mode scheme is presented. A local-to-normal mode transition (LNT) is identified and studied from temporal perspective through time-dependent frequencies of the oscillators. The LNT is established as a polyad-breaking phenomenon from the local standpoint for the stretching degrees of freedom in a triatomic molecule. This study is carried out in the algebraic representation of bosonic operators. The dynamics of the states are determined via the solutions of the corresponding nonlinear Ermakov equation and a local time-dependent polyad is obtained as a tool to identify the LNT. Applications of this formalism to H2O, CO2, O3 and NO2 molecules in the adiabatic, sudden and linear regime are considered.

Frequency dispersion of sound propagation in Rouse polymer melts via generalized dynamic random phase approximation.

PubMed

Erukhimovich, I Ya; Kudryavtsev, Ya V

2003-08-01

An extended generalization of the dynamic random phase approximation (DRPA) for L-component polymer systems is presented. Unlike the original version of the DRPA, which relates the (LxL) matrices of the collective density-density time correlation functions and the corresponding susceptibilities of concentrated polymer systems to those of the tracer macromolecules and so-called broken-links system (BLS), our generalized DRPA solves this problem for the (5xL) x (5xL) matrices of the coupled susceptibilities and time correlation functions of the component number, kinetic energy and flux densities. The presented technique is used to study propagation of sound and dynamic form-factor in disentangled (Rouse) monodisperse homopolymer melt. The calculated ultrasonic velocity and absorption coefficient reveal substantial frequency dispersion. The relaxation time tau is proportional to the degree of polymerization N, which is N times less than the Rouse time and evidences strong dynamic screening because of interchain interaction. We discuss also some peculiarities of the Brillouin scattering in polymer melts. Besides, a new convenient expression for the dynamic structure function of the single Rouse chain in (q,p) representation is found.

Assessing the utility of frequency tagging for tracking memory-based reactivation of word representations.

PubMed

Lewis, Ashley Glen; Schriefers, Herbert; Bastiaansen, Marcel; Schoffelen, Jan-Mathijs

2018-05-21

Reinstatement of memory-related neural activity measured with high temporal precision potentially provides a useful index for real-time monitoring of the timing of activation of memory content during cognitive processing. The utility of such an index extends to any situation where one is interested in the (relative) timing of activation of different sources of information in memory, a paradigm case of which is tracking lexical activation during language processing. Essential for this approach is that memory reinstatement effects are robust, so that their absence (in the average) definitively indicates that no lexical activation is present. We used electroencephalography to test the robustness of a reported subsequent memory finding involving reinstatement of frequency-specific entrained oscillatory brain activity during subsequent recognition. Participants learned lists of words presented on a background flickering at either 6 or 15 Hz to entrain a steady-state brain response. Target words subsequently presented on a non-flickering background that were correctly identified as previously seen exhibited reinstatement effects at both entrainment frequencies. Reliability of these statistical inferences was however critically dependent on the approach used for multiple comparisons correction. We conclude that effects are not robust enough to be used as a reliable index of lexical activation during language processing.

The seasonal predictability of blocking frequency in two seasonal prediction systems (CMCC, Met-Office) and the associated representation of low-frequency variability.

NASA Astrophysics Data System (ADS)

Athanasiadis, Panos; Gualdi, Silvio; Scaife, Adam A.; Bellucci, Alessio; Hermanson, Leon; MacLachlan, Craig; Arribas, Alberto; Materia, Stefano; Borelli, Andrea

2014-05-01

Low-frequency variability is a fundamental component of the atmospheric circulation. Extratropical teleconnections, the occurrence of blocking and the slow modulation of the jet streams and storm tracks are all different aspects of low-frequency variability. Part of the latter is attributed to the chaotic nature of the atmosphere and is inherently unpredictable. On the other hand, primarily as a response to boundary forcings, tropospheric low-frequency variability includes components that are potentially predictable. Seasonal forecasting faces the difficult task of predicting these components. Particularly referring to the extratropics, the current generation of seasonal forecasting systems seem to be approaching this target by realistically initializing most components of the climate system, using higher resolution and utilizing large ensemble sizes. Two seasonal prediction systems (Met-Office GloSea and CMCC-SPS-v1.5) are analyzed in terms of their representation of different aspects of extratropical low-frequency variability. The current operational Met-Office system achieves unprecedented high scores in predicting the winter-mean phase of the North Atlantic Oscillation (NAO, corr. 0.74 at 500 hPa) and the Pacific-N. American pattern (PNA, corr. 0.82). The CMCC system, considering its small ensemble size and course resolution, also achieves good scores (0.42 for NAO, 0.51 for PNA). Despite these positive features, both models suffer from biases in low-frequency variance, particularly in the N. Atlantic. Consequently, it is found that their intrinsic variability patterns (sectoral EOFs) differ significantly from the observed, and the known teleconnections are underrepresented. Regarding the representation of N. hemisphere blocking, after bias correction both systems exhibit a realistic climatology of blocking frequency. In this assessment, instantaneous blocking and large-scale persistent blocking events are identified using daily geopotential height fields at 500 hPa. Given a documented strong relationship between high-latitude N. Atlantic blocking and the NAO, one would expect a predictive skill for the seasonal frequency of blocking comparable to that of the NAO. However, this remains elusive. Future efforts should be in the direction of reducing model biases not only in the mean but also in variability (band-passed variances).

Casimir and Casimir-Polder forces with dissipation from first principles

NASA Astrophysics Data System (ADS)

Bordag, M.

2017-12-01

We consider Casimir-Polder and Casimir forces with finite dissipation by coupling heat baths to the dipoles introducing, this way, dissipation from first principles. We derive a representation of the free energy as an integral over real frequencies, which can be viewed as an generalization of the remarkable formula introduced by Ford et al. [Phys. Rev. Lett. 55, 2273 (1985), 10.1103/PhysRevLett.55.2273]. For instance, we obtain a nonperturbative representation for the atom-atom and atom-wall interactions. We investigate several limiting cases. From the limit T →0 we show that the third law of thermodynamics cannot be violated within the given approach, where the dissipation parameter cannot depend on temperature by construction. We conclude that the given approach is insufficient to resolve the thermodynamic puzzle connected with the Drude model when inserted into the Lifshitz formula. Further, we consider the transition to the Matsubara representation and discuss modifications of the contribution from the zeroth Matsubara frequency.

Hippocampal Theta-Gamma Coupling Reflects State-Dependent Information Processing in Decision Making.

PubMed

Amemiya, Seiichiro; Redish, A David

2018-03-20

During decision making, hippocampal activity encodes information sometimes about present and sometimes about potential future plans. The mechanisms underlying this transition remain unknown. Building on the evidence that gamma oscillations at different frequencies (low gamma [LG], 30-55 Hz; high gamma [HG], 60-90 Hz; and epsilon, 100-140 Hz) reflect inputs from different circuits, we identified how changes in those frequencies reflect different information-processing states. Using a unique noradrenergic manipulation by clonidine, which shifted both neural representations and gamma states, we found that future representations depended on gamma components. These changes were identifiable on each cycle of theta as asymmetries in the theta cycle, which arose from changes within the ratio of LG and HG power and the underlying phases of those gamma rhythms within the theta cycle. These changes in asymmetry of the theta cycle reflected changes in representations of present and future on each theta cycle. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

Mechanisms Underlying Selective Neuronal Tracking of Attended Speech at a ‘Cocktail Party’

PubMed Central

Zion Golumbic, Elana M.; Ding, Nai; Bickel, Stephan; Lakatos, Peter; Schevon, Catherine A.; McKhann, Guy M.; Goodman, Robert R.; Emerson, Ronald; Mehta, Ashesh D.; Simon, Jonathan Z.; Poeppel, David; Schroeder, Charles E.

2013-01-01

Summary The ability to focus on and understand one talker in a noisy social environment is a critical social-cognitive capacity, whose underlying neuronal mechanisms are unclear. We investigated the manner in which speech streams are represented in brain activity and the way that selective attention governs the brain’s representation of speech using a ‘Cocktail Party’ Paradigm, coupled with direct recordings from the cortical surface in surgical epilepsy patients. We find that brain activity dynamically tracks speech streams using both low frequency phase and high frequency amplitude fluctuations, and that optimal encoding likely combines the two. In and near low level auditory cortices, attention ‘modulates’ the representation by enhancing cortical tracking of attended speech streams, but ignored speech remains represented. In higher order regions, the representation appears to become more ‘selective,’ in that there is no detectable tracking of ignored speech. This selectivity itself seems to sharpen as a sentence unfolds. PMID:23473326

Signal analysis by means of time-frequency (Wigner-type) distributions -- Applications to sonar and radar echoes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gaunaurd, G.; Strifors, H.C.

1996-09-01

Time series data have been traditionally analyzed in either the time or the frequency domains. For signals with a time-varying frequency content, the combined time-frequency (TF) representations, based on the Cohen class of (generalized) Wigner distributions (WD`s) offer a powerful analysis tool. Using them, it is possible to: (1) trace the time-evolution of the resonance features usually present in a standard sonar cross section (SCS), or in a radar cross section (RCS) and (2) extract target information that may be difficult to even notice in an ordinary SCS or RCS. After a brief review of the fundamental properties of themore » WD, the authors discuss ways to reduce or suppress the cross term interference that appears in the WD of multicomponent systems. These points are illustrated with a variety of three-dimensional (3-D) plots of Wigner and pseudo-Wigner distributions (PWD), in which the strength of the distribution is depicted as the height of a Wigner surface with height scales measured by various color shades or pseudocolors. The authors also review studies they have made of the echoes returned by conducting or dielectric targets in the atmosphere, when they are illuminated by broadband radar pings. A TF domain analysis of these impulse radar returns demonstrates their superior informative content. These plots allow the identification of targets in an easier and clearer fashion than by the conventional RCS of narrowband systems. The authors show computed and measured plots of WD and PWD of various types of aircraft to illustrate the classification advantages of the approach at any aspect angle. They also show analogous results for metallic objects buried underground, in dielectric media, at various depths.« less

Decoding Face Information in Time, Frequency and Space from Direct Intracranial Recordings of the Human Brain

PubMed Central

Oya, Hiroyuki; Howard, Matthew A.; Adolphs, Ralph

2008-01-01

Faces are processed by a neural system with distributed anatomical components, but the roles of these components remain unclear. A dominant theory of face perception postulates independent representations of invariant aspects of faces (e.g., identity) in ventral temporal cortex including the fusiform gyrus, and changeable aspects of faces (e.g., emotion) in lateral temporal cortex including the superior temporal sulcus. Here we recorded neuronal activity directly from the cortical surface in 9 neurosurgical subjects undergoing epilepsy monitoring while they viewed static and dynamic facial expressions. Applying novel decoding analyses to the power spectrogram of electrocorticograms (ECoG) from over 100 contacts in ventral and lateral temporal cortex, we found better representation of both invariant and changeable aspects of faces in ventral than lateral temporal cortex. Critical information for discriminating faces from geometric patterns was carried by power modulations between 50 to 150 Hz. For both static and dynamic face stimuli, we obtained a higher decoding performance in ventral than lateral temporal cortex. For discriminating fearful from happy expressions, critical information was carried by power modulation between 60–150 Hz and below 30 Hz, and again better decoded in ventral than lateral temporal cortex. Task-relevant attention improved decoding accuracy more than10% across a wide frequency range in ventral but not at all in lateral temporal cortex. Spatial searchlight decoding showed that decoding performance was highest around the middle fusiform gyrus. Finally, we found that the right hemisphere, in general, showed superior decoding to the left hemisphere. Taken together, our results challenge the dominant model for independent face representation of invariant and changeable aspects: information about both face attributes was better decoded from a single region in the middle fusiform gyrus. PMID:19065268

Native language shapes automatic neural processing of speech.

PubMed

Intartaglia, Bastien; White-Schwoch, Travis; Meunier, Christine; Roman, Stéphane; Kraus, Nina; Schön, Daniele

2016-08-01

The development of the phoneme inventory is driven by the acoustic-phonetic properties of one's native language. Neural representation of speech is known to be shaped by language experience, as indexed by cortical responses, and recent studies suggest that subcortical processing also exhibits this attunement to native language. However, most work to date has focused on the differences between tonal and non-tonal languages that use pitch variations to convey phonemic categories. The aim of this cross-language study is to determine whether subcortical encoding of speech sounds is sensitive to language experience by comparing native speakers of two non-tonal languages (French and English). We hypothesized that neural representations would be more robust and fine-grained for speech sounds that belong to the native phonemic inventory of the listener, and especially for the dimensions that are phonetically relevant to the listener such as high frequency components. We recorded neural responses of American English and French native speakers, listening to natural syllables of both languages. Results showed that, independently of the stimulus, American participants exhibited greater neural representation of the fundamental frequency compared to French participants, consistent with the importance of the fundamental frequency to convey stress patterns in English. Furthermore, participants showed more robust encoding and more precise spectral representations of the first formant when listening to the syllable of their native language as compared to non-native language. These results align with the hypothesis that language experience shapes sensory processing of speech and that this plasticity occurs as a function of what is meaningful to a listener. Copyright © 2016 Elsevier Ltd. All rights reserved.

Beyond Capacity Limitations: Determinants of Word Recall Performance on Verbal Working Memory Span Tasks in Children With SLI

PubMed Central

Mainela-Arnold, Elina; Evans, Julia L.

2016-01-01

Reduced verbal working memory capacity has been proposed as a possible account of language impairments in specific language impairment (SLI). Studies have shown, however, that differences in strength of linguistic representations in the form of word frequency affect list recall and performance on verbal working memory tasks. This suggests that verbal memory capacity and long-term linguistic knowledge may not be distinct constructs. It has been suggested that linguistic representations in SLI are weak in ways that result in a breakdown in language processing on tasks that require manipulation of unfamiliar material. In this study, the effects of word frequency, long-term linguistic knowledge, and serial order position on recall performance in the competing language processing task (CLPT) were investigated in 10 children with SLI and 10 age-matched peers (age 8 years 6 months to 12 years 4 months). The children with SLI recalled significantly fewer target words on the CLPT as compared with their age-matched controls. The SLI group did not differ, however, in their ability to recall target words having high word frequency but were significantly poorer in their ability to recall words on the CLPT having low word frequency. Differences in receptive and expressive language abilities also appeared closely related to performance on the CLPT, suggesting that working memory capacity is not distinct from language knowledge and that degraded linguistic representations may have an effect on performance on verbal working memory span tasks in children with SLI. PMID:16378481

Daily water and sediment discharges from selected rivers of the eastern United States; a time-series modeling approach

USGS Publications Warehouse

Fitzgerald, Michael G.; Karlinger, Michael R.

1983-01-01

Time-series models were constructed for analysis of daily runoff and sediment discharge data from selected rivers of the Eastern United States. Logarithmic transformation and first-order differencing of the data sets were necessary to produce second-order, stationary time series and remove seasonal trends. Cyclic models accounted for less than 42 percent of the variance in the water series and 31 percent in the sediment series. Analysis of the apparent oscillations of given frequencies occurring in the data indicates that frequently occurring storms can account for as much as 50 percent of the variation in sediment discharge. Components of the frequency analysis indicate that a linear representation is reasonable for the water-sediment system. Models that incorporate lagged water discharge as input prove superior to univariate techniques in modeling and prediction of sediment discharges. The random component of the models includes errors in measurement and model hypothesis and indicates no serial correlation. An index of sediment production within or between drain-gage basins can be calculated from model parameters.

Classification of the intention to generate a shoulder versus elbow torque by means of a time frequency synthesized spatial patterns BCI algorithm

NASA Astrophysics Data System (ADS)

Deng, Jie; Yao, Jun; Dewald, Julius P. A.

2005-12-01

In this paper, we attempt to determine a subject's intention of generating torque at the shoulder or elbow, two neighboring joints, using scalp electroencephalogram signals from 163 electrodes for a brain-computer interface (BCI) application. To achieve this goal, we have applied a time-frequency synthesized spatial patterns (TFSP) BCI algorithm with a presorting procedure. Using this method, we were able to achieve an average recognition rate of 89% in four healthy subjects, which is comparable to the highest rates reported in the literature but now for tasks with much closer spatial representations on the motor cortex. This result demonstrates, for the first time, that the TFSP BCI method can be applied to separate intentions between generating static shoulder versus elbow torque. Furthermore, in this study, the potential application of this BCI algorithm for brain-injured patients was tested in one chronic hemiparetic stroke subject. A recognition rate of 76% was obtained, suggesting that this BCI method can provide a potential control signal for neural prostheses or other movement coordination improving devices for patients following brain injury.

Heat conductivity in graphene and related materials: A time-domain modal analysis

NASA Astrophysics Data System (ADS)

Gill-Comeau, Maxime; Lewis, Laurent J.

2015-11-01

We use molecular dynamics (MD) simulations to study heat conductivity in single-layer graphene and graphite. We analyze the MD trajectories through a time-domain modal analysis and show that this is essential for obtaining a reliable representation of the heat flow in graphene and graphite as it permits the proper treatment of collective vibrational excitations, in contrast to a frequency-domain formulation. Our temperature-dependent results are in very good agreement with experiment and, for temperatures in the range 300-1200 K, we find that the ZA branch allows more heat flow than all other branches combined while the contributions of the TA, LA, and ZO branches are comparable at all temperatures. Conductivity mappings reveal strong collective excitations associated with low-frequency ZA modes. We demonstrate that these collective effects are a consequence of the quadratic nature of the ZA branch as they also show up in graphite but are reduced in strained graphene, where the dispersion becomes linear, and are absent in diamond, where acoustic branches are linear. In general, neglecting collective excitations yields errors similar to those from the single-mode relaxation-time approximation.

Contrast in Terahertz Images of Archival Documents—Part II: Influence of Topographic Features

NASA Astrophysics Data System (ADS)

Bardon, Tiphaine; May, Robert K.; Taday, Philip F.; Strlič, Matija

2017-04-01

We investigate the potential of terahertz time-domain imaging in reflection mode to reveal archival information in documents in a non-invasive way. In particular, this study explores the parameters and signal processing tools that can be used to produce well-contrasted terahertz images of topographic features commonly found in archival documents, such as indentations left by a writing tool, as well as sieve lines. While the amplitude of the waveforms at a specific time delay can provide the most contrasted and legible images of topographic features on flat paper or parchment sheets, this parameter may not be suitable for documents that have a highly irregular surface, such as water- or fire-damaged documents. For analysis of such documents, cross-correlation of the time-domain signals can instead yield images with good contrast. Analysis of the frequency-domain representation of terahertz waveforms can also provide well-contrasted images of topographic features, with improved spatial resolution when utilising high-frequency content. Finally, we point out some of the limitations of these means of analysis for extracting information relating to topographic features of interest from documents.

Representations and uses of light distribution functions

NASA Astrophysics Data System (ADS)

Lalonde, Paul Albert

1998-11-01

At their lowest level, all rendering algorithms depend on models of local illumination to define the interplay of light with the surfaces being rendered. These models depend both on the representations of light scattering at a surface due to reflection and to an equal extent on the representation of light sources and light fields. Both emission and reflection have in common that they describe how light leaves a surface as a function of direction. Reflection also depends on an incident light direction. Emission can depend on the position on the light source We call the functions representing emission and reflection light distribution functions (LDF's). There are some difficulties to using measured light distribution functions. The data sets are very large-the size of the data grows with the fourth power of the sampling resolution. For example, a bidirectional reflectance distribution function (BRDF) sampled at five degrees angular resolution, which is arguably insufficient to capture highlights and other high frequency effects in the reflection, can easily require one and a half million samples. Once acquired this data requires some form of interpolation to use them. Any compression method used must be efficient, both in space and in the time required to evaluate the function at a point or over a range of points. This dissertation examines a wavelet representation of light distribution functions that addresses these issues. A data structure is presented that allows efficient reconstruction of LDFs for a given set of parameters, making the wavelet representation feasible for rendering tasks. Texture mapping methods that take advantage of our LDF representations are examined, as well as techniques for filtering LDFs, and methods for using wavelet compressed bidirection reflectance distribution functions (BRDFs) and light sources with Monte Carlo path tracing algorithms. The wavelet representation effectively compresses BRDF and emission data while inducing only a small error in the reconstructed signal. The representation can be used to evaluate efficiently some integrals that appear in shading computation which allows fast, accurate computation of local shading. The representation can be used to represent light fields and is used to reconstruct views of environments interactively from a precomputed set of views. The representation of the BRDF also allows the efficient generation of reflected directions for Monte Carlo array tracing applications. The method can be integrated into many different global illumination algorithms, including ray tracers and wavelet radiosity systems.

The influence of lexical statistics on temporal lobe cortical dynamics during spoken word listening

PubMed Central

Cibelli, Emily S.; Leonard, Matthew K.; Johnson, Keith; Chang, Edward F.

2015-01-01

Neural representations of words are thought to have a complex spatio-temporal cortical basis. It has been suggested that spoken word recognition is not a process of feed-forward computations from phonetic to lexical forms, but rather involves the online integration of bottom-up input with stored lexical knowledge. Using direct neural recordings from the temporal lobe, we examined cortical responses to words and pseudowords. We found that neural populations were not only sensitive to lexical status (real vs. pseudo), but also to cohort size (number of words matching the phonetic input at each time point) and cohort frequency (lexical frequency of those words). These lexical variables modulated neural activity from the posterior to anterior temporal lobe, and also dynamically as the stimuli unfolded on a millisecond time scale. Our findings indicate that word recognition is not purely modular, but relies on rapid and online integration of multiple sources of lexical knowledge. PMID:26072003

Ultrawideband radar; Proceedings of the Meeting, Los Angeles, CA, Jan. 22, 23, 1992

NASA Astrophysics Data System (ADS)

Lahaie, Ivan J.

1992-05-01

The present conference discusses a canonical representation of the radar range equation in the time domain, two-way beam patterns fron ultrawideband arrays, modeling of ultrawideband sea clutter, the analysis of time-domain ultrawideband radar signals, a frequency-agile ultrawideband microwave source, and the performance of ultrawideband antennas. Also discussed are the diffraction of ultrawideband radar pulses, sea-clutter measurements with an ultrawideband X-band radar having variable resolution, results from a VHF-impulse SAR, an ultrawideband differential radar, the development of 2D target images from ultrawideband radar systems, ultrawideband generators, and the radiated waveform of a monolithic photoconductive GaAs pulser. (For individual items see A93-28202 to A93-28223)

Losing the music: aging affects the perception and subcortical neural representation of musical harmony.

PubMed

Bones, Oliver; Plack, Christopher J

2015-03-04

When two musical notes with simple frequency ratios are played simultaneously, the resulting musical chord is pleasing and evokes a sense of resolution or "consonance". Complex frequency ratios, on the other hand, evoke feelings of tension or "dissonance". Consonance and dissonance form the basis of harmony, a central component of Western music. In earlier work, we provided evidence that consonance perception is based on neural temporal coding in the brainstem (Bones et al., 2014). Here, we show that for listeners with clinically normal hearing, aging is associated with a decline in both the perceptual distinction and the distinctiveness of the neural representations of different categories of two-note chords. Compared with younger listeners, older listeners rated consonant chords as less pleasant and dissonant chords as more pleasant. Older listeners also had less distinct neural representations of consonant and dissonant chords as measured using a Neural Consonance Index derived from the electrophysiological "frequency-following response." The results withstood a control for the effect of age on general affect, suggesting that different mechanisms are responsible for the perceived pleasantness of musical chords and affective voices and that, for listeners with clinically normal hearing, age-related differences in consonance perception are likely to be related to differences in neural temporal coding. Copyright © 2015 Bones and Plack.

Beyond capacity limitations II: Effects of lexical processes on word recall in verbal working memory tasks in children with and without specific language impairment

PubMed Central

Mainela-Arnold, Elina; Evans, Julia L.; Coady, Jeffry

2010-01-01

Purpose This study investigated the impact of lexical processes on target word recall in sentence span tasks in children with and without specific language impairment (SLI). Method Participants were 42 children (ages 8;2–12;3), 21 with SLI and 21 typically developing peers matched on age and nonverbal IQ. Children completed a sentence span task where target words to be recalled varied in word frequency and neighborhood density. Two measures of lexical processes were examined, the number of non-target competitor words activated during a gating task (lexical cohort competition) and word definitions. Results Neighborhood density had no effect on word recall for either group. However, both groups recalled significantly more high than low frequency words. Lexical cohort competition and specificity of semantic representations accounted for unique variance in the number of target word recalled in the SLI and CA groups combined. Conclusions Performance on verbal working memory span tasks for both SLI and CA children is influenced by word frequency, lexical cohorts, and semantic representations. Future studies need to examine the extent to which verbal working memory capacity is a cognitive construct independent of extant language knowledge representations. PMID:20705747

Losing the Music: Aging Affects the Perception and Subcortical Neural Representation of Musical Harmony

PubMed Central

Plack, Christopher J.

2015-01-01

When two musical notes with simple frequency ratios are played simultaneously, the resulting musical chord is pleasing and evokes a sense of resolution or “consonance”. Complex frequency ratios, on the other hand, evoke feelings of tension or “dissonance”. Consonance and dissonance form the basis of harmony, a central component of Western music. In earlier work, we provided evidence that consonance perception is based on neural temporal coding in the brainstem (Bones et al., 2014). Here, we show that for listeners with clinically normal hearing, aging is associated with a decline in both the perceptual distinction and the distinctiveness of the neural representations of different categories of two-note chords. Compared with younger listeners, older listeners rated consonant chords as less pleasant and dissonant chords as more pleasant. Older listeners also had less distinct neural representations of consonant and dissonant chords as measured using a Neural Consonance Index derived from the electrophysiological “frequency-following response.” The results withstood a control for the effect of age on general affect, suggesting that different mechanisms are responsible for the perceived pleasantness of musical chords and affective voices and that, for listeners with clinically normal hearing, age-related differences in consonance perception are likely to be related to differences in neural temporal coding. PMID:25740534

Representation of pitch chroma by multi-peak spectral tuning in human auditory cortex

PubMed Central

Moerel, Michelle; De Martino, Federico; Santoro, Roberta; Yacoub, Essa; Formisano, Elia

2015-01-01

Musical notes played at octave intervals (i.e., having the same pitch chroma) are perceived as similar. This well-known perceptual phenomenon lays at the foundation of melody recognition and music perception, yet its neural underpinnings remain largely unknown to date. Using fMRI with high sensitivity and spatial resolution, we examined the contribution of multi-peak spectral tuning to the neural representation of pitch chroma in human auditory cortex in two experiments. In experiment 1, our estimation of population spectral tuning curves from the responses to natural sounds confirmed—with new data—our recent results on the existence of cortical ensemble responses finely tuned to multiple frequencies at one octave distance (Moerel et al., 2013). In experiment 2, we fitted a mathematical model consisting of a pitch chroma and height component to explain the measured fMRI responses to piano notes. This analysis revealed that the octave-tuned populations—but not other cortical populations—harbored a neural representation of musical notes according to their pitch chroma. These results indicate that responses of auditory cortical populations selectively tuned to multiple frequencies at one octave distance predict well the perceptual similarity of musical notes with the same chroma, beyond the physical (frequency) distance of notes. PMID:25479020

Representation of pitch chroma by multi-peak spectral tuning in human auditory cortex.

PubMed

Moerel, Michelle; De Martino, Federico; Santoro, Roberta; Yacoub, Essa; Formisano, Elia

2015-02-01

Musical notes played at octave intervals (i.e., having the same pitch chroma) are perceived as similar. This well-known perceptual phenomenon lays at the foundation of melody recognition and music perception, yet its neural underpinnings remain largely unknown to date. Using fMRI with high sensitivity and spatial resolution, we examined the contribution of multi-peak spectral tuning to the neural representation of pitch chroma in human auditory cortex in two experiments. In experiment 1, our estimation of population spectral tuning curves from the responses to natural sounds confirmed--with new data--our recent results on the existence of cortical ensemble responses finely tuned to multiple frequencies at one octave distance (Moerel et al., 2013). In experiment 2, we fitted a mathematical model consisting of a pitch chroma and height component to explain the measured fMRI responses to piano notes. This analysis revealed that the octave-tuned populations-but not other cortical populations-harbored a neural representation of musical notes according to their pitch chroma. These results indicate that responses of auditory cortical populations selectively tuned to multiple frequencies at one octave distance predict well the perceptual similarity of musical notes with the same chroma, beyond the physical (frequency) distance of notes. Copyright © 2014 Elsevier Inc. All rights reserved.

Nonlinear data-driven identification of polymer electrolyte membrane fuel cells for diagnostic purposes: A Volterra series approach

NASA Astrophysics Data System (ADS)

Ritzberger, D.; Jakubek, S.

2017-09-01

In this work, a data-driven identification method, based on polynomial nonlinear autoregressive models with exogenous inputs (NARX) and the Volterra series, is proposed to describe the dynamic and nonlinear voltage and current characteristics of polymer electrolyte membrane fuel cells (PEMFCs). The structure selection and parameter estimation of the NARX model is performed on broad-band voltage/current data. By transforming the time-domain NARX model into a Volterra series representation using the harmonic probing algorithm, a frequency-domain description of the linear and nonlinear dynamics is obtained. With the Volterra kernels corresponding to different operating conditions, information from existing diagnostic tools in the frequency domain such as electrochemical impedance spectroscopy (EIS) and total harmonic distortion analysis (THDA) are effectively combined. Additionally, the time-domain NARX model can be utilized for fault detection by evaluating the difference between measured and simulated output. To increase the fault detectability, an optimization problem is introduced which maximizes this output residual to obtain proper excitation frequencies. As a possible extension it is shown, that by optimizing the periodic signal shape itself that the fault detectability is further increased.

Flexible and fast: linguistic shortcut affects both shallow and deep conceptual processing.

PubMed

Connell, Louise; Lynott, Dermot

2013-06-01

Previous research has shown that people use linguistic distributional information during conceptual processing, and that it is especially useful for shallow tasks and rapid responding. Using two conceptual combination tasks, we showed that this linguistic shortcut extends to the processing of novel stimuli, is used in both successful and unsuccessful conceptual processing, and is evident in both shallow and deep conceptual tasks. Specifically, as predicted by the ECCo theory of conceptual combination, people use the linguistic shortcut as a "quick-and-dirty" guide to whether the concepts are likely to combine into a coherent conceptual representation, in both shallow sensibility judgment and deep interpretation generation tasks. Linguistic distributional frequency predicts both the likelihood and the time course of rejecting a novel word compound as nonsensical or uninterpretable. However, it predicts the time course of successful processing only in shallow sensibility judgment, because the deeper conceptual process of interpretation generation does not allow the linguistic shortcut to suffice. Furthermore, the effects of linguistic distributional frequency are independent of any effects of conventional word frequency. We discuss the utility of the linguistic shortcut as a cognitive triage mechanism that can optimize processing in a limited-resource conceptual system.

High-frequency neural activity predicts word parsing in ambiguous speech streams.

PubMed

Kösem, Anne; Basirat, Anahita; Azizi, Leila; van Wassenhove, Virginie

2016-12-01

During speech listening, the brain parses a continuous acoustic stream of information into computational units (e.g., syllables or words) necessary for speech comprehension. Recent neuroscientific hypotheses have proposed that neural oscillations contribute to speech parsing, but whether they do so on the basis of acoustic cues (bottom-up acoustic parsing) or as a function of available linguistic representations (top-down linguistic parsing) is unknown. In this magnetoencephalography study, we contrasted acoustic and linguistic parsing using bistable speech sequences. While listening to the speech sequences, participants were asked to maintain one of the two possible speech percepts through volitional control. We predicted that the tracking of speech dynamics by neural oscillations would not only follow the acoustic properties but also shift in time according to the participant's conscious speech percept. Our results show that the latency of high-frequency activity (specifically, beta and gamma bands) varied as a function of the perceptual report. In contrast, the phase of low-frequency oscillations was not strongly affected by top-down control. Whereas changes in low-frequency neural oscillations were compatible with the encoding of prelexical segmentation cues, high-frequency activity specifically informed on an individual's conscious speech percept. Copyright © 2016 the American Physiological Society.

High-frequency neural activity predicts word parsing in ambiguous speech streams

PubMed Central

Basirat, Anahita; Azizi, Leila; van Wassenhove, Virginie

2016-01-01

During speech listening, the brain parses a continuous acoustic stream of information into computational units (e.g., syllables or words) necessary for speech comprehension. Recent neuroscientific hypotheses have proposed that neural oscillations contribute to speech parsing, but whether they do so on the basis of acoustic cues (bottom-up acoustic parsing) or as a function of available linguistic representations (top-down linguistic parsing) is unknown. In this magnetoencephalography study, we contrasted acoustic and linguistic parsing using bistable speech sequences. While listening to the speech sequences, participants were asked to maintain one of the two possible speech percepts through volitional control. We predicted that the tracking of speech dynamics by neural oscillations would not only follow the acoustic properties but also shift in time according to the participant's conscious speech percept. Our results show that the latency of high-frequency activity (specifically, beta and gamma bands) varied as a function of the perceptual report. In contrast, the phase of low-frequency oscillations was not strongly affected by top-down control. Whereas changes in low-frequency neural oscillations were compatible with the encoding of prelexical segmentation cues, high-frequency activity specifically informed on an individual's conscious speech percept. PMID:27605528

System and method for detection of dispersed broadband signals

DOEpatents

Qian, S.; Dunham, M.E.

1999-06-08

A system and method for detecting the presence of dispersed broadband signals in real time are disclosed. The present invention utilizes a bank of matched filters for detecting the received dispersed broadband signals. Each matched filter uses a respective robust time template that has been designed to approximate the dispersed broadband signals of interest, and each time template varies across a spectrum of possible dispersed broadband signal time templates. The received dispersed broadband signal x(t) is received by each of the matched filters, and if one or more matches occurs, then the received data is determined to have signal data of interest. This signal data can then be analyzed and/or transmitted to Earth for analysis, as desired. The system and method of the present invention will prove extremely useful in many fields, including satellite communications, plasma physics, and interstellar research. The varying time templates used in the bank of matched filters are determined as follows. The robust time domain template is assumed to take the form w(t)=A(t)cos[l brace]2[phi](t)[r brace]. Since the instantaneous frequency f(t) is known to be equal to the derivative of the phase [phi](t), the trajectory of a joint time-frequency representation of x(t) is used as an approximation of [phi][prime](t). 10 figs.

System and method for detection of dispersed broadband signals

DOEpatents

Qian, Shie; Dunham, Mark E.

1999-06-08

A system and method for detecting the presence of dispersed broadband signals in real time. The present invention utilizes a bank of matched filters for detecting the received dispersed broadband signals. Each matched filter uses a respective robust time template that has been designed to approximate the dispersed broadband signals of interest, and each time template varies across a spectrum of possible dispersed broadband signal time templates. The received dispersed broadband signal x(t) is received by each of the matched filters, and if one or more matches occurs, then the received data is determined to have signal data of interest. This signal data can then be analyzed and/or transmitted to Earth for analysis, as desired. The system and method of the present invention will prove extremely useful in many fields, including satellite communications, plasma physics, and interstellar research. The varying time templates used in the bank of matched filters are determined as follows. The robust time domain template is assumed to take the form w(t)=A(t)cos{2.phi.(t)}. Since the instantaneous frequency f(t) is known to be equal to the derivative of the phase .phi.(t), the trajectory of a joint time-frequency representation of x(t) is used as an approximation of .phi.'(t).

Characterization and prediction of the backscattered form function of an immersed cylindrical shell using hybrid fuzzy clustering and bio-inspired algorithms.

PubMed

Agounad, Said; Aassif, El Houcein; Khandouch, Younes; Maze, Gérard; Décultot, Dominique

2018-02-01

The acoustic scattering of a plane wave by an elastic cylindrical shell is studied. A new approach is developed to predict the form function of an immersed cylindrical shell of the radius ratio b/a ('b' is the inner radius and 'a' is the outer radius). The prediction of the backscattered form function is investigated by a combined approach between fuzzy clustering algorithms and bio-inspired algorithms. Four famous fuzzy clustering algorithms: the fuzzy c-means (FCM), the Gustafson-Kessel algorithm (GK), the fuzzy c-regression model (FCRM) and the Gath-Geva algorithm (GG) are combined with particle swarm optimization and genetic algorithm. The symmetric and antisymmetric circumferential waves A, S 0 , A 1 , S 1 and S 2 are investigated in a reduced frequency (k 1 a) range extends over 0.1

Gender disparity in subcortical encoding of binaurally presented speech stimuli: an auditory evoked potentials study.

PubMed

Ahadi, Mohsen; Pourbakht, Akram; Jafari, Amir Homayoun; Shirjian, Zahra; Jafarpisheh, Amir Salar

2014-06-01

To investigate the influence of gender on subcortical representation of speech acoustic parameters where simultaneously presented to both ears. Two-channel speech-evoked auditory brainstem responses were obtained in 25 female and 23 male normal hearing young adults by using binaural presentation of the 40 ms synthetic consonant-vowel/da/, and the encoding of the fast and slow elements of speech stimuli at subcortical level were compared in the temporal and spectral domains between the sexes using independent sample, two tailed t-test. Highly detectable responses were established in both groups. Analysis in the time domain revealed earlier and larger Fast-onset-responses in females but there was no gender related difference in sustained segment and offset of the response. Interpeak intervals between Frequency Following Response peaks were also invariant to sex. Based on shorter onset responses in females, composite onset measures were also sex dependent. Analysis in the spectral domain showed more robust and better representation of fundamental frequency as well as the first formant and high frequency components of first formant in females than in males. Anatomical, biological and biochemical distinctions between females and males could alter the neural encoding of the acoustic cues of speech stimuli at subcortical level. Females have an advantage in binaural processing of the slow and fast elements of speech. This could be a physiological evidence for better identification of speaker and emotional tone of voice, as well as better perceiving the phonetic information of speech in women. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Structural, electrical properties and dielectric relaxations in Na+-ion-conducting solid polymer electrolyte

NASA Astrophysics Data System (ADS)

Arya, Anil; Sharma, A. L.

2018-04-01

In this paper, we have studied the structural, microstructural, electrical, dielectric properties and ion dynamics of a sodium-ion-conducting solid polymer electrolyte film comprising PEO8-NaPF6+  x wt. % succinonitrile. The structural and surface morphology properties have been investigated, respectively using x-ray diffraction and field emission scanning electron microscopy. The complex formation was examined using Fourier transform infrared spectroscopy, and the fraction of free anions/ion pairs obtained via deconvolution. The complex dielectric permittivity and loss tangent has been analyzed across the whole frequency window, and enables us to estimate the DC conductivity, dielectric strength, double layer capacitance and relaxation time. The presence of relaxing dipoles was determined by the addition of succinonitrile (wt./wt.) and the peak shift towards high frequency indicates the decrease of relaxation time. Further, relations among various relaxation times ({{τ }{{\\varepsilon \\prime}}}>~{{τ }tanδ }>{{τ }z}>{{τ }m} ) have been elucidated. The complex conductivity has been examined across the whole frequency window; it obeys the Universal Power Law, and displays strong dependency on succinonitrile content. The sigma representation ({{σ }\\prime\\prime}~versus~{{σ }\\prime} ) was introduced in order to explore the ion dynamics by highlighting the dispersion region in the Cole–Cole plot ({{\\varepsilon }\\prime\\prime}~versus~{{\\varepsilon }\\prime} ) in the lower frequency window; increase in the semicircle radius indicates a decrease of relaxation time. This observation is accompanied by enhancement in ionic conductivity and faster ion transport. A convincing, logical scheme to justify the experimental data has been proposed.

Small Craters and Their Diagnostic Potential

NASA Astrophysics Data System (ADS)

Bugiolacchi, R.

2017-07-01

I analysed and compared the size-frequency distributions of craters in the Apollo 17 landing region, comprising of six mare terrains with varying morphologies and cratering characteristics, along with three other regions allegedly affected by the same secondary event (Tycho secondary surge). I propose that for the smaller crater sizes (in this work 9-30 m), a] an exponential curve of power -0.18D can approximate Nkm-2 crater densities in a regime of equilibrium, while b] a power function D-3 closely describes the factorised representation of craters by size (1 m). The saturation level within the Central Area suggests that c] either the modelled rates of crater erosion on the Moon should be revised, or that the Tycho event occurred much earlier in time than the current estimate. We propose that d] the size-frequency distribution of small secondary craters may bear the signature (in terms of size-frequency distribution of debris/surge) of the source impact and that this observation should be tested further.

Probability and possibility-based representations of uncertainty in fault tree analysis.

PubMed

Flage, Roger; Baraldi, Piero; Zio, Enrico; Aven, Terje

2013-01-01

Expert knowledge is an important source of input to risk analysis. In practice, experts might be reluctant to characterize their knowledge and the related (epistemic) uncertainty using precise probabilities. The theory of possibility allows for imprecision in probability assignments. The associated possibilistic representation of epistemic uncertainty can be combined with, and transformed into, a probabilistic representation; in this article, we show this with reference to a simple fault tree analysis. We apply an integrated (hybrid) probabilistic-possibilistic computational framework for the joint propagation of the epistemic uncertainty on the values of the (limiting relative frequency) probabilities of the basic events of the fault tree, and we use possibility-probability (probability-possibility) transformations for propagating the epistemic uncertainty within purely probabilistic and possibilistic settings. The results of the different approaches (hybrid, probabilistic, and possibilistic) are compared with respect to the representation of uncertainty about the top event (limiting relative frequency) probability. Both the rationale underpinning the approaches and the computational efforts they require are critically examined. We conclude that the approaches relevant in a given setting depend on the purpose of the risk analysis, and that further research is required to make the possibilistic approaches operational in a risk analysis context. © 2012 Society for Risk Analysis.

On the Locus of the Syllable Frequency Effect in Speech Production

ERIC Educational Resources Information Center

Laganaro, Marina; Alario, F. -Xavier

2006-01-01

The observation of a syllable frequency effect in naming latencies has been an argument in favor of a functional role of stored syllables in speech production. Accordingly, various theoretical models postulate that a repository of syllable representations is accessed during phonetic encoding. However, the direct empirical evidence for locating the…

Image Fusion of CT and MR with Sparse Representation in NSST Domain

PubMed Central

Qiu, Chenhui; Wang, Yuanyuan; Zhang, Huan

2017-01-01

Multimodal image fusion techniques can integrate the information from different medical images to get an informative image that is more suitable for joint diagnosis, preoperative planning, intraoperative guidance, and interventional treatment. Fusing images of CT and different MR modalities are studied in this paper. Firstly, the CT and MR images are both transformed to nonsubsampled shearlet transform (NSST) domain. So the low-frequency components and high-frequency components are obtained. Then the high-frequency components are merged using the absolute-maximum rule, while the low-frequency components are merged by a sparse representation- (SR-) based approach. And the dynamic group sparsity recovery (DGSR) algorithm is proposed to improve the performance of the SR-based approach. Finally, the fused image is obtained by performing the inverse NSST on the merged components. The proposed fusion method is tested on a number of clinical CT and MR images and compared with several popular image fusion methods. The experimental results demonstrate that the proposed fusion method can provide better fusion results in terms of subjective quality and objective evaluation. PMID:29250134

Experimental diagnostics and modeling of inductive phenomena at low frequencies in impedance spectra of proton exchange membrane fuel cells

NASA Astrophysics Data System (ADS)

Pivac, Ivan; Šimić, Boris; Barbir, Frano

2017-10-01

Representation of fuel cell processes by equivalent circuit models, involving resistance and capacitance elements representing activation losses on both anode and cathode in series with resistance representing ohmic losses, cannot capture and explain the inductive loop that may show up at low frequencies in Nyquist diagram representation of the electrochemical impedance spectra. In an attempt to explain the cause of the low-frequency inductive loop and correlate it with the processes within the fuel cell electrodes, a novel equivalent circuit model of a Proton Exchange Membrane (PEM) fuel cell has been proposed and experimentally verified here in detail. The model takes into account both the anode and the cathode, and has an additional resonant loop on each side, comprising of a resistance, capacitance and inductance in parallel representing the processes within the catalyst layer. Using these additional circuit elements, more accurate and better fits to experimental impedance data in the wide frequency range at different current densities, cell temperatures, humidity of gases, air flow stoichiometries and backpressures were obtained.

Image Fusion of CT and MR with Sparse Representation in NSST Domain.

PubMed

Qiu, Chenhui; Wang, Yuanyuan; Zhang, Huan; Xia, Shunren

2017-01-01

Multimodal image fusion techniques can integrate the information from different medical images to get an informative image that is more suitable for joint diagnosis, preoperative planning, intraoperative guidance, and interventional treatment. Fusing images of CT and different MR modalities are studied in this paper. Firstly, the CT and MR images are both transformed to nonsubsampled shearlet transform (NSST) domain. So the low-frequency components and high-frequency components are obtained. Then the high-frequency components are merged using the absolute-maximum rule, while the low-frequency components are merged by a sparse representation- (SR-) based approach. And the dynamic group sparsity recovery (DGSR) algorithm is proposed to improve the performance of the SR-based approach. Finally, the fused image is obtained by performing the inverse NSST on the merged components. The proposed fusion method is tested on a number of clinical CT and MR images and compared with several popular image fusion methods. The experimental results demonstrate that the proposed fusion method can provide better fusion results in terms of subjective quality and objective evaluation.

Ubiquitous Log Odds: A Common Representation of Probability and Frequency Distortion in Perception, Action, and Cognition

PubMed Central

Zhang, Hang; Maloney, Laurence T.

2012-01-01

In decision from experience, the source of probability information affects how probability is distorted in the decision task. Understanding how and why probability is distorted is a key issue in understanding the peculiar character of experience-based decision. We consider how probability information is used not just in decision-making but also in a wide variety of cognitive, perceptual, and motor tasks. Very similar patterns of distortion of probability/frequency information have been found in visual frequency estimation, frequency estimation based on memory, signal detection theory, and in the use of probability information in decision-making under risk and uncertainty. We show that distortion of probability in all cases is well captured as linear transformations of the log odds of frequency and/or probability, a model with a slope parameter, and an intercept parameter. We then consider how task and experience influence these two parameters and the resulting distortion of probability. We review how the probability distortions change in systematic ways with task and report three experiments on frequency distortion where the distortions change systematically in the same task. We found that the slope of frequency distortions decreases with the sample size, which is echoed by findings in decision from experience. We review previous models of the representation of uncertainty and find that none can account for the empirical findings. PMID:22294978

Bearing fault diagnosis under unknown time-varying rotational speed conditions via multiple time-frequency curve extraction

NASA Astrophysics Data System (ADS)

Huang, Huan; Baddour, Natalie; Liang, Ming

2018-02-01

Under normal operating conditions, bearings often run under time-varying rotational speed conditions. Under such circumstances, the bearing vibrational signal is non-stationary, which renders ineffective the techniques used for bearing fault diagnosis under constant running conditions. One of the conventional methods of bearing fault diagnosis under time-varying speed conditions is resampling the non-stationary signal to a stationary signal via order tracking with the measured variable speed. With the resampled signal, the methods available for constant condition cases are thus applicable. However, the accuracy of the order tracking is often inadequate and the time-varying speed is sometimes not measurable. Thus, resampling-free methods are of interest for bearing fault diagnosis under time-varying rotational speed for use without tachometers. With the development of time-frequency analysis, the time-varying fault character manifests as curves in the time-frequency domain. By extracting the Instantaneous Fault Characteristic Frequency (IFCF) from the Time-Frequency Representation (TFR) and converting the IFCF, its harmonics, and the Instantaneous Shaft Rotational Frequency (ISRF) into straight lines, the bearing fault can be detected and diagnosed without resampling. However, so far, the extraction of the IFCF for bearing fault diagnosis is mostly based on the assumption that at each moment the IFCF has the highest amplitude in the TFR, which is not always true. Hence, a more reliable T-F curve extraction approach should be investigated. Moreover, if the T-F curves including the IFCF, its harmonic, and the ISRF can be all extracted from the TFR directly, no extra processing is needed for fault diagnosis. Therefore, this paper proposes an algorithm for multiple T-F curve extraction from the TFR based on a fast path optimization which is more reliable for T-F curve extraction. Then, a new procedure for bearing fault diagnosis under unknown time-varying speed conditions is developed based on the proposed algorithm and a new fault diagnosis strategy. The average curve-to-curve ratios are utilized to describe the relationship of the extracted curves and fault diagnosis can then be achieved by comparing the ratios to the fault characteristic coefficients. The effectiveness of the proposed method is validated by simulated and experimental signals.

Decomposing delta, theta, and alpha time–frequency ERP activity from a visual oddball task using PCA

PubMed Central

Bernat, Edward M.; Malone, Stephen M.; Williams, William J.; Patrick, Christopher J.; Iacono, William G.

2008-01-01

Objective Time–frequency (TF) analysis has become an important tool for assessing electrical and magnetic brain activity from event-related paradigms. In electrical potential data, theta and delta activities have been shown to underlie P300 activity, and alpha has been shown to be inhibited during P300 activity. Measures of delta, theta, and alpha activity are commonly taken from TF surfaces. However, methods for extracting relevant activity do not commonly go beyond taking means of windows on the surface, analogous to measuring activity within a defined P300 window in time-only signal representations. The current objective was to use a data driven method to derive relevant TF components from event-related potential data from a large number of participants in an oddball paradigm. Methods A recently developed PCA approach was employed to extract TF components [Bernat, E. M., Williams, W. J., and Gehring, W. J. (2005). Decomposing ERP time-frequency energy using PCA. Clin Neurophysiol, 116(6), 1314–1334] from an ERP dataset of 2068 17 year olds (979 males). TF activity was taken from both individual trials and condition averages. Activity including frequencies ranging from 0 to 14 Hz and time ranging from stimulus onset to 1312.5 ms were decomposed. Results A coordinated set of time–frequency events was apparent across the decompositions. Similar TF components representing earlier theta followed by delta were extracted from both individual trials and averaged data. Alpha activity, as predicted, was apparent only when time–frequency surfaces were generated from trial level data, and was characterized by a reduction during the P300. Conclusions Theta, delta, and alpha activities were extracted with predictable time-courses. Notably, this approach was effective at characterizing data from a single-electrode. Finally, decomposition of TF data generated from individual trials and condition averages produced similar results, but with predictable differences. Specifically, trial level data evidenced more and more varied theta measures, and accounted for less overall variance. PMID:17027110

Human operator identification model and related computer programs

NASA Technical Reports Server (NTRS)

Kessler, K. M.; Mohr, J. N.

1978-01-01

Four computer programs which provide computational assistance in the analysis of man/machine systems are reported. The programs are: (1) Modified Transfer Function Program (TF); (2) Time Varying Response Program (TVSR); (3) Optimal Simulation Program (TVOPT); and (4) Linear Identification Program (SCIDNT). The TV program converts the time domain state variable system representative to frequency domain transfer function system representation. The TVSR program computes time histories of the input/output responses of the human operator model. The TVOPT program is an optimal simulation program and is similar to TVSR in that it produces time histories of system states associated with an operator in the loop system. The differences between the two programs are presented. The SCIDNT program is an open loop identification code which operates on the simulated data from TVOPT (or TVSR) or real operator data from motion simulators.

Music and learning-induced cortical plasticity.

PubMed

Pantev, Christo; Ross, Bernhard; Fujioka, Takkao; Trainor, Laurel J; Schulte, Michael; Schulz, Matthias

2003-11-01

Auditory stimuli are encoded by frequency-tuned neurons in the auditory cortex. There are a number of tonotopic maps, indicating that there are multiple representations, as in a mosaic. However, the cortical organization is not fixed due to the brain's capacity to adapt to current requirements of the environment. Several experiments on cerebral cortical organization in musicians demonstrate an astonishing plasticity. We used the MEG technique in a number of studies to investigate the changes that occur in the human auditory cortex when a skill is acquired, such as when learning to play a musical instrument. We found enlarged cortical representation of tones of the musical scale as compared to pure tones in skilled musicians. Enlargement was correlated with the age at which musicians began to practice. We also investigated cortical representations for notes of different timbre (violin and trumpet) and found that they are enhanced in violinists and trumpeters, preferentially for the timbre of the instrument on which the musician was trained. In recent studies we extended these findings in three ways. First, we show that we can use MEG to measure the effects of relatively short-term laboratory training involving learning to perceive virtual instead of spectral pitch and that the switch to perceiving virtual pitch is manifested in the gamma band frequency. Second, we show that there is cross-modal plasticity in that when the lips of trumpet players are stimulated (trumpet players assess their auditory performance by monitoring the position and pressure of their lips touching the mouthpiece of their instrument) at the same time as a trumpet tone, activation in the somatosensory cortex is increased more than it is during the sum of the separate lip and trumpet tone stimulation. Third, we show that musicians' automatic encoding and discrimination of pitch contour and interval information in melodies are specifically enhanced compared to those in nonmusicians in that musicians show larger functional mismatch negativity (MMNm) responses to occasional changes in melodic contour or interval, but that the two groups show similar MMNm responses to changes in the frequency of a pure tone.

Quantitative analysis of harmonic convergence in mosquito auditory interactions

PubMed Central

Aldersley, Andrew; Champneys, Alan; Robert, Daniel

2016-01-01

This article analyses the hearing and behaviour of mosquitoes in the context of inter-individual acoustic interactions. The acoustic interactions of tethered live pairs of Aedes aegypti mosquitoes, from same and opposite sex mosquitoes of the species, are recorded on independent and unique audio channels, together with the response of tethered individual mosquitoes to playbacks of pre-recorded flight tones of lone or paired individuals. A time-dependent representation of each mosquito's non-stationary wing beat frequency signature is constructed, based on Hilbert spectral analysis. A range of algorithmic tools is developed to automatically analyse these data, and used to perform a robust quantitative identification of the ‘harmonic convergence’ phenomenon. The results suggest that harmonic convergence is an active phenomenon, which does not occur by chance. It occurs for live pairs, as well as for lone individuals responding to playback recordings, whether from the same or opposite sex. Male–female behaviour is dominated by frequency convergence at a wider range of harmonic combinations than previously reported, and requires participation from both partners in the duet. New evidence is found to show that male–male interactions are more varied than strict frequency avoidance. Rather, they can be divided into two groups: convergent pairs, typified by tightly bound wing beat frequencies, and divergent pairs, that remain widely spaced in the frequency domain. Overall, the results reveal that mosquito acoustic interaction is a delicate and intricate time-dependent active process that involves both individuals, takes place at many different frequencies, and which merits further enquiry. PMID:27053654

39 CFR 966.6 - Filing, docketing and serving documents; computation of time; representation of parties.

Code of Federal Regulations, 2013 CFR

2013-07-01

... are between 8:45 a.m. and 4:45 p.m., eastern standard or daylight saving time as appropriate during...; computation of time; representation of parties. 966.6 Section 966.6 Postal Service UNITED STATES POSTAL... time; representation of parties. (a) Filing. All documents required under this part must be filed by...

39 CFR 966.6 - Filing, docketing and serving documents; computation of time; representation of parties.

Code of Federal Regulations, 2014 CFR

2014-07-01

... are between 8:45 a.m. and 4:45 p.m., eastern standard or daylight saving time as appropriate during...; computation of time; representation of parties. 966.6 Section 966.6 Postal Service UNITED STATES POSTAL... time; representation of parties. (a) Filing. All documents required under this part must be filed by...

Female Representation in the Academic Oncology Physician Workforce: Radiation Oncology Losing Ground to Hematology Oncology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ahmed, Awad A.; Hwang, Wei-Ting; Holliday, Emma B.

Purpose: Our purpose was to assess comparative female representation trends for trainees and full-time faculty in the academic radiation oncology and hematology oncology workforce of the United States over 3 decades. Methods and Materials: Simple linear regression models with year as the independent variable were used to determine changes in female percentage representation per year and associated 95% confidence intervals for trainees and full-time faculty in each specialty. Results: Peak representation was 48.4% (801/1654) in 2013 for hematology oncology trainees, 39.0% (585/1499) in 2014 for hematology oncology full-time faculty, 34.8% (202/581) in 2007 for radiation oncology trainees, and 27.7% (439/1584) inmore » 2015 for radiation oncology full-time faculty. Representation significantly increased for trainees and full-time faculty in both specialties at approximately 1% per year for hematology oncology trainees and full-time faculty and 0.3% per year for radiation oncology trainees and full-time faculty. Compared with radiation oncology, the rates were 3.84 and 2.94 times greater for hematology oncology trainees and full-time faculty, respectively. Conclusion: Despite increased female trainee and full-time faculty representation over time in the academic oncology physician workforce, radiation oncology is lagging behind hematology oncology, with trainees declining in recent years in radiation oncology; this suggests a de facto ceiling in female representation. Whether such issues as delayed or insufficient exposure, inadequate mentorship, or specialty competitiveness disparately affect female representation in radiation oncology compared to hematology oncology are underexplored and require continued investigation to ensure that the future oncologic physician workforce reflects the diversity of the population it serves.« less

Female Representation in the Academic Oncology Physician Workforce: Radiation Oncology Losing Ground to Hematology Oncology.

PubMed

Ahmed, Awad A; Hwang, Wei-Ting; Holliday, Emma B; Chapman, Christina H; Jagsi, Reshma; Thomas, Charles R; Deville, Curtiland

2017-05-01

Our purpose was to assess comparative female representation trends for trainees and full-time faculty in the academic radiation oncology and hematology oncology workforce of the United States over 3 decades. Simple linear regression models with year as the independent variable were used to determine changes in female percentage representation per year and associated 95% confidence intervals for trainees and full-time faculty in each specialty. Peak representation was 48.4% (801/1654) in 2013 for hematology oncology trainees, 39.0% (585/1499) in 2014 for hematology oncology full-time faculty, 34.8% (202/581) in 2007 for radiation oncology trainees, and 27.7% (439/1584) in 2015 for radiation oncology full-time faculty. Representation significantly increased for trainees and full-time faculty in both specialties at approximately 1% per year for hematology oncology trainees and full-time faculty and 0.3% per year for radiation oncology trainees and full-time faculty. Compared with radiation oncology, the rates were 3.84 and 2.94 times greater for hematology oncology trainees and full-time faculty, respectively. Despite increased female trainee and full-time faculty representation over time in the academic oncology physician workforce, radiation oncology is lagging behind hematology oncology, with trainees declining in recent years in radiation oncology; this suggests a de facto ceiling in female representation. Whether such issues as delayed or insufficient exposure, inadequate mentorship, or specialty competitiveness disparately affect female representation in radiation oncology compared to hematology oncology are underexplored and require continued investigation to ensure that the future oncologic physician workforce reflects the diversity of the population it serves. Copyright © 2017 Elsevier Inc. All rights reserved.

Gaussian representation of high-intensity focused ultrasound beams.

PubMed

Soneson, Joshua E; Myers, Matthew R

2007-11-01

A method for fast numerical simulation of high-intensity focused ultrasound beams is derived. The method is based on the frequency-domain representation of the Khokhlov-Zabolotskaya-Kuznetsov (KZK) equation, and assumes for each harmonic a Gaussian transverse pressure distribution at all distances from the transducer face. The beamwidths of the harmonics are constrained to vary inversely with the square root of the harmonic number, and as such this method may be viewed as an extension of a quasilinear approximation. The technique is capable of determining pressure or intensity fields of moderately nonlinear high-intensity focused ultrasound beams in water or biological tissue, usually requiring less than a minute of computer time on a modern workstation. Moreover, this method is particularly well suited to high-gain simulations since, unlike traditional finite-difference methods, it is not subject to resolution limitations in the transverse direction. Results are shown to be in reasonable agreement with numerical solutions of the full KZK equation in both tissue and water for moderately nonlinear beams.

The Impact of Air-Sea Interactions on the Representation of Tropical Precipitation Extremes

NASA Astrophysics Data System (ADS)

Hirons, L. C.; Klingaman, N. P.; Woolnough, S. J.

2018-02-01

The impacts of air-sea interactions on the representation of tropical precipitation extremes are investigated using an atmosphere-ocean-mixed-layer coupled model. The coupled model is compared to two atmosphere-only simulations driven by the coupled-model sea-surface temperatures (SSTs): one with 31 day running means (31 d), the other with a repeating mean annual cycle. This allows separation of the effects of interannual SST variability from those of coupled feedbacks on shorter timescales. Crucially, all simulations have a consistent mean state with very small SST biases against present-day climatology. 31d overestimates the frequency, intensity, and persistence of extreme tropical precipitation relative to the coupled model, likely due to excessive SST-forced precipitation variability. This implies that atmosphere-only attribution and time-slice experiments may overestimate the strength and duration of precipitation extremes. In the coupled model, air-sea feedbacks damp extreme precipitation, through negative local thermodynamic feedbacks between convection, surface fluxes, and SST.

Oscillatory brain responses in spoken word production reflect lexical frequency and sentential constraint.

PubMed

Piai, Vitória; Roelofs, Ardi; Maris, Eric

2014-01-01

Two fundamental factors affecting the speed of spoken word production are lexical frequency and sentential constraint, but little is known about their timing and electrophysiological basis. In the present study, we investigated event-related potentials (ERPs) and oscillatory brain responses induced by these factors, using a task in which participants named pictures after reading sentences. Sentence contexts were either constraining or nonconstraining towards the final word, which was presented as a picture. Picture names varied in their frequency of occurrence in the language. Naming latencies and electrophysiological responses were examined as a function of context and lexical frequency. Lexical frequency is an index of our cumulative learning experience with words, so lexical-frequency effects most likely reflect access to memory representations for words. Pictures were named faster with constraining than nonconstraining contexts. Associated with this effect, starting around 400 ms pre-picture presentation, oscillatory power between 8 and 30 Hz was lower for constraining relative to nonconstraining contexts. Furthermore, pictures were named faster with high-frequency than low-frequency names, but only for nonconstraining contexts, suggesting differential ease of memory access as a function of sentential context. Associated with the lexical-frequency effect, starting around 500 ms pre-picture presentation, oscillatory power between 4 and 10 Hz was higher for high-frequency than for low-frequency names, but only for constraining contexts. Our results characterise electrophysiological responses associated with lexical frequency and sentential constraint in spoken word production, and point to new avenues for studying these fundamental factors in language production. © 2013 Published by Elsevier Ltd.

Covariance-based direction-of-arrival estimation of wideband coherent chirp signals via sparse representation.

PubMed

Sha, Zhichao; Liu, Zhengmeng; Huang, Zhitao; Zhou, Yiyu

2013-08-29

This paper addresses the problem of direction-of-arrival (DOA) estimation of multiple wideband coherent chirp signals, and a new method is proposed. The new method is based on signal component analysis of the array output covariance, instead of the complicated time-frequency analysis used in previous literatures, and thus is more compact and effectively avoids possible signal energy loss during the hyper-processes. Moreover, the a priori information of signal number is no longer a necessity for DOA estimation in the new method. Simulation results demonstrate the performance superiority of the new method over previous ones.

Disease clusters, exact distributions of maxima, and P-values.

PubMed

Grimson, R C

1993-10-01

This paper presents combinatorial (exact) methods that are useful in the analysis of disease cluster data obtained from small environments, such as buildings and neighbourhoods. Maxwell-Boltzmann and Fermi-Dirac occupancy models are compared in terms of appropriateness of representation of disease incidence patterns (space and/or time) in these environments. The methods are illustrated by a statistical analysis of the incidence pattern of bone fractures in a setting wherein fracture clustering was alleged to be occurring. One of the methodological results derived in this paper is the exact distribution of the maximum cell frequency in occupancy models.

Application of a repetitive process setting to design of monotonically convergent iterative learning control

NASA Astrophysics Data System (ADS)

Boski, Marcin; Paszke, Wojciech

2015-11-01

This paper deals with the problem of designing an iterative learning control algorithm for discrete linear systems using repetitive process stability theory. The resulting design produces a stabilizing output feedback controller in the time domain and a feedforward controller that guarantees monotonic convergence in the trial-to-trial domain. The results are also extended to limited frequency range design specification. New design procedure is introduced in terms of linear matrix inequality (LMI) representations, which guarantee the prescribed performances of ILC scheme. A simulation example is given to illustrate the theoretical developments.

Wavelet Applications for Flight Flutter Testing

NASA Technical Reports Server (NTRS)

Lind, Rick; Brenner, Marty; Freudinger, Lawrence C.

1999-01-01

Wavelets present a method for signal processing that may be useful for analyzing responses of dynamical systems. This paper describes several wavelet-based tools that have been developed to improve the efficiency of flight flutter testing. One of the tools uses correlation filtering to identify properties of several modes throughout a flight test for envelope expansion. Another tool uses features in time-frequency representations of responses to characterize nonlinearities in the system dynamics. A third tool uses modulus and phase information from a wavelet transform to estimate modal parameters that can be used to update a linear model and reduce conservatism in robust stability margins.

EEG error potentials detection and classification using time-frequency features for robot reinforcement learning.

PubMed

Boubchir, Larbi; Touati, Youcef; Daachi, Boubaker; Chérif, Arab Ali

2015-08-01

In thought-based steering of robots, error potentials (ErrP) can appear when the action resulting from the brain-machine interface (BMI) classifier/controller does not correspond to the user's thought. Using the Steady State Visual Evoked Potentials (SSVEP) techniques, ErrP, which appear when a classification error occurs, are not easily recognizable by only examining the temporal or frequency characteristics of EEG signals. A supplementary classification process is therefore needed to identify them in order to stop the course of the action and back up to a recovery state. This paper presents a set of time-frequency (t-f) features for the detection and classification of EEG ErrP in extra-brain activities due to misclassification observed by a user exploiting non-invasive BMI and robot control in the task space. The proposed features are able to characterize and detect ErrP activities in the t-f domain. These features are derived from the information embedded in the t-f representation of EEG signals, and include the Instantaneous Frequency (IF), t-f information complexity, SVD information, energy concentration and sub-bands' energies. The experiment results on real EEG data show that the use of the proposed t-f features for detecting and classifying EEG ErrP achieved an overall classification accuracy up to 97% for 50 EEG segments using 2-class SVM classifier.

Reconstructing the spectrotemporal modulations of real-life sounds from fMRI response patterns

PubMed Central

Santoro, Roberta; Moerel, Michelle; De Martino, Federico; Valente, Giancarlo; Ugurbil, Kamil; Yacoub, Essa; Formisano, Elia

2017-01-01

Ethological views of brain functioning suggest that sound representations and computations in the auditory neural system are optimized finely to process and discriminate behaviorally relevant acoustic features and sounds (e.g., spectrotemporal modulations in the songs of zebra finches). Here, we show that modeling of neural sound representations in terms of frequency-specific spectrotemporal modulations enables accurate and specific reconstruction of real-life sounds from high-resolution functional magnetic resonance imaging (fMRI) response patterns in the human auditory cortex. Region-based analyses indicated that response patterns in separate portions of the auditory cortex are informative of distinctive sets of spectrotemporal modulations. Most relevantly, results revealed that in early auditory regions, and progressively more in surrounding regions, temporal modulations in a range relevant for speech analysis (∼2–4 Hz) were reconstructed more faithfully than other temporal modulations. In early auditory regions, this effect was frequency-dependent and only present for lower frequencies (<∼2 kHz), whereas for higher frequencies, reconstruction accuracy was higher for faster temporal modulations. Further analyses suggested that auditory cortical processing optimized for the fine-grained discrimination of speech and vocal sounds underlies this enhanced reconstruction accuracy. In sum, the present study introduces an approach to embed models of neural sound representations in the analysis of fMRI response patterns. Furthermore, it reveals that, in the human brain, even general purpose and fundamental neural processing mechanisms are shaped by the physical features of real-world stimuli that are most relevant for behavior (i.e., speech, voice). PMID:28420788

Stochastic shock response spectrum decomposition method based on probabilistic definitions of temporal peak acceleration, spectral energy, and phase lag distributions of mechanical impact pyrotechnic shock test data

NASA Astrophysics Data System (ADS)

Hwang, James Ho-Jin; Duran, Adam

2016-08-01

Most of the times pyrotechnic shock design and test requirements for space systems are provided in Shock Response Spectrum (SRS) without the input time history. Since the SRS does not describe the input or the environment, a decomposition method is used to obtain the source time history. The main objective of this paper is to develop a decomposition method producing input time histories that can satisfy the SRS requirement based on the pyrotechnic shock test data measured from a mechanical impact test apparatus. At the heart of this decomposition method is the statistical representation of the pyrotechnic shock test data measured from the MIT Lincoln Laboratory (LL) designed Universal Pyrotechnic Shock Simulator (UPSS). Each pyrotechnic shock test data measured at the interface of a test unit has been analyzed to produce the temporal peak acceleration, Root Mean Square (RMS) acceleration, and the phase lag at each band center frequency. Maximum SRS of each filtered time history has been calculated to produce a relationship between the input and the response. Two new definitions are proposed as a result. The Peak Ratio (PR) is defined as the ratio between the maximum SRS and the temporal peak acceleration at each band center frequency. The ratio between the maximum SRS and the RMS acceleration is defined as the Energy Ratio (ER) at each band center frequency. Phase lag is estimated based on the time delay between the temporal peak acceleration at each band center frequency and the peak acceleration at the lowest band center frequency. This stochastic process has been applied to more than one hundred pyrotechnic shock test data to produce probabilistic definitions of the PR, ER, and the phase lag. The SRS is decomposed at each band center frequency using damped sinusoids with the PR and the decays obtained by matching the ER of the damped sinusoids to the ER of the test data. The final step in this stochastic SRS decomposition process is the Monte Carlo (MC) simulation. The MC simulation identifies combinations of the PR and decays that can meet the SRS requirement at each band center frequency. Decomposed input time histories are produced by summing the converged damped sinusoids with the MC simulation of the phase lag distribution.

Encoding frequency contrast in primate auditory cortex

PubMed Central

Scott, Brian H.; Semple, Malcolm N.

2014-01-01

Changes in amplitude and frequency jointly determine much of the communicative significance of complex acoustic signals, including human speech. We have previously described responses of neurons in the core auditory cortex of awake rhesus macaques to sinusoidal amplitude modulation (SAM) signals. Here we report a complementary study of sinusoidal frequency modulation (SFM) in the same neurons. Responses to SFM were analogous to SAM responses in that changes in multiple parameters defining SFM stimuli (e.g., modulation frequency, modulation depth, carrier frequency) were robustly encoded in the temporal dynamics of the spike trains. For example, changes in the carrier frequency produced highly reproducible changes in shapes of the modulation period histogram, consistent with the notion that the instantaneous probability of discharge mirrors the moment-by-moment spectrum at low modulation rates. The upper limit for phase locking was similar across SAM and SFM within neurons, suggesting shared biophysical constraints on temporal processing. Using spike train classification methods, we found that neural thresholds for modulation depth discrimination are typically far lower than would be predicted from frequency tuning to static tones. This “dynamic hyperacuity” suggests a substantial central enhancement of the neural representation of frequency changes relative to the auditory periphery. Spike timing information was superior to average rate information when discriminating among SFM signals, and even when discriminating among static tones varying in frequency. This finding held even when differences in total spike count across stimuli were normalized, indicating both the primacy and generality of temporal response dynamics in cortical auditory processing. PMID:24598525

Giving dementia a face? The portrayal of older people with dementia in German weekly news magazines between the years 2000 and 2009.

PubMed

Kessler, Eva-Marie; Schwender, Clemens

2012-03-01

We investigated photographic depictions of older people with dementia in news magazines according to their frequency as well as observable characteristics of the characters. We examined all 2,604 photos appearing in articles identified using the key words "dementia" and "Alzheimer's" published in the 4 major German weekly news magazines between 2000 and 2009. According to the body text and/or the legend, 154 characters with dementia were identified. Trained judges rated the age and gender of each character as well as the emotional expression, physical functioning, physical surroundings, and social context of the characters. Visual representations of characters with dementia linearly increased across time (both in terms of absolute and relative figures). Women were shown more often than men. Young-old and old-old characters were depicted equally often. Characters were mostly depicted as having positive emotions and good functional health. A large majority of characters were shown in individualized contexts and together with social partners. Only 2 social partners displayed negative emotions, and he/she was a "helper" in less than one third of cases. Despite the overall low frequency of photos of older people with dementia, dementia seems to have "acquired a face" across the past decade. Although our analysis revealed a heterogeneous portrayal of older people with dementia, "positive" representations clearly prevailed.

The Benefits of Using Time-Frequency Analysis with Synthetic Aperture Focusing Technique

DOE Office of Scientific and Technical Information (OSTI.GOV)

Albright, Austin P; Clayton, Dwight A

2015-01-01

Improvements in detection and resolution are always desired and needed. There are various instruments available for the inspection of concrete structures that can be used with confidence for detecting different defects. However, more often than not that confidence is heavily dependent on the experience of the operator rather than the clear, objective discernibility of the output of the instrument. The challenge of objective discernment is amplified when the concrete structures contain multiple layers of reinforcement, are of significant thickness, or both, such as concrete structures in nuclear power plants. We seek to improve and extend the usefulness of results producedmore » using the synthetic aperture focusing technique (SAFT) on data collected from thick, complex concrete structures. A secondary goal is to improve existing SAFT results, with regards to repeatedly and objectively identifying defects and/or internal structure of concrete structures. Towards these goals, we are applying the time-frequency technique of wavelet packet decomposition and reconstruction using a mother wavelet that possesses the exact reconstruction property. However, instead of analyzing the coefficients of each decomposition node, we select and reconstruct specific nodes based on the frequency band it contains to produce a frequency band specific time-series representation. SAFT is then applied to these frequency specific reconstructions allowing SAFT to be used to visualize the reflectivity of a frequency band and that band s interaction with the contents of the concrete structure. We apply our technique to data sets collected using a commercial, ultrasonic linear array (MIRA) from two 1.5m x 2m x 25cm concrete test specimens. One specimen contains multiple layers of rebar. The other contains honeycomb, crack, and rebar bonding defect analogs. This approach opens up a multitude of possibilities for improved detection, readability, and overall improved objectivity. We will focus on improved defect/reinforcement isolation in thick and multilayered reinforcement environments. Additionally, the ability to empirically explore the possibility of a frequency-band-defect-type relationship or sensitivity becomes available.« less

The benefits of using time-frequency analysis with synthetic aperture focusing technique

DOE Office of Scientific and Technical Information (OSTI.GOV)

Albright, Austin, E-mail: albrightap@ornl.gov, E-mail: claytonda@ornl.gov; Clayton, Dwight, E-mail: albrightap@ornl.gov, E-mail: claytonda@ornl.gov

2015-03-31

Improvements in detection and resolution are always desired and needed. There are various instruments available for the inspection of concrete structures that can be used with confidence for detecting different defects. However, more often than not that confidence is heavily dependent on the experience of the operator rather than the clear, objective discernibility of the output of the instrument. The challenge of objective discernment is amplified when the concrete structures contain multiple layers of reinforcement, are of significant thickness, or both, such as concrete structures in nuclear power plants. We seek to improve and extend the usefulness of results producedmore » using the synthetic aperture focusing technique (SAFT) on data collected from thick, complex concrete structures. A secondary goal is to improve existing SAFT results, with regards to repeatedly and objectively identifying defects and/or internal structure of concrete structures. Towards these goals, we are applying the time-frequency technique of wavelet packet decomposition and reconstruction using a mother wavelet that possesses the exact reconstruction property. However, instead of analyzing the coefficients of each decomposition node, we select and reconstruct specific nodes based on the frequency band it contains to produce a frequency band specific time-series representation. SAFT is then applied to these frequency specific reconstructions allowing SAFT to be used to visualize the reflectivity of a frequency band and that band's interaction with the contents of the concrete structure. We apply our technique to data sets collected using a commercial, ultrasonic linear array (MIRA) from two 1.5m × 2m × 25cm concrete test specimens. One specimen contains multiple layers of rebar. The other contains honeycomb, crack, and rebar bonding defect analogs. This approach opens up a multitude of possibilities for improved detection, readability, and overall improved objectivity. We will focus on improved defect/reinforcement isolation in thick and multilayered reinforcement environments. Additionally, the ability to empirically explore the possibility of a frequency-band-defect-type relationship or sensitivity becomes available.« less

The benefits of using time-frequency analysis with synthetic aperture focusing technique

NASA Astrophysics Data System (ADS)

Albright, Austin; Clayton, Dwight

2015-03-01

Improvements in detection and resolution are always desired and needed. There are various instruments available for the inspection of concrete structures that can be used with confidence for detecting different defects. However, more often than not that confidence is heavily dependent on the experience of the operator rather than the clear, objective discernibility of the output of the instrument. The challenge of objective discernment is amplified when the concrete structures contain multiple layers of reinforcement, are of significant thickness, or both, such as concrete structures in nuclear power plants. We seek to improve and extend the usefulness of results produced using the synthetic aperture focusing technique (SAFT) on data collected from thick, complex concrete structures. A secondary goal is to improve existing SAFT results, with regards to repeatedly and objectively identifying defects and/or internal structure of concrete structures. Towards these goals, we are applying the time-frequency technique of wavelet packet decomposition and reconstruction using a mother wavelet that possesses the exact reconstruction property. However, instead of analyzing the coefficients of each decomposition node, we select and reconstruct specific nodes based on the frequency band it contains to produce a frequency band specific time-series representation. SAFT is then applied to these frequency specific reconstructions allowing SAFT to be used to visualize the reflectivity of a frequency band and that band's interaction with the contents of the concrete structure. We apply our technique to data sets collected using a commercial, ultrasonic linear array (MIRA) from two 1.5m × 2m × 25cm concrete test specimens. One specimen contains multiple layers of rebar. The other contains honeycomb, crack, and rebar bonding defect analogs. This approach opens up a multitude of possibilities for improved detection, readability, and overall improved objectivity. We will focus on improved defect/reinforcement isolation in thick and multilayered reinforcement environments. Additionally, the ability to empirically explore the possibility of a frequency-band-defect-type relationship or sensitivity becomes available.

Performance of the Wavelet Decomposition on Massively Parallel Architectures

NASA Technical Reports Server (NTRS)

El-Ghazawi, Tarek A.; LeMoigne, Jacqueline; Zukor, Dorothy (Technical Monitor)

2001-01-01

Traditionally, Fourier Transforms have been utilized for performing signal analysis and representation. But although it is straightforward to reconstruct a signal from its Fourier transform, no local description of the signal is included in its Fourier representation. To alleviate this problem, Windowed Fourier transforms and then wavelet transforms have been introduced, and it has been proven that wavelets give a better localization than traditional Fourier transforms, as well as a better division of the time- or space-frequency plane than Windowed Fourier transforms. Because of these properties and after the development of several fast algorithms for computing the wavelet representation of any signal, in particular the Multi-Resolution Analysis (MRA) developed by Mallat, wavelet transforms have increasingly been applied to signal analysis problems, especially real-life problems, in which speed is critical. In this paper we present and compare efficient wavelet decomposition algorithms on different parallel architectures. We report and analyze experimental measurements, using NASA remotely sensed images. Results show that our algorithms achieve significant performance gains on current high performance parallel systems, and meet scientific applications and multimedia requirements. The extensive performance measurements collected over a number of high-performance computer systems have revealed important architectural characteristics of these systems, in relation to the processing demands of the wavelet decomposition of digital images.

Cognitive strategies in the mental rotation task revealed by EEG spectral power.

PubMed

Gardony, Aaron L; Eddy, Marianna D; Brunyé, Tad T; Taylor, Holly A

2017-11-01

The classic mental rotation task (MRT; Shepard & Metzler, 1971) is commonly thought to measure mental rotation, a cognitive process involving covert simulation of motor rotation. Yet much research suggests that the MRT recruits both motor simulation and other analytic cognitive strategies that depend on visuospatial representation and visual working memory (WM). In the present study, we investigated cognitive strategies in the MRT using time-frequency analysis of EEG and independent component analysis. We scrutinized sensorimotor mu (µ) power reduction, associated with motor simulation, parietal alpha (pα) power reduction, associated with visuospatial representation, and frontal midline theta (fmθ) power enhancement, associated with WM maintenance and manipulation. µ power increased concomitant with increasing task difficulty, suggesting reduced use of motor simulation, while pα decreased and fmθ power increased, suggesting heightened use of visuospatial representation processing and WM, respectively. These findings suggest that MRT performance involves flexibly trading off between cognitive strategies, namely a motor simulation-based mental rotation strategy and WM-intensive analytic strategies based on task difficulty. Flexible cognitive strategy use may be a domain-general cognitive principle that underlies aptitude and spatial intelligence in a variety of cognitive domains. We close with discussion of the present study's implications as well as future directions. Published by Elsevier Inc.

Representing spatial structure through maps and language: Lord of the Rings encodes the spatial structure of middle Earth.

PubMed

Louwerse, Max M; Benesh, Nick

2012-01-01

Spatial mental representations can be derived from linguistic and non-linguistic sources of information. This study tested whether these representations could be formed from statistical linguistic frequencies of city names, and to what extent participants differed in their performance when they estimated spatial locations from language or maps. In a computational linguistic study, we demonstrated that co-occurrences of cities in Tolkien's Lord of the Rings trilogy and The Hobbit predicted the authentic longitude and latitude of those cities in Middle Earth. In a human study, we showed that human spatial estimates of the location of cities were very similar regardless of whether participants read Tolkien's texts or memorized a map of Middle Earth. However, text-based location estimates obtained from statistical linguistic frequencies better predicted the human text-based estimates than the human map-based estimates. These findings suggest that language encodes spatial structure of cities, and that human cognitive map representations can come from implicit statistical linguistic patterns, from explicit non-linguistic perceptual information, or from both. Copyright © 2012 Cognitive Science Society, Inc.

39 CFR 966.6 - Filing, docketing and serving documents; computation of time; representation of parties.

Code of Federal Regulations, 2010 CFR

2010-07-01

... business hours are between 8:15 a.m. and 4:45 p.m., eastern standard or daylight saving time as appropriate...; computation of time; representation of parties. 966.6 Section 966.6 Postal Service UNITED STATES POSTAL... time; representation of parties. (a) Filing. All documents required under this part must be filed by...

39 CFR 966.6 - Filing, docketing and serving documents; computation of time; representation of parties.

Code of Federal Regulations, 2011 CFR

2011-07-01

... business hours are between 8:15 a.m. and 4:45 p.m., eastern standard or daylight saving time as appropriate...; computation of time; representation of parties. 966.6 Section 966.6 Postal Service UNITED STATES POSTAL... time; representation of parties. (a) Filing. All documents required under this part must be filed by...

39 CFR 966.6 - Filing, docketing and serving documents; computation of time; representation of parties.

Code of Federal Regulations, 2012 CFR

2012-07-01

... business hours are between 8:15 a.m. and 4:45 p.m., eastern standard or daylight saving time as appropriate...; computation of time; representation of parties. 966.6 Section 966.6 Postal Service UNITED STATES POSTAL... time; representation of parties. (a) Filing. All documents required under this part must be filed by...

Wavelet-promoted sparsity for non-invasive reconstruction of electrical activity of the heart.

PubMed

Cluitmans, Matthijs; Karel, Joël; Bonizzi, Pietro; Volders, Paul; Westra, Ronald; Peeters, Ralf

2018-05-12

We investigated a novel sparsity-based regularization method in the wavelet domain of the inverse problem of electrocardiography that aims at preserving the spatiotemporal characteristics of heart-surface potentials. In three normal, anesthetized dogs, electrodes were implanted around the epicardium and body-surface electrodes were attached to the torso. Potential recordings were obtained simultaneously on the body surface and on the epicardium. A CT scan was used to digitize a homogeneous geometry which consisted of the body-surface electrodes and the epicardial surface. A novel multitask elastic-net-based method was introduced to regularize the ill-posed inverse problem. The method simultaneously pursues a sparse wavelet representation in time-frequency and exploits correlations in space. Performance was assessed in terms of quality of reconstructed epicardial potentials, estimated activation and recovery time, and estimated locations of pacing, and compared with performance of Tikhonov zeroth-order regularization. Results in the wavelet domain obtained higher sparsity than those in the time domain. Epicardial potentials were non-invasively reconstructed with higher accuracy than with Tikhonov zeroth-order regularization (p < 0.05), and recovery times were improved (p < 0.05). No significant improvement was found in terms of activation times and localization of origin of pacing. Next to improved estimation of recovery isochrones, which is important when assessing substrate for cardiac arrhythmias, this novel technique opens potentially powerful opportunities for clinical application, by allowing to choose wavelet bases that are optimized for specific clinical questions. Graphical Abstract The inverse problem of electrocardiography is to reconstruct heart-surface potentials from recorded bodysurface electrocardiograms (ECGs) and a torso-heart geometry. However, it is ill-posed and solving it requires additional constraints for regularization. We introduce a regularization method that simultaneously pursues a sparse wavelet representation in time-frequency and exploits correlations in space. Our approach reconstructs epicardial (heart-surface) potentials with higher accuracy than common methods. It also improves the reconstruction of recovery isochrones, which is important when assessing substrate for cardiac arrhythmias. This novel technique opens potentially powerful opportunities for clinical application, by allowing to choose wavelet bases that are optimized for specific clinical questions.

A possible role for a paralemniscal auditory pathway in the coding of slow temporal information

PubMed Central

Abrams, Daniel A.; Nicol, Trent; Zecker, Steven; Kraus, Nina

2010-01-01

Low frequency temporal information present in speech is critical for normal perception, however the neural mechanism underlying the differentiation of slow rates in acoustic signals is not known. Data from the rat trigeminal system suggest that the paralemniscal pathway may be specifically tuned to code low-frequency temporal information. We tested whether this phenomenon occurs in the auditory system by measuring the representation of temporal rate in lemniscal and paralemniscal auditory thalamus and cortex in guinea pig. Similar to the trigeminal system, responses measured in auditory thalamus indicate that slow rates are differentially represented in a paralemniscal pathway. In cortex, both lemniscal and paralemniscal neurons indicated sensitivity to slow rates. We speculate that a paralemniscal pathway in the auditory system may be specifically tuned to code low frequency temporal information present in acoustic signals. These data suggest that somatosensory and auditory modalities have parallel sub-cortical pathways that separately process slow rates and the spatial representation of the sensory periphery. PMID:21094680

Modeling chloride transport using travel time distributions at Plynlimon, Wales

NASA Astrophysics Data System (ADS)

Benettin, Paolo; Kirchner, James W.; Rinaldo, Andrea; Botter, Gianluca

2015-05-01

Here we present a theoretical interpretation of high-frequency, high-quality tracer time series from the Hafren catchment at Plynlimon in mid-Wales. We make use of the formulation of transport by travel time distributions to model chloride transport originating from atmospheric deposition and compute catchment-scale travel time distributions. The relevance of the approach lies in the explanatory power of the chosen tools, particularly to highlight hydrologic processes otherwise clouded by the integrated nature of the measured outflux signal. The analysis reveals the key role of residual storages that are poorly visible in the hydrological response, but are shown to strongly affect water quality dynamics. A significant accuracy in reproducing data is shown by our calibrated model. A detailed representation of catchment-scale travel time distributions has been derived, including the time evolution of the overall dispersion processes (which can be expressed in terms of time-varying storage sampling functions). Mean computed travel times span a broad range of values (from 80 to 800 days) depending on the catchment state. Results also suggest that, in the average, discharge waters are younger than storage water. The model proves able to capture high-frequency fluctuations in the measured chloride concentrations, which are broadly explained by the sharp transition between groundwaters and faster flows originating from topsoil layers. This article was corrected on 22 JUN 2015. See the end of the full text for details.

Incomplete data based parameter identification of nonlinear and time-variant oscillators with fractional derivative elements

NASA Astrophysics Data System (ADS)

Kougioumtzoglou, Ioannis A.; dos Santos, Ketson R. M.; Comerford, Liam

2017-09-01

Various system identification techniques exist in the literature that can handle non-stationary measured time-histories, or cases of incomplete data, or address systems following a fractional calculus modeling. However, there are not many (if any) techniques that can address all three aforementioned challenges simultaneously in a consistent manner. In this paper, a novel multiple-input/single-output (MISO) system identification technique is developed for parameter identification of nonlinear and time-variant oscillators with fractional derivative terms subject to incomplete non-stationary data. The technique utilizes a representation of the nonlinear restoring forces as a set of parallel linear sub-systems. In this regard, the oscillator is transformed into an equivalent MISO system in the wavelet domain. Next, a recently developed L1-norm minimization procedure based on compressive sensing theory is applied for determining the wavelet coefficients of the available incomplete non-stationary input-output (excitation-response) data. Finally, these wavelet coefficients are utilized to determine appropriately defined time- and frequency-dependent wavelet based frequency response functions and related oscillator parameters. Several linear and nonlinear time-variant systems with fractional derivative elements are used as numerical examples to demonstrate the reliability of the technique even in cases of noise corrupted and incomplete data.

Fidelity of the representation of value in decision-making

PubMed Central

Dowding, Ben A.

2017-01-01

The ability to make optimal decisions depends on evaluating the expected rewards associated with different potential actions. This process is critically dependent on the fidelity with which reward value information can be maintained in the nervous system. Here we directly probe the fidelity of value representation following a standard reinforcement learning task. The results demonstrate a previously-unrecognized bias in the representation of value: extreme reward values, both low and high, are stored significantly more accurately and precisely than intermediate rewards. The symmetry between low and high rewards pertained despite substantially higher frequency of exposure to high rewards, resulting from preferential exploitation of more rewarding options. The observed variation in fidelity of value representation retrospectively predicted performance on the reinforcement learning task, demonstrating that the bias in representation has an impact on decision-making. A second experiment in which one or other extreme-valued option was omitted from the learning sequence showed that representational fidelity is primarily determined by the relative position of an encoded value on the scale of rewards experienced during learning. Both variability and guessing decreased with the reduction in the number of options, consistent with allocation of a limited representational resource. These findings have implications for existing models of reward-based learning, which typically assume defectless representation of reward value. PMID:28248958

Aeroelastic Response of Swept Aircraft Wings in a Compressible Flow Field

NASA Technical Reports Server (NTRS)

Marzocca, Piergiovanni; Librescu, Liviu; Silva, Walter A.

2000-01-01

The present study addresses the subcritical aeroelastic response of swept wings, in various flight speed regimes, to arbitrary time-dependent external excitations. The methodology based on the concept of indicial functions is carried out in time and frequency domains. As a result of this approach, the proper unsteady aerodynamic loads necessary to study the subcritical aeroelastic response of the open/closed loop aeroelastic systems, and of flutter instability, respectively are obtained. Validation of the aeroelastic model is provided, and applications to subcritical aeroelastic response to blast pressure signatures are illustrated. In this context, an original representation of the aeroelastic response in the phase-space is displayed, and pertinent conclusions on the implications of a number of selected parameters of the system are outlined.

A simple filter circuit for denoising biomechanical impact signals.

PubMed

Subramaniam, Suba R; Georgakis, Apostolos

2009-01-01

We present a simple scheme for denoising non-stationary biomechanical signals with the aim of accurately estimating their second derivative (acceleration). The method is based on filtering in fractional Fourier domains using well-known low-pass filters in a way that amounts to a time-varying cut-off threshold. The resulting algorithm is linear and its design is facilitated by the relationship between the fractional Fourier transform and joint time-frequency representations. The implemented filter circuit employs only three low-order filters while its efficiency is further supported by the low computational complexity of the fractional Fourier transform. The results demonstrate that the proposed method can denoise the signals effectively and is more robust against noise as compared to conventional low-pass filters.

EEG-Based Brain-Computer Interface for Decoding Motor Imagery Tasks within the Same Hand Using Choi-Williams Time-Frequency Distribution

PubMed Central

Alwanni, Hisham; Baslan, Yara; Alnuman, Nasim; Daoud, Mohammad I.

2017-01-01

This paper presents an EEG-based brain-computer interface system for classifying eleven motor imagery (MI) tasks within the same hand. The proposed system utilizes the Choi-Williams time-frequency distribution (CWD) to construct a time-frequency representation (TFR) of the EEG signals. The constructed TFR is used to extract five categories of time-frequency features (TFFs). The TFFs are processed using a hierarchical classification model to identify the MI task encapsulated within the EEG signals. To evaluate the performance of the proposed approach, EEG data were recorded for eighteen intact subjects and four amputated subjects while imagining to perform each of the eleven hand MI tasks. Two performance evaluation analyses, namely channel- and TFF-based analyses, are conducted to identify the best subset of EEG channels and the TFFs category, respectively, that enable the highest classification accuracy between the MI tasks. In each evaluation analysis, the hierarchical classification model is trained using two training procedures, namely subject-dependent and subject-independent procedures. These two training procedures quantify the capability of the proposed approach to capture both intra- and inter-personal variations in the EEG signals for different MI tasks within the same hand. The results demonstrate the efficacy of the approach for classifying the MI tasks within the same hand. In particular, the classification accuracies obtained for the intact and amputated subjects are as high as 88.8% and 90.2%, respectively, for the subject-dependent training procedure, and 80.8% and 87.8%, respectively, for the subject-independent training procedure. These results suggest the feasibility of applying the proposed approach to control dexterous prosthetic hands, which can be of great benefit for individuals suffering from hand amputations. PMID:28832513

CoSMoMVPA: Multi-Modal Multivariate Pattern Analysis of Neuroimaging Data in Matlab/GNU Octave.

PubMed

Oosterhof, Nikolaas N; Connolly, Andrew C; Haxby, James V

2016-01-01

Recent years have seen an increase in the popularity of multivariate pattern (MVP) analysis of functional magnetic resonance (fMRI) data, and, to a much lesser extent, magneto- and electro-encephalography (M/EEG) data. We present CoSMoMVPA, a lightweight MVPA (MVP analysis) toolbox implemented in the intersection of the Matlab and GNU Octave languages, that treats both fMRI and M/EEG data as first-class citizens. CoSMoMVPA supports all state-of-the-art MVP analysis techniques, including searchlight analyses, classification, correlations, representational similarity analysis, and the time generalization method. These can be used to address both data-driven and hypothesis-driven questions about neural organization and representations, both within and across: space, time, frequency bands, neuroimaging modalities, individuals, and species. It uses a uniform data representation of fMRI data in the volume or on the surface, and of M/EEG data at the sensor and source level. Through various external toolboxes, it directly supports reading and writing a variety of fMRI and M/EEG neuroimaging formats, and, where applicable, can convert between them. As a result, it can be integrated readily in existing pipelines and used with existing preprocessed datasets. CoSMoMVPA overloads the traditional volumetric searchlight concept to support neighborhoods for M/EEG and surface-based fMRI data, which supports localization of multivariate effects of interest across space, time, and frequency dimensions. CoSMoMVPA also provides a generalized approach to multiple comparison correction across these dimensions using Threshold-Free Cluster Enhancement with state-of-the-art clustering and permutation techniques. CoSMoMVPA is highly modular and uses abstractions to provide a uniform interface for a variety of MVP measures. Typical analyses require a few lines of code, making it accessible to beginner users. At the same time, expert programmers can easily extend its functionality. CoSMoMVPA comes with extensive documentation, including a variety of runnable demonstration scripts and analysis exercises (with example data and solutions). It uses best software engineering practices including version control, distributed development, an automated test suite, and continuous integration testing. It can be used with the proprietary Matlab and the free GNU Octave software, and it complies with open source distribution platforms such as NeuroDebian. CoSMoMVPA is Free/Open Source Software under the permissive MIT license. Website: http://cosmomvpa.org Source code: https://github.com/CoSMoMVPA/CoSMoMVPA.

CoSMoMVPA: Multi-Modal Multivariate Pattern Analysis of Neuroimaging Data in Matlab/GNU Octave

PubMed Central

Oosterhof, Nikolaas N.; Connolly, Andrew C.; Haxby, James V.

2016-01-01

Recent years have seen an increase in the popularity of multivariate pattern (MVP) analysis of functional magnetic resonance (fMRI) data, and, to a much lesser extent, magneto- and electro-encephalography (M/EEG) data. We present CoSMoMVPA, a lightweight MVPA (MVP analysis) toolbox implemented in the intersection of the Matlab and GNU Octave languages, that treats both fMRI and M/EEG data as first-class citizens. CoSMoMVPA supports all state-of-the-art MVP analysis techniques, including searchlight analyses, classification, correlations, representational similarity analysis, and the time generalization method. These can be used to address both data-driven and hypothesis-driven questions about neural organization and representations, both within and across: space, time, frequency bands, neuroimaging modalities, individuals, and species. It uses a uniform data representation of fMRI data in the volume or on the surface, and of M/EEG data at the sensor and source level. Through various external toolboxes, it directly supports reading and writing a variety of fMRI and M/EEG neuroimaging formats, and, where applicable, can convert between them. As a result, it can be integrated readily in existing pipelines and used with existing preprocessed datasets. CoSMoMVPA overloads the traditional volumetric searchlight concept to support neighborhoods for M/EEG and surface-based fMRI data, which supports localization of multivariate effects of interest across space, time, and frequency dimensions. CoSMoMVPA also provides a generalized approach to multiple comparison correction across these dimensions using Threshold-Free Cluster Enhancement with state-of-the-art clustering and permutation techniques. CoSMoMVPA is highly modular and uses abstractions to provide a uniform interface for a variety of MVP measures. Typical analyses require a few lines of code, making it accessible to beginner users. At the same time, expert programmers can easily extend its functionality. CoSMoMVPA comes with extensive documentation, including a variety of runnable demonstration scripts and analysis exercises (with example data and solutions). It uses best software engineering practices including version control, distributed development, an automated test suite, and continuous integration testing. It can be used with the proprietary Matlab and the free GNU Octave software, and it complies with open source distribution platforms such as NeuroDebian. CoSMoMVPA is Free/Open Source Software under the permissive MIT license. Website: http://cosmomvpa.org Source code: https://github.com/CoSMoMVPA/CoSMoMVPA PMID:27499741

Affective and contextual values modulate spatial frequency use in object recognition

PubMed Central

Caplette, Laurent; West, Gregory; Gomot, Marie; Gosselin, Frédéric; Wicker, Bruno

2014-01-01

Visual object recognition is of fundamental importance in our everyday interaction with the environment. Recent models of visual perception emphasize the role of top-down predictions facilitating object recognition via initial guesses that limit the number of object representations that need to be considered. Several results suggest that this rapid and efficient object processing relies on the early extraction and processing of low spatial frequencies (LSF). The present study aimed to investigate the SF content of visual object representations and its modulation by contextual and affective values of the perceived object during a picture-name verification task. Stimuli consisted of pictures of objects equalized in SF content and categorized as having low or high affective and contextual values. To access the SF content of stored visual representations of objects, SFs of each image were then randomly sampled on a trial-by-trial basis. Results reveal that intermediate SFs between 14 and 24 cycles per object (2.3–4 cycles per degree) are correlated with fast and accurate identification for all categories of objects. Moreover, there was a significant interaction between affective and contextual values over the SFs correlating with fast recognition. These results suggest that affective and contextual values of a visual object modulate the SF content of its internal representation, thus highlighting the flexibility of the visual recognition system. PMID:24904514

Bounded diffusion impedance characterization of battery electrodes using fractional modeling

NASA Astrophysics Data System (ADS)

Gabano, Jean-Denis; Poinot, Thierry; Huard, Benoît

2017-06-01

This article deals with the ability of fractional modeling to describe the bounded diffusion behavior encountered in modern thin film and nanoparticles lithium battery electrodes. Indeed, the diffusion impedance of such batteries behaves as a half order integrator characterized by the Warburg impedance at high frequencies and becomes a classical integrator described by a capacitor at low frequencies. The transition between these two behaviors depends on the particles geometry. Three of them will be considered in this paper: planar, cylindrical and spherical ones. The fractional representation proposed is a gray box model able to perfectly fit the low and high frequency diffusive impedance behaviors while optimizing the frequency response transition. Identification results are provided using frequential simulation data considering the three electrochemical diffusion models based on the particles geometry. Furthermore, knowing this geometry allows to estimate the diffusion ionic resistance and time constant using the relationships linking these physical parameters to the structural fractional model parameters. Finally, other simulations using Randles impedance models including the charge transfer impedance and the external resistance demonstrate the interest of fractional modeling in order to identify properly not only the charge transfer impedance but also the diffusion physical parameters whatever the particles geometry.

Time-frequency analysis to a particular type of scattering problems involving metallic-polymer tubing structures.

PubMed

Elhanaoui, Abdelkader; Aassif, Elhoucein; Maze, Gérard; Décultot, Dominique

2018-01-01

In this paper, recent studies of backscattered acoustic signals in thinner steel-polymer tubing structures have been presented. Reassigned smoothed pseudo Wigner-Ville (rspWV) analysis has been adopted in order to diminish the cross-term effect, and achieve high resolution spectral. Vibration modes, which are associated to the resonances of circumferential waves, have been determined by using the modal isolation plan representation. At normalized frequencies below 140, an appreciable influence from the polymer coating thickness on the A 0 + and S 0 modes has been noticed. Furthermore, the trajectory of the A 0 - wave has been modified in the normalized frequency band 40-42. Group velocity curves of the A 0 - wave have, then, been graphically illustrated. The findings have shown a particular curvature change at reduced frequency 41 in the case of an immersed two-layer tube in water. Studies of acoustic backscattering involving steel-polymer tubing structures have confirmed the significant coupling of A 0 + and S 0 waves. Besides, the disappearance of the A 0 + resonance trajectory has been observed; which is a very important phenomenon to understand. Copyright © 2017 Elsevier B.V. All rights reserved.

Design Considerations for Aural Vital Signs Using PZT Piezoelectric Ceramics Sensor Based on the Computerization Method.

PubMed

Noimanee, Suranan; Tunkasiri, Tawee; Siriwitayakorn, Kingkeo; Tantrakoon, Jerapong

2007-11-11

The purpose was to illustrate how system developed for measurement of the aural vital signs such as patient's heart and lung sounds in the hospital. For heart sounds measurement must operate the frequency response between 20 - 800 Hz, and lung sounds measurement must operate the frequency response between 160 - 4,000 Hz. The method was designed PZT piezoelectric ceramics for both frequency response in the same PZT sensor. It converts a signal from aural vital sign form to voltage signal. The signal is suitably amplified and re-filtered in band pass frequency band. It is converted to digital signal by an analog to digital conversion circuitry developed for the purpose. The results were that all signals can fed to personal computer through the sound card port. With the supporting software for drawing of graphic on the screen, the signal for a specific duration is accessed and stored in the computer's memory in term of each patient's data. In conclusion, the data of each patient call dot pcg (.pcg) for drawing graph and dot wave (.wave) for sound listening or automatic sending via electronic mail to the physician for later analysis of interpreting the sounds on the basis of their time domain and frequency domain representation to diagnose heart disorders.

Inside stories: maternal representations of first time mothers from pre-pregnancy to early pregnancy.

PubMed

Hopkins, Julia; Clarke, David; Cross, Wendy

2014-03-01

According to the psychoanalytical literature, it is during pregnancy that maternal representations of the mother-infant relationship become activated. Midwives who are engaged with the mother and the baby have not drawn upon this concept in their practice. In order for this to happen, it is important to understand better the nature of maternal representations and when they are activated from empirical studies. The research question is: what are the maternal representations of a group of first time mothers from pre-pregnancy, early pregnancy and to the first ultrasound. A narrative approach was used to gain insight into the maternal representations of first time pregnant womens' account of their representations. The analysis method was based on thematic approach. Fifteen women aged between 23 and 38 years. A midwives clinic attached to a tertiary hospital in Melbourne, Australia. First-time pregnant women's maternal representations were activated when a woman begins to plan her pregnancy ('the time is right'), again at the onset of physical changes to her body as a result of conception ('my body is changing'), and at the first early ultrasound at around twelve weeks ('it' is a real baby). Maternal representations are important for the midwife and pregnant women because this concept provides another understanding in relation to the psychological dimension of pregnancy. Copyright © 2013 Australian College of Midwives. Published by Elsevier Ltd. All rights reserved.

High-temperature ratchets with sawtooth potentials

NASA Astrophysics Data System (ADS)

Rozenbaum, Viktor M.; Shapochkina, Irina V.; Sheu, Sheh-Yi; Yang, Dah-Yen; Lin, Sheng Hsien

2016-11-01

The concept of the effective potential is suggested as an efficient instrument to get a uniform analytical description of stochastic high-temperature on-off flashing and rocking ratchets. The analytical representation for the average particle velocity, obtained within this technique, allows description of ratchets with sharp potentials (and potentials with jumps in particular). For sawtooth potentials, the explicit analytical expressions for the average velocity of on-off flashing and rocking ratchets valid for arbitrary frequencies of potential energy fluctuations are derived; the difference in their high-frequency asymptotics is explored for the smooth and cusped profiles, and profiles with jumps. The origin of the difference as well as the appearance of the jump behavior in ratchet characteristics are interpreted in terms of self-similar universal solutions which give the continuous description of the effect. It is shown how the jump behavior in motor characteristics arises from the competition between the characteristic times of the system.

A note on the resonant interaction between a surface wave and two interfacial waves

NASA Astrophysics Data System (ADS)

Jamali, Mirmosadegh; Lawrence, Gregory A.; Seymour, Brian

2003-09-01

Hill & Foda (1998) and Jamali (1998) have presented theoretical and experimental studies of the resonant interaction between a surface wave and two oblique interfacial waves. Despite many similarities between the findings there is one seemingly major difference. Hill & Foda's (1998) analysis indicated that there are only narrow bands of frequency, density ratio and direction angle within which growth is possible. On the other hand, Jamali (1998) predicted and observed wave growth over wide ranges of frequency and direction angle, and for all the density ratios that he investigated. We show that Hill & Foda's (1998) second-order representation of the dynamic interfacial boundary condition is missing a term proportional to the time derivative of the square of the velocity shear across the interface. When this missing term is included in the analysis, the resulting predictions are consistent with the laboratory experiments.

Specific contributions of basal ganglia and cerebellum to the neural tracking of rhythm.

PubMed

Nozaradan, Sylvie; Schwartze, Michael; Obermeier, Christian; Kotz, Sonja A

2017-10-01

How specific brain networks track rhythmic sensory input over time remains a challenge in neuroimaging work. Here we show that subcortical areas, namely the basal ganglia and the cerebellum, specifically contribute to the neural tracking of rhythm. We tested patients with focal lesions in either of these areas and healthy controls by means of electroencephalography (EEG) while they listened to rhythmic sequences known to induce selective neural tracking at a frequency corresponding to the most-often perceived pulse-like beat. Both patients and controls displayed neural responses to the rhythmic sequences. However, these response patterns were different across groups, with patients showing reduced tracking at beat frequency, especially for the more challenging rhythms. In the cerebellar patients, this effect was specific to the rhythm played at a fast tempo, which places high demands on the temporally precise encoding of events. In contrast, basal ganglia patients showed more heterogeneous responses at beat frequency specifically for the most complex rhythm, which requires more internal generation of the beat. These findings provide electrophysiological evidence that these subcortical structures selectively shape the neural representation of rhythm. Moreover, they suggest that the processing of rhythmic auditory input relies on an extended cortico-subcortico-cortical functional network providing specific timing and entrainment sensitivities. Copyright © 2017 Elsevier Ltd. All rights reserved.

The role of physical digit representation and numerical magnitude representation in children's multiplication fact retrieval.

PubMed

De Visscher, Alice; Noël, Marie-Pascale; De Smedt, Bert

2016-12-01

Arithmetic facts, in particular multiplication tables, are thought to be stored in long-term memory and to be interference prone. At least two representations underpinning these arithmetic facts have been suggested: a physical representation of the digits and a numerical magnitude representation. We hypothesized that both representations are possible sources of interference that could explain individual differences in multiplication fact performance and/or in strategy use. We investigated the specificity of these interferences on arithmetic fact retrieval and explored the relation between interference and performance on the different arithmetic operations and on general mathematics achievement. Participants were 79 fourth-grade children (M age =9.6 years) who completed a products comparison and a multiplication production task with verbal strategy reports. Performances on a speeded calculation test including the four operations and on a general mathematics achievement test were also collected. Only the interference coming from physical representations was a significant predictor of the performance across multiplications. However, both the magnitude and physical representations were unique predictors of individual differences in multiplication. The frequency of the retrieval strategy across multiplication problems and across individuals was determined only by the physical representation, which therefore is suggested as being responsible for memory storage issues. Interestingly, this impact of physical representation was not observed when predicting performance on subtraction or on general mathematical achievement. In contrast, the impact of the numerical magnitude representation was more general in that it was observed across all arithmetic operations and in general mathematics achievement. Copyright © 2016 Elsevier Inc. All rights reserved.

Benefits of fading in perceptual learning are driven by more than dimensional attention.

PubMed

Wisniewski, Matthew G; Radell, Milen L; Church, Barbara A; Mercado, Eduardo

2017-01-01

Individuals learn to classify percepts effectively when the task is initially easy and then gradually increases in difficulty. Some suggest that this is because easy-to-discriminate events help learners focus attention on discrimination-relevant dimensions. Here, we tested whether such attentional-spotlighting accounts are sufficient to explain easy-to-hard effects in auditory perceptual learning. In two experiments, participants were trained to discriminate periodic, frequency-modulated (FM) tones in two separate frequency ranges (300-600 Hz or 3000-6000 Hz). In one frequency range, sounds gradually increased in similarity as training progressed. In the other, stimulus similarity was constant throughout training. After training, participants showed better performance in their progressively trained frequency range, even though the discrimination-relevant dimension across ranges was the same. Learning theories that posit experience-dependent changes in stimulus representations and/or the strengthening of associations with differential responses, predict the observed specificity of easy-to-hard effects, whereas attentional-spotlighting theories do not. Calibrating the difficulty and temporal sequencing of training experiences to support more incremental representation-based learning can enhance the effectiveness of practice beyond any benefits gained from explicitly highlighting relevant dimensions.

[Some aspects of animal-to-human approximation of low frequency electromagnetic field exposure conditions].

PubMed

Vasin, A L

2003-01-01

Appropriateness of representation of a biological object surface as an equipotential surface has been proved for conditions of a quasistatic exposure to EMF of frequencies lower than 1 MHz. The conditions, at which a self capacitance of a biological object is its basic electrical parameter, have been considered. A factor of animal-to-human approximation of low-frequency EMF exposure conditions was estimated on the basis of equal dose loading in biological objects of different geometric sizes.

Redundant binary number representation for an inherently parallel arithmetic on optical computers.

PubMed

De Biase, G A; Massini, A

1993-02-10

A simple redundant binary number representation suitable for digital-optical computers is presented. By means of this representation it is possible to build an arithmetic with carry-free parallel algebraic sums carried out in constant time and parallel multiplication in log N time. This redundant number representation naturally fits the 2's complement binary number system and permits the construction of inherently parallel arithmetic units that are used in various optical technologies. Some properties of this number representation and several examples of computation are presented.

EliXR-TIME: A Temporal Knowledge Representation for Clinical Research Eligibility Criteria.

PubMed

Boland, Mary Regina; Tu, Samson W; Carini, Simona; Sim, Ida; Weng, Chunhua

2012-01-01

Effective clinical text processing requires accurate extraction and representation of temporal expressions. Multiple temporal information extraction models were developed but a similar need for extracting temporal expressions in eligibility criteria (e.g., for eligibility determination) remains. We identified the temporal knowledge representation requirements of eligibility criteria by reviewing 100 temporal criteria. We developed EliXR-TIME, a frame-based representation designed to support semantic annotation for temporal expressions in eligibility criteria by reusing applicable classes from well-known clinical temporal knowledge representations. We used EliXR-TIME to analyze a training set of 50 new temporal eligibility criteria. We evaluated EliXR-TIME using an additional random sample of 20 eligibility criteria with temporal expressions that have no overlap with the training data, yielding 92.7% (76 / 82) inter-coder agreement on sentence chunking and 72% (72 / 100) agreement on semantic annotation. We conclude that this knowledge representation can facilitate semantic annotation of the temporal expressions in eligibility criteria.

The Effect of Two-dimensional and Stereoscopic Presentation on Middle School Students' Performance of Spatial Cognition Tasks

NASA Astrophysics Data System (ADS)

Price, Aaron; Lee, Hee-Sun

2010-02-01

We investigated whether and how student performance on three types of spatial cognition tasks differs when worked with two-dimensional or stereoscopic representations. We recruited nineteen middle school students visiting a planetarium in a large Midwestern American city and analyzed their performance on a series of spatial cognition tasks in terms of response accuracy and task completion time. Results show that response accuracy did not differ between the two types of representations while task completion time was significantly greater with the stereoscopic representations. The completion time increased as the number of mental manipulations of 3D objects increased in the tasks. Post-interviews provide evidence that some students continued to think of stereoscopic representations as two-dimensional. Based on cognitive load and cue theories, we interpret that, in the absence of pictorial depth cues, students may need more time to be familiar with stereoscopic representations for optimal performance. In light of these results, we discuss potential uses of stereoscopic representations for science learning.

Stimulus sequence context differentially modulates inhibition-related theta and delta band activity in a go/nogo task

PubMed Central

Harper, Jeremy; Malone, Stephen M.; Bachman, Matthew D.; Bernat, Edward M.

2015-01-01

Recent work suggests that dissociable activity in theta and delta frequency bands underlies several common event-related potential (ERP) components, including the nogo N2/P3 complex, which can better index separable functional processes than traditional time-domain measures. Reports have also demonstrated that neural activity can be affected by stimulus sequence context information (i.e., the number and type of preceding stimuli). Stemming from prior work demonstrating that theta and delta index separable processes during response inhibition, the current study assessed sequence context in a Go/Nogo paradigm in which the number of go stimuli preceding each nogo was selectively manipulated. Principal component analysis (PCA) of time-frequency representations revealed differential modulation of evoked theta and delta related to sequence context, where delta increased robustly with additional preceding go stimuli, while theta did not. Findings are consistent with the view that theta indexes simpler initial salience-related processes, while delta indexes more varied and complex processes related to a variety of task parameters. PMID:26751830

Linearized self-consistent quasiparticle GW method: Application to semiconductors and simple metals

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kutepov, A. L.; Oudovenko, V. S.; Kotliar, G.

We present a code implementing the linearized self-consistent quasiparticle GW method (QSGW) in the LAPW basis. Our approach is based on the linearization of the self-energy around zero frequency which differs it from the existing implementations of the QSGW method. The linearization allows us to use Matsubara frequencies instead of working on the real axis. This results in efficiency gains by switching to the imaginary time representation in the same way as in the space time method. The all electron LAPW basis set eliminates the need for pseudopotentials. We discuss the advantages of our approach, such as its N 3more » scaling with the system size N, as well as its shortcomings. We apply our approach to study the electronic properties of selected semiconductors, insulators, and simple metals and show that our code produces the results very close to the previously published QSGW data. Our implementation is a good platform for further many body diagrammatic resummations such as the vertex-corrected GW approach and the GW+DMFT method.« less

Analysis of the ν 12 Band of Ethylene- 13C 2 by High-Resolution FTIR Spectroscopy

NASA Astrophysics Data System (ADS)

Tan, T. L.; Goh, K. L.; Ong, P. P.; Teo, H. H.

2001-06-01

The Fourier transform infrared (FTIR) spectrum of the ν12 fundamental band of ethylene-13C2 (13C2H4) was recorded with an unapodized resolution of 0.004 cm-1 in the frequency range from 1380 to 1500 cm-1. Rovibrational constants for the upper state (ν12=1) up to five quartic and three sextic centrifugal distortion terms were derived for the first time by assigning and fitting a total of 1177 infrared transitions using a Watson's A-reduced Hamiltonian in the Ir representation. The rms deviation of the fit was 0.00045 cm-1. The ground state rovibrational constants were also determined for the first time by a fit of 738 combination differences from the present infrared measurements, with a rms deviation of 0.00060 cm-1. The A-type ν12 band with a band center at 1436.65411±0.00005 cm-1 was found to be relatively free from local frequency perturbations. The inertial defect Δ12 was found to be 0.24300±0.00002 uÅ2.

Linearized self-consistent quasiparticle GW method: Application to semiconductors and simple metals

DOE PAGES

Kutepov, A. L.; Oudovenko, V. S.; Kotliar, G.

2017-06-23

We present a code implementing the linearized self-consistent quasiparticle GW method (QSGW) in the LAPW basis. Our approach is based on the linearization of the self-energy around zero frequency which differs it from the existing implementations of the QSGW method. The linearization allows us to use Matsubara frequencies instead of working on the real axis. This results in efficiency gains by switching to the imaginary time representation in the same way as in the space time method. The all electron LAPW basis set eliminates the need for pseudopotentials. We discuss the advantages of our approach, such as its N 3more » scaling with the system size N, as well as its shortcomings. We apply our approach to study the electronic properties of selected semiconductors, insulators, and simple metals and show that our code produces the results very close to the previously published QSGW data. Our implementation is a good platform for further many body diagrammatic resummations such as the vertex-corrected GW approach and the GW+DMFT method.« less

Target recognition based on the moment functions of radar signatures

NASA Astrophysics Data System (ADS)

Kim, Kyung-Tae; Kim, Hyo-Tae

2002-03-01

In this paper, we present the results of target recognition research based on the moment functions of various radar signatures, such as time-frequency signatures, range profiles, and scattering centers. The proposed approach utilizes geometrical moments or central moments of the obtained radar signatures. In particular, we derived exact and closed form expressions of the geometrical moments of the adaptive Gaussian representation (AGR), which is one of the adaptive joint time-frequency techniques, and also computed the central moments of range profiles and one-dimensional (1-D) scattering centers on a target, which are obtained by various super-resolution techniques. The obtained moment functions are further processed to provide small dimensional and redundancy-free feature vectors, and classified via a neural network approach or a Bayes classifier. The performances of the proposed technique are demonstrated using a simulated radar cross section (RCS) data set, or a measured RCS data set of various scaled aircraft models, obtained at the Pohang University of Science and Technology (POSTECH) compact range facility. Results show that the techniques in this paper can not only provide reliable classification accuracy, but also save computational resources.

Dynamics of Sensorimotor Oscillations in a Motor Task

NASA Astrophysics Data System (ADS)

Pfurtscheller, Gert; Neuper, Christa

Many BCI systems rely on imagined movement. The brain activity associated with real or imagined movement produces reliable changes in the EEG. Therefore, many people can use BCI systems by imagining movements to convey information. The EEG has many regular rhythms. The most famous are the occipital alpha rhythm and the central mu and beta rhythms. People can desynchronize the alpha rhythm (that is, produce weaker alpha activity) by being alert, and can increase alpha activity by closing their eyes and relaxing. Sensory processing or motor behavior leads to EEG desynchronization or blocking of central beta and mu rhythms, as originally reported by Berger [1], Jasper and Andrew [2] and Jasper and Penfield [3]. This desynchronization reflects a decrease of oscillatory activity related to an internally or externally-paced event and is known as Event-Related Desynchronization (ERD, [4]). The opposite, namely the increase of rhythmic activity, was termed Event-Related Synchronization (ERS, [5]). ERD and ERS are characterized by fairly localized topography and frequency specificity [6]. Both phenomena can be studied through topographiuthc maps, time courses, and time-frequency representations (ERD maps, [7]).

Peripheral facial nerve lesions induce changes in the firing properties of primary motor cortex layer 5 pyramidal cells.

PubMed

Múnera, A; Cuestas, D M; Troncoso, J

2012-10-25

Facial nerve lesions elicit long-lasting changes in vibrissal primary motor cortex (M1) muscular representation in rodents. Reorganization of cortical representation has been attributed to potentiation of preexisting horizontal connections coming from neighboring muscle representation. However, changes in layer 5 pyramidal neuron activity induced by facial nerve lesion have not yet been explored. To do so, the effect of irreversible facial nerve injury on electrophysiological properties of layer 5 pyramidal neurons was characterized. Twenty-four adult male Wistar rats were randomly subjected to two experimental treatments: either surgical transection of mandibular and buccal branches of the facial nerve (n=18) or sham surgery (n=6). Unitary and population activity of vibrissal M1 layer 5 pyramidal neurons recorded in vivo under general anesthesia was compared between sham-operated and facial nerve-injured animals. Injured animals were allowed either one (n=6), three (n=6), or five (n=6) weeks recovery before recording in order to characterize the evolution of changes in electrophysiological activity. As compared to control, facial nerve-injured animals displayed the following sustained and significant changes in spontaneous activity: increased basal firing frequency, decreased spike-associated local field oscillation amplitude, and decreased spontaneous theta burst firing frequency. Significant changes in evoked-activity with whisker pad stimulation included: increased short latency population spike amplitude, decreased long latency population oscillations amplitude and frequency, and decreased peak frequency during evoked single-unit burst firing. Taken together, such changes demonstrate that peripheral facial nerve lesions induce robust and sustained changes of layer 5 pyramidal neurons in vibrissal motor cortex. Copyright © 2012 IBRO. Published by Elsevier Ltd. All rights reserved.

Neuroimaging paradigms for tonotopic mapping (II): the influence of acquisition protocol.

PubMed

Langers, Dave R M; Sanchez-Panchuelo, Rosa M; Francis, Susan T; Krumbholz, Katrin; Hall, Deborah A

2014-10-15

Numerous studies on the tonotopic organisation of auditory cortex in humans have employed a wide range of neuroimaging protocols to assess cortical frequency tuning. In the present functional magnetic resonance imaging (fMRI) study, we made a systematic comparison between acquisition protocols with variable levels of interference from acoustic scanner noise. Using sweep stimuli to evoke travelling waves of activation, we measured sound-evoked response signals using sparse, clustered, and continuous imaging protocols that were characterised by inter-scan intervals of 8.8, 2.2, or 0.0 s, respectively. With regard to sensitivity to sound-evoked activation, the sparse and clustered protocols performed similarly, and both detected more activation than the continuous method. Qualitatively, tonotopic maps in activated areas proved highly similar, in the sense that the overall pattern of tonotopic gradients was reproducible across all three protocols. However, quantitatively, we observed substantial reductions in response amplitudes to moderately low stimulus frequencies that coincided with regions of strong energy in the scanner noise spectrum for the clustered and continuous protocols compared to the sparse protocol. At the same time, extreme frequencies became over-represented for these two protocols, and high best frequencies became relatively more abundant. Our results indicate that although all three scanning protocols are suitable to determine the layout of tonotopic fields, an exact quantitative assessment of the representation of various sound frequencies is substantially confounded by the presence of scanner noise. In addition, we noticed anomalous signal dynamics in response to our travelling wave paradigm that suggest that the assessment of frequency-dependent tuning is non-trivially influenced by time-dependent (hemo)dynamics when using sweep stimuli. Copyright © 2014. Published by Elsevier Inc.

The role of ECoG magnitude and phase in decoding position, velocity, and acceleration during continuous motor behavior

PubMed Central

Hammer, Jiri; Fischer, Jörg; Ruescher, Johanna; Schulze-Bonhage, Andreas; Aertsen, Ad; Ball, Tonio

2013-01-01

In neuronal population signals, including the electroencephalogram (EEG) and electrocorticogram (ECoG), the low-frequency component (LFC) is particularly informative about motor behavior and can be used for decoding movement parameters for brain-machine interface (BMI) applications. An idea previously expressed, but as of yet not quantitatively tested, is that it is the LFC phase that is the main source of decodable information. To test this issue, we analyzed human ECoG recorded during a game-like, one-dimensional, continuous motor task with a novel decoding method suitable for unfolding magnitude and phase explicitly into a complex-valued, time-frequency signal representation, enabling quantification of the decodable information within the temporal, spatial and frequency domains and allowing disambiguation of the phase contribution from that of the spectral magnitude. The decoding accuracy based only on phase information was substantially (at least 2 fold) and significantly higher than that based only on magnitudes for position, velocity and acceleration. The frequency profile of movement-related information in the ECoG data matched well with the frequency profile expected when assuming a close time-domain correlate of movement velocity in the ECoG, e.g., a (noisy) “copy” of hand velocity. No such match was observed with the frequency profiles expected when assuming a copy of either hand position or acceleration. There was also no indication of additional magnitude-based mechanisms encoding movement information in the LFC range. Thus, our study contributes to elucidating the nature of the informative LFC of motor cortical population activity and may hence contribute to improve decoding strategies and BMI performance. PMID:24198757

Linearized self-consistent quasiparticle GW method: Application to semiconductors and simple metals

NASA Astrophysics Data System (ADS)

Kutepov, A. L.; Oudovenko, V. S.; Kotliar, G.

2017-10-01

We present a code implementing the linearized quasiparticle self-consistent GW method (LQSGW) in the LAPW basis. Our approach is based on the linearization of the self-energy around zero frequency which differs it from the existing implementations of the QSGW method. The linearization allows us to use Matsubara frequencies instead of working on the real axis. This results in efficiency gains by switching to the imaginary time representation in the same way as in the space time method. The all electron LAPW basis set eliminates the need for pseudopotentials. We discuss the advantages of our approach, such as its N3 scaling with the system size N, as well as its shortcomings. We apply our approach to study the electronic properties of selected semiconductors, insulators, and simple metals and show that our code produces the results very close to the previously published QSGW data. Our implementation is a good platform for further many body diagrammatic resummations such as the vertex-corrected GW approach and the GW+DMFT method. Program Files doi:http://dx.doi.org/10.17632/cpchkfty4w.1 Licensing provisions: GNU General Public License Programming language: Fortran 90 External routines/libraries: BLAS, LAPACK, MPI (optional) Nature of problem: Direct implementation of the GW method scales as N4 with the system size, which quickly becomes prohibitively time consuming even in the modern computers. Solution method: We implemented the GW approach using a method that switches between real space and momentum space representations. Some operations are faster in real space, whereas others are more computationally efficient in the reciprocal space. This makes our approach scale as N3. Restrictions: The limiting factor is usually the memory available in a computer. Using 10 GB/core of memory allows us to study the systems up to 15 atoms per unit cell.

The big brown bat's perceptual dimension of target range

NASA Astrophysics Data System (ADS)

Simmons, James A.

2005-09-01

Big brown bats determine the distance to targets from echo delay, but information actually is entered onto the bat's psychological delay scale from two sources. The first is the target-ranging system itself, from the time that elapses between single-spike neural responses evoked by the broadcast and similar responses evoked by echoes at different delays. These responses register the FM sweeps of broadcasts or echoes, and the associated system of neural delay lines and coincidence detectors cross correlates the spectrograms along the time axis. The second source is the echo spectrum, which relates to shape expressed as range profile. The target-ranging system extracts this by fanning out to encompass parallel representations of many possible notch frequencies and notch widths in echoes. Bats perceive delay separations of 5-30 μs and have a resolution limit of about 2 μs, but interference amplifies small delay separations by transposing them into large changes in notch frequency, so only perception of intervals smaller than 5 μs is surprising. Experiments with phase-shifted echoes show that the psychological time scale can represent two different delays originating entirely in the time domain when they are at least as close together as 10 μs. [Work supported by NIH and ONR.

Generalised Transfer Functions of Neural Networks

NASA Astrophysics Data System (ADS)

Fung, C. F.; Billings, S. A.; Zhang, H.

1997-11-01

When artificial neural networks are used to model non-linear dynamical systems, the system structure which can be extremely useful for analysis and design, is buried within the network architecture. In this paper, explicit expressions for the frequency response or generalised transfer functions of both feedforward and recurrent neural networks are derived in terms of the network weights. The derivation of the algorithm is established on the basis of the Taylor series expansion of the activation functions used in a particular neural network. This leads to a representation which is equivalent to the non-linear recursive polynomial model and enables the derivation of the transfer functions to be based on the harmonic expansion method. By mapping the neural network into the frequency domain information about the structure of the underlying non-linear system can be recovered. Numerical examples are included to demonstrate the application of the new algorithm. These examples show that the frequency response functions appear to be highly sensitive to the network topology and training, and that the time domain properties fail to reveal deficiencies in the trained network structure.

Basic composition and enriched integration in idiom processing: An EEG study.

PubMed

Canal, Paolo; Pesciarelli, Francesca; Vespignani, Francesco; Molinaro, Nicola; Cacciari, Cristina

2017-06-01

We investigated the extent to which the literal meanings of the words forming literally plausible idioms (e.g., break the ice) are semantically composed and how the idiomatic meaning is integrated in the unfolding sentence representation. Participants read ambiguous idiom strings embedded in highly predictable, literal, and idiomatic contexts while their EEG was recorded. Control sentences only contained the idiom-final word whose cloze values were as high as in literal and idiomatic contexts. Event-related potentials data showed that differences in the amplitude of a frontal positivity (PNP) emerged at the beginning and at the end of the idiom strings, with the idiomatic context condition associated with more positive voltages. The time frequency analysis of the EEG showed an increase in power of the middle gamma frequency band only in the literal context condition. These findings suggest that sentence revision mechanisms, associated with the frontal PNP, are involved in idiom meaning integration, and that the literal semantic composition of the idiomatic constituents, associated with changes in gamma frequency, is not carried out after idiom recognition. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Emerging Object Representations in the Visual System Predict Reaction Times for Categorization

PubMed Central

Ritchie, J. Brendan; Tovar, David A.; Carlson, Thomas A.

2015-01-01

Recognizing an object takes just a fraction of a second, less than the blink of an eye. Applying multivariate pattern analysis, or “brain decoding”, methods to magnetoencephalography (MEG) data has allowed researchers to characterize, in high temporal resolution, the emerging representation of object categories that underlie our capacity for rapid recognition. Shortly after stimulus onset, object exemplars cluster by category in a high-dimensional activation space in the brain. In this emerging activation space, the decodability of exemplar category varies over time, reflecting the brain’s transformation of visual inputs into coherent category representations. How do these emerging representations relate to categorization behavior? Recently it has been proposed that the distance of an exemplar representation from a categorical boundary in an activation space is critical for perceptual decision-making, and that reaction times should therefore correlate with distance from the boundary. The predictions of this distance hypothesis have been born out in human inferior temporal cortex (IT), an area of the brain crucial for the representation of object categories. When viewed in the context of a time varying neural signal, the optimal time to “read out” category information is when category representations in the brain are most decodable. Here, we show that the distance from a decision boundary through activation space, as measured using MEG decoding methods, correlates with reaction times for visual categorization during the period of peak decodability. Our results suggest that the brain begins to read out information about exemplar category at the optimal time for use in choice behaviour, and support the hypothesis that the structure of the representation for objects in the visual system is partially constitutive of the decision process in recognition. PMID:26107634

Object Categorization in Finer Levels Relies More on Higher Spatial Frequencies and Takes Longer.

PubMed

Ashtiani, Matin N; Kheradpisheh, Saeed R; Masquelier, Timothée; Ganjtabesh, Mohammad

2017-01-01

The human visual system contains a hierarchical sequence of modules that take part in visual perception at different levels of abstraction, i.e., superordinate, basic, and subordinate levels. One important question is to identify the "entry" level at which the visual representation is commenced in the process of object recognition. For a long time, it was believed that the basic level had a temporal advantage over two others. This claim has been challenged recently. Here we used a series of psychophysics experiments, based on a rapid presentation paradigm, as well as two computational models, with bandpass filtered images of five object classes to study the processing order of the categorization levels. In these experiments, we investigated the type of visual information required for categorizing objects in each level by varying the spatial frequency bands of the input image. The results of our psychophysics experiments and computational models are consistent. They indicate that the different spatial frequency information had different effects on object categorization in each level. In the absence of high frequency information, subordinate and basic level categorization are performed less accurately, while the superordinate level is performed well. This means that low frequency information is sufficient for superordinate level, but not for the basic and subordinate levels. These finer levels rely more on high frequency information, which appears to take longer to be processed, leading to longer reaction times. Finally, to avoid the ceiling effect, we evaluated the robustness of the results by adding different amounts of noise to the input images and repeating the experiments. As expected, the categorization accuracy decreased and the reaction time increased significantly, but the trends were the same. This shows that our results are not due to a ceiling effect. The compatibility between our psychophysical and computational results suggests that the temporal advantage of the superordinate (resp. basic) level to basic (resp. subordinate) level is mainly due to the computational constraints (the visual system processes higher spatial frequencies more slowly, and categorization in finer levels depends more on these higher spatial frequencies).

Object Categorization in Finer Levels Relies More on Higher Spatial Frequencies and Takes Longer

PubMed Central

Ashtiani, Matin N.; Kheradpisheh, Saeed R.; Masquelier, Timothée; Ganjtabesh, Mohammad

2017-01-01

The human visual system contains a hierarchical sequence of modules that take part in visual perception at different levels of abstraction, i.e., superordinate, basic, and subordinate levels. One important question is to identify the “entry” level at which the visual representation is commenced in the process of object recognition. For a long time, it was believed that the basic level had a temporal advantage over two others. This claim has been challenged recently. Here we used a series of psychophysics experiments, based on a rapid presentation paradigm, as well as two computational models, with bandpass filtered images of five object classes to study the processing order of the categorization levels. In these experiments, we investigated the type of visual information required for categorizing objects in each level by varying the spatial frequency bands of the input image. The results of our psychophysics experiments and computational models are consistent. They indicate that the different spatial frequency information had different effects on object categorization in each level. In the absence of high frequency information, subordinate and basic level categorization are performed less accurately, while the superordinate level is performed well. This means that low frequency information is sufficient for superordinate level, but not for the basic and subordinate levels. These finer levels rely more on high frequency information, which appears to take longer to be processed, leading to longer reaction times. Finally, to avoid the ceiling effect, we evaluated the robustness of the results by adding different amounts of noise to the input images and repeating the experiments. As expected, the categorization accuracy decreased and the reaction time increased significantly, but the trends were the same. This shows that our results are not due to a ceiling effect. The compatibility between our psychophysical and computational results suggests that the temporal advantage of the superordinate (resp. basic) level to basic (resp. subordinate) level is mainly due to the computational constraints (the visual system processes higher spatial frequencies more slowly, and categorization in finer levels depends more on these higher spatial frequencies). PMID:28790954

Comparison of filtering methods for extracellular gastric slow wave recordings.

PubMed

Paskaranandavadivel, Niranchan; O'Grady, Gregory; Du, Peng; Cheng, Leo K

2013-01-01

Extracellular recordings are used to define gastric slow wave propagation. Signal filtering is a key step in the analysis and interpretation of extracellular slow wave data; however, there is controversy and uncertainty regarding the appropriate filtering settings. This study investigated the effect of various standard filters on the morphology and measurement of extracellular gastric slow waves. Experimental extracellular gastric slow waves were recorded from the serosal surface of the stomach from pigs and humans. Four digital filters: finite impulse response filter (0.05-1 Hz); Savitzky-Golay filter (0-1.98 Hz); Bessel filter (2-100 Hz); and Butterworth filter (5-100 Hz); were applied on extracellular gastric slow wave signals to compare the changes temporally (morphology of the signal) and spectrally (signals in the frequency domain). The extracellular slow wave activity is represented in the frequency domain by a dominant frequency and its associated harmonics in diminishing power. Optimal filters apply cutoff frequencies consistent with the dominant slow wave frequency (3-5 cpm) and main harmonics (up to ≈ 2 Hz). Applying filters with cutoff frequencies above or below the dominant and harmonic frequencies was found to distort or eliminate slow wave signal content. Investigators must be cognizant of these optimal filtering practices when detecting, analyzing, and interpreting extracellular slow wave recordings. The use of frequency domain analysis is important for identifying the dominant and harmonics of the signal of interest. Capturing the dominant frequency and major harmonics of slow wave is crucial for accurate representation of slow wave activity in the time domain. Standardized filter settings should be determined. © 2012 Blackwell Publishing Ltd.

Specialized mechanisms for theory of mind: are mental representations special because they are mental or because they are representations?

PubMed

Cohen, Adam S; Sasaki, Joni Y; German, Tamsin C

2015-03-01

Does theory of mind depend on a capacity to reason about representations generally or on mechanisms selective for the processing of mental state representations? In four experiments, participants reasoned about beliefs (mental representations) and notes (non-mental, linguistic representations), which according to two prominent theories are closely matched representations because both are represented propositionally. Reaction times were faster and accuracies higher when participants endorsed or rejected statements about false beliefs than about false notes (Experiment 1), even when statements emphasized representational format (Experiment 2), which should have favored the activation of representation concepts. Experiments 3 and 4 ruled out a counterhypothesis that differences in task demands were responsible for the advantage in belief processing. These results demonstrate for the first time that understanding of mental and linguistic representations can be dissociated even though both may carry propositional content, supporting the theory that mechanisms governing theory of mind reasoning are narrowly specialized to process mental states, not representations more broadly. Extending this theory, we discuss whether less efficient processing of non-mental representations may be a by-product of mechanisms specialized for processing mental states. Crown Copyright © 2014. Published by Elsevier B.V. All rights reserved.

A scale-invariant internal representation of time.

PubMed

Shankar, Karthik H; Howard, Marc W

2012-01-01

We propose a principled way to construct an internal representation of the temporal stimulus history leading up to the present moment. A set of leaky integrators performs a Laplace transform on the stimulus function, and a linear operator approximates the inversion of the Laplace transform. The result is a representation of stimulus history that retains information about the temporal sequence of stimuli. This procedure naturally represents more recent stimuli more accurately than less recent stimuli; the decrement in accuracy is precisely scale invariant. This procedure also yields time cells that fire at specific latencies following the stimulus with a scale-invariant temporal spread. Combined with a simple associative memory, this representation gives rise to a moment-to-moment prediction that is also scale invariant in time. We propose that this scale-invariant representation of temporal stimulus history could serve as an underlying representation accessible to higher-level behavioral and cognitive mechanisms. In order to illustrate the potential utility of this scale-invariant representation in a variety of fields, we sketch applications using minimal performance functions to problems in classical conditioning, interval timing, scale-invariant learning in autoshaping, and the persistence of the recency effect in episodic memory across timescales.

Cortical plasticity as a mechanism for storing Bayesian priors in sensory perception.

PubMed

Köver, Hania; Bao, Shaowen

2010-05-05

Human perception of ambiguous sensory signals is biased by prior experiences. It is not known how such prior information is encoded, retrieved and combined with sensory information by neurons. Previous authors have suggested dynamic encoding mechanisms for prior information, whereby top-down modulation of firing patterns on a trial-by-trial basis creates short-term representations of priors. Although such a mechanism may well account for perceptual bias arising in the short-term, it does not account for the often irreversible and robust changes in perception that result from long-term, developmental experience. Based on the finding that more frequently experienced stimuli gain greater representations in sensory cortices during development, we reasoned that prior information could be stored in the size of cortical sensory representations. For the case of auditory perception, we use a computational model to show that prior information about sound frequency distributions may be stored in the size of primary auditory cortex frequency representations, read-out by elevated baseline activity in all neurons and combined with sensory-evoked activity to generate a perception that conforms to Bayesian integration theory. Our results suggest an alternative neural mechanism for experience-induced long-term perceptual bias in the context of auditory perception. They make the testable prediction that the extent of such perceptual prior bias is modulated by both the degree of cortical reorganization and the magnitude of spontaneous activity in primary auditory cortex. Given that cortical over-representation of frequently experienced stimuli, as well as perceptual bias towards such stimuli is a common phenomenon across sensory modalities, our model may generalize to sensory perception, rather than being specific to auditory perception.

Three-dimensional imaging of biological cells with picosecond ultrasonics

NASA Astrophysics Data System (ADS)

Danworaphong, Sorasak; Tomoda, Motonobu; Matsumoto, Yuki; Matsuda, Osamu; Ohashi, Toshiro; Watanabe, Hiromu; Nagayama, Masafumi; Gohara, Kazutoshi; Otsuka, Paul H.; Wright, Oliver B.

2015-04-01

We use picosecond ultrasonics to image animal cells in vitro—a bovine aortic endothelial cell and a mouse adipose cell—fixed to Ti-coated sapphire. Tightly focused ultrashort laser pulses generate and detect GHz acoustic pulses, allowing three-dimensional imaging (x, y, and t) of the ultrasonic propagation in the cells with ˜1 μm lateral and ˜150 nm depth resolutions. Time-frequency representations of the continuous-wavelet-transform amplitude of the optical reflectivity variations inside and outside the cells show GHz Brillouin oscillations, allowing the average sound velocities of the cells and their ultrasonic attenuation to be obtained as well as the average bulk moduli.

Sinusoidal transform coding

NASA Technical Reports Server (NTRS)

Mcaulay, Robert J.; Quatieri, Thomas F.

1988-01-01

It has been shown that an analysis/synthesis system based on a sinusoidal representation of speech leads to synthetic speech that is essentially perceptually indistinguishable from the original. Strategies for coding the amplitudes, frequencies and phases of the sine waves have been developed that have led to a multirate coder operating at rates from 2400 to 9600 bps. The encoded speech is highly intelligible at all rates with a uniformly improving quality as the data rate is increased. A real-time fixed-point implementation has been developed using two ADSP2100 DSP chips. The methods used for coding and quantizing the sine-wave parameters for operation at the various frame rates are described.

Reconstruction of fiber grating period profiles by use of Wigner-Ville distributions and spectrograms.

PubMed

Azaña, J; Muriel, M A

2000-12-01

The grating-period profile and length of an arbitrary fiber Bragg grating structure can be reconstructed from the structure's reflection response by use of a time-frequency signal representation based on the well-known Wigner-Ville distribution and spectrogram. We present a detailed description of this synthesis technique. By means of numerical simulations, the technique is tested with several fiber grating structures. In general, our results show good agreement between exact and reconstructed functions. The technique's advantages and limitations are discussed. We propose and demonstrate the application of the proposed synthesis technique to distributed mechanical strain or temperature sensing.

Les résonances d'un trou noir de Schwarzschild.

NASA Astrophysics Data System (ADS)

Bachelot, A.; Motet-Bachelot, A.

1993-09-01

This paper is devoted to the theoretical and computational investigations of the scattering frequencies of scalar, electromagnetic, gravitational waves around a spherical black hole. The authors adopt a time dependent approach: construction of wave operators for the hyperbolic Regge-Wheeler equation; asymptotic completeness; outgoing and incoming spectral representations; meromorphic continuation of the Heisenberg matrix; approximation by dumping and cut-off of the potentials and interpretation of the semi group Z(t) in the framework of the membrane paradigma. They develop a new procedure for the computation of the resonances by the spectral analysis of the transient scattered wave, based on Prony's algorithm.

An Energy Decaying Scheme for Nonlinear Dynamics of Shells

NASA Technical Reports Server (NTRS)

Bottasso, Carlo L.; Bauchau, Olivier A.; Choi, Jou-Young; Bushnell, Dennis M. (Technical Monitor)

2000-01-01

A novel integration scheme for nonlinear dynamics of geometrically exact shells is developed based on the inextensible director assumption. The new algorithm is designed so as to imply the strict decay of the system total mechanical energy at each time step, and consequently unconditional stability is achieved in the nonlinear regime. Furthermore, the scheme features tunable high frequency numerical damping and it is therefore stiffly accurate. The method is tested for a finite element spatial formulation of shells based on mixed interpolations of strain tensorial components and on a two-parameter representation of director rotations. The robustness of the, scheme is illustrated with the help of numerical examples.

A multivariate time-frequency method to characterize the influence of respiration over heart period and arterial pressure

NASA Astrophysics Data System (ADS)

Orini, Michele; Bailón, Raquel; Laguna, Pablo; Mainardi, Luca T.; Barbieri, Riccardo

2012-12-01

Respiratory activity introduces oscillations both in arterial pressure and heart period, through mechanical and autonomic mechanisms. Respiration, arterial pressure, and heart period are, generally, non-stationary processes and the interactions between them are dynamic. In this study we present a methodology to robustly estimate the time course of cross spectral indices to characterize dynamic interactions between respiratory oscillations of heart period and blood pressure, as well as their interactions with respiratory activity. Time-frequency distributions belonging to Cohen's class are used to estimate time-frequency (TF) representations of coherence, partial coherence and phase difference. The characterization is based on the estimation of the time course of cross spectral indices estimated in specific TF regions around the respiratory frequency. We used this methodology to describe the interactions between respiration, heart period variability (HPV) and systolic arterial pressure variability (SAPV) during tilt table test with both spontaneous and controlled respiratory patterns. The effect of selective autonomic blockade was also studied. Results suggest the presence of common underling mechanisms of regulation between cardiovascular signals, whose interactions are time-varying. SAPV changes followed respiratory flow both in supine and standing positions and even after selective autonomic blockade. During head-up tilt, phase differences between respiration and SAPV increased. Phase differences between respiration and HPV were comparable to those between respiration and SAPV during supine position, and significantly increased during standing. As a result, respiratory oscillations in SAPV preceded respiratory oscillations in HPV during standing. Partial coherence was the most sensitive index to orthostatic stress. Phase difference estimates were consistent among spontaneous and controlled breathing patterns, whereas coherence was higher in spontaneous breathing. Parasympathetic blockade did not affect interactions between respiration and SAPV, reduced the coherence between SAPV and HPV and between respiration and HPV. Our results support the hypothesis that non-autonomic, possibly mechanically mediated, mechanisms also contributes to the respiratory oscillations in HPV. A small contribution of sympathetic activity on HPV-SAPV interactions around the respiratory frequency was also observed.

Transition Icons for Time-Series Visualization and Exploratory Analysis.

PubMed

Nickerson, Paul V; Baharloo, Raheleh; Wanigatunga, Amal A; Manini, Todd M; Tighe, Patrick J; Rashidi, Parisa

2018-03-01

The modern healthcare landscape has seen the rapid emergence of techniques and devices that temporally monitor and record physiological signals. The prevalence of time-series data within the healthcare field necessitates the development of methods that can analyze the data in order to draw meaningful conclusions. Time-series behavior is notoriously difficult to intuitively understand due to its intrinsic high-dimensionality, which is compounded in the case of analyzing groups of time series collected from different patients. Our framework, which we call transition icons, renders common patterns in a visual format useful for understanding the shared behavior within groups of time series. Transition icons are adept at detecting and displaying subtle differences and similarities, e.g., between measurements taken from patients receiving different treatment strategies or stratified by demographics. We introduce various methods that collectively allow for exploratory analysis of groups of time series, while being free of distribution assumptions and including simple heuristics for parameter determination. Our technique extracts discrete transition patterns from symbolic aggregate approXimation representations, and compiles transition frequencies into a bag of patterns constructed for each group. These transition frequencies are normalized and aligned in icon form to intuitively display the underlying patterns. We demonstrate the transition icon technique for two time-series datasets-postoperative pain scores, and hip-worn accelerometer activity counts. We believe transition icons can be an important tool for researchers approaching time-series data, as they give rich and intuitive information about collective time-series behaviors.

Time-Frequency Analysis of Chemosensory Event-Related Potentials to Characterize the Cortical Representation of Odors in Humans

PubMed Central

Huart, Caroline; Legrain, Valéry; Hummel, Thomas; Rombaux, Philippe; Mouraux, André

2012-01-01

Background The recording of olfactory and trigeminal chemosensory event-related potentials (ERPs) has been proposed as an objective and non-invasive technique to study the cortical processing of odors in humans. Until now, the responses have been characterized mainly using across-trial averaging in the time domain. Unfortunately, chemosensory ERPs, in particular, olfactory ERPs, exhibit a relatively low signal-to-noise ratio. Hence, although the technique is increasingly used in basic research as well as in clinical practice to evaluate people suffering from olfactory disorders, its current clinical relevance remains very limited. Here, we used a time-frequency analysis based on the wavelet transform to reveal EEG responses that are not strictly phase-locked to onset of the chemosensory stimulus. We hypothesized that this approach would significantly enhance the signal-to-noise ratio of the EEG responses to chemosensory stimulation because, as compared to conventional time-domain averaging, (1) it is less sensitive to temporal jitter and (2) it can reveal non phase-locked EEG responses such as event-related synchronization and desynchronization. Methodology/Principal Findings EEG responses to selective trigeminal and olfactory stimulation were recorded in 11 normosmic subjects. A Morlet wavelet was used to characterize the elicited responses in the time-frequency domain. We found that this approach markedly improved the signal-to-noise ratio of the obtained EEG responses, in particular, following olfactory stimulation. Furthermore, the approach allowed characterizing non phase-locked components that could not be identified using conventional time-domain averaging. Conclusion/Significance By providing a more robust and complete view of how odors are represented in the human brain, our approach could constitute the basis for a robust tool to study olfaction, both for basic research and clinicians. PMID:22427997

Predictions of Speech Chimaera Intelligibility Using Auditory Nerve Mean-Rate and Spike-Timing Neural Cues.

PubMed

Wirtzfeld, Michael R; Ibrahim, Rasha A; Bruce, Ian C

2017-10-01

Perceptual studies of speech intelligibility have shown that slow variations of acoustic envelope (ENV) in a small set of frequency bands provides adequate information for good perceptual performance in quiet, whereas acoustic temporal fine-structure (TFS) cues play a supporting role in background noise. However, the implications for neural coding are prone to misinterpretation because the mean-rate neural representation can contain recovered ENV cues from cochlear filtering of TFS. We investigated ENV recovery and spike-time TFS coding using objective measures of simulated mean-rate and spike-timing neural representations of chimaeric speech, in which either the ENV or the TFS is replaced by another signal. We (a) evaluated the levels of mean-rate and spike-timing neural information for two categories of chimaeric speech, one retaining ENV cues and the other TFS; (b) examined the level of recovered ENV from cochlear filtering of TFS speech; (c) examined and quantified the contribution to recovered ENV from spike-timing cues using a lateral inhibition network (LIN); and (d) constructed linear regression models with objective measures of mean-rate and spike-timing neural cues and subjective phoneme perception scores from normal-hearing listeners. The mean-rate neural cues from the original ENV and recovered ENV partially accounted for perceptual score variability, with additional variability explained by the recovered ENV from the LIN-processed TFS speech. The best model predictions of chimaeric speech intelligibility were found when both the mean-rate and spike-timing neural cues were included, providing further evidence that spike-time coding of TFS cues is important for intelligibility when the speech envelope is degraded.

Synchronization between two coupled direct current glow discharge plasma sources

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chaubey, Neeraj; Mukherjee, S.; Sen, A.

2015-02-15

Experimental results on the nonlinear dynamics of two coupled glow discharge plasma sources are presented. A variety of nonlinear phenomena including frequency synchronization and frequency pulling are observed as the coupling strength is varied. Numerical solutions of a model representation of the experiment consisting of two coupled asymmetric Van der Pol type equations are found to be in good agreement with the observed results.

Translation of time-reversal violation in the neutral K-meson system into a table-top mechanical system

NASA Astrophysics Data System (ADS)

Reiser, Andreas; Schubert, Klaus R.; Stiewe, Jürgen

2012-08-01

Weak interactions break time-reversal (T) symmetry in the two-state system of neutral K-mesons. We present and discuss a two-state mechanical system, i.e. a Foucault-type pendulum on a rotating table, for a full representation of {K^0}{{\\overlineK}{}^0} transitions by the pendulum motions including T violation. The pendulum moves with two different oscillation frequencies and two different magnetic dampings. Its equation of motion is identical to the differential equation for the real part of the CPT-symmetric K-meson wavefunction. The pendulum is able to represent microscopic CP and T violation with CPT symmetry owing to the macroscopic Coriolis force, which breaks the symmetry under reversal-of-motion. Video clips of the pendulum motions are given as supplementary material.

Losing track of time through delayed body representations.

PubMed

Fritz, Thomas H; Steixner, Agnes; Boettger, Joachim; Villringer, Arno

2015-01-01

The ability to keep track of time is perceived as crucial in most human societies. However, to lose track of time may also serve an important social role, associated with recreational purpose. To this end a number of social technologies are employed, some of which may relate to a manipulation of time perception through a modulation of body representation. Here, we investigated an influence of real-time or delayed videos of own-body representations on time perception in an experimental setup with virtual mirrors. Seventy participants were asked to either stay in the installation until they thought that a defined time (90 s) had passed, or they were encouraged to stay in the installation as long as they wanted and after exiting were asked to estimate the duration of their stay. Results show that a modulation of body representation by time-delayed representations of the mirror-video displays influenced time perception. Furthermore, these time-delayed conditions were associated with a greater sense of arousal and intoxication. We suggest that feeding in references to the immediate past into working memory could be the underlying mental mechanism mediating the observed modulation of time perception. We argue that such an influence on time perception would probably not only be achieved visually, but might also work with acoustic references to the immediate past (e.g., with music).

Frequency-shift detectors bind binaural as well as monaural frequency representations.

PubMed

Carcagno, Samuele; Semal, Catherine; Demany, Laurent

2011-12-01

Previous psychophysical work provided evidence for the existence of automatic frequency-shift detectors (FSDs) that establish perceptual links between successive sounds. In this study, we investigated the characteristics of the FSDs with respect to the binaural system. Listeners were presented with sound sequences consisting of a chord of pure tones followed by a single test tone. Two tasks were performed. In the "present/absent" task, the test tone was either identical to one of the chord components or positioned halfway in frequency between two components, and listeners had to discriminate between these two possibilities. In the "up/down" task, the test tone was slightly different in frequency from one of the chord components and listeners had to identify the direction (up or down) of the corresponding shift. When the test tone was a pure tone presented monaurally, either to the same ear as the chord or to the opposite ear, listeners performed the up/down task better than the present/absent task. This paradoxical advantage for directional frequency shifts, providing evidence for FSDs, persisted when the test tone was replaced by a dichotic stimulus consisting of noise but evoking a pitch sensation as a consequence of binaural processing. Performance in the up/down task was similar for the dichotic stimulus and for a monaural narrow-band noise matched in pitch salience to it. Our results indicate that the FSDs are insensitive to sound localization mechanisms and operate on central frequency representations, at or above the level of convergence of the monaural auditory pathways.

Ionosonde-based indices for improved representation of solar cycle variation in the International Reference Ionosphere model

NASA Astrophysics Data System (ADS)

Brown, Steven; Bilitza, Dieter; Yiǧit, Erdal

2018-06-01

A new monthly ionospheric index, IGNS, is presented to improve the representation of the solar cycle variation of the ionospheric F2 peak plasma frequency, foF2. IGNS is calculated using a methodology similar to the construction of the "global effective sunspot number", IG, given by Liu et al. (1983) but selects ionosonde observations based on hemispheres. We incorporated the updated index into the International Reference Ionosphere (IRI) model and compared the foF2 model predictions with global ionospheric observations. We also investigated the influence of the underlying foF2 model on the IG index. IRI has two options for foF2 specification, the CCIR-66 and URSI-88 foF2 models. For the first time, we have calculated IG using URSI-88 and assessed the impact on model predictions. Through a retrospective model-data comparison, results show that the inclusion of the new monthly IGNS index in place of the current 12-month smoothed IG index reduce the foF2 model prediction errors by nearly a factor of two. These results apply to both day-time and nightime predictions. This is due to an overall improved prediction of foF2 seasonal and solar cycle variations in the different hemispheres.

Lift and moment coefficients expanded to the seventh power of frequency for oscillating rectangular wings in supersonic flow and applied to a specific flutter problem

NASA Technical Reports Server (NTRS)

Nelson, Herbert C; Rainey, Ruby A; Watkins, Charles E

1954-01-01

Linearized theory for compressible unsteady flow is used to derive the velocity potential and lift and moment coefficients in the form of oscillating rectangular wing moving at a constant supersonic speed. Closed expressions for the velocity potential and lift and moment coefficients associated with pitching and translation are given to seventh power of the frequency. These expressions extend the range of usefulness of NACA report 1028 in which similar expressions were derived to the third power of the frequency of oscillation. For example, at a Mach number of 10/9 the expansion of the potential to the third power is an accurate representation of the potential for values of the reduced frequency only up to about 0.08; whereas the expansion of the potential to the seventh power is an accurate representation for values of the reduced frequency up to about 0.2. The section and total lift and moment coefficients are discussed with the aid of several figures. In addition, flutter speeds obtained in the Mach number range from 10/9 to 10/6 for a rectangular wing of aspect ratio 4.53 by using section coefficients derived on the basis of three-dimensional flow are compared with flutter speeds for this wing obtained by using coefficients derived on the basis of two-dimensional flow.

Articulatory rehearsal is more than refreshing memory traces.

PubMed

Nishiyama, Ryoji; Ukita, Jun

2013-01-01

This study examined whether additional articulatory rehearsal induced temporary durability of phonological representations, using a 10-s delayed nonword free recall task. Three experiments demonstrated that cumulative rehearsal between the offset of the last study item and the start of the filled delay (Experiments 1 and 3) and a fixed rehearsal of the immediate item during the subsequent interstimulus interval (Experiments 2 and 3) improved free recall performance. These results suggest that an additional rehearsal helps to stabilize phonological representations for a short period. Furthermore, the analyses of serial position curves suggested that the frequency of the articulation affected the durability of the phonological representation. The significance of these findings as clues of the mechanism maintaining verbal information (i.e., verbal working memory) is discussed.

Atmospheric blocking in the Climate SPHINX simulations: the role of orography and resolution

NASA Astrophysics Data System (ADS)

Davini, Paolo; Corti, Susanna; D'Andrea, Fabio; Riviere, Gwendal; von Hardenberg, Jost

2017-04-01

The representation of atmospheric blocking in numerical simulations, especially over the Euro-Atlantic region, still represents a main concern for the climate modelling community. We here discuss the Northern Hemisphere winter atmospheric blocking representation in a set of 30-year simulations which has been performed in the framework of the PRACE project "Climate SPHINX". Simulations were run using the EC-Earth Global Climate Model with several ensemble members at 5 different horizontal resolutions (ranging from 125 km to 16 km). Results show that the negative bias in blocking frequency over Europe becomes negligible at resolutions of about 40 km and finer. However, the blocking duration is still underestimated by 1-2 days, suggesting that the correct blocking frequencies are achieved with an overestimation of the number of blocking onsets. The reasons leading to such improvements are then discussed, highlighting the role of orography in shaping the Atlantic jet stream: at higher resolution the jet is weaker and less penetrating over Europe, favoring the breaking of synoptic Rossby waves over the Atlantic stationary ridge and thus increasing the simulated blocking frequency.

Detection of the valvular split within the second heart sound using the reassigned smoothed pseudo Wigner–Ville distribution

PubMed Central

2013-01-01

Background In this paper, we developed a novel algorithm to detect the valvular split between the aortic and pulmonary components in the second heart sound which is a valuable medical information. Methods The algorithm is based on the Reassigned smoothed pseudo Wigner–Ville distribution which is a modified time–frequency distribution of the Wigner–Ville distribution. A preprocessing amplitude recovery procedure is carried out on the analysed heart sound to improve the readability of the time–frequency representation. The simulated S2 heart sounds were generated by an overlapping frequency modulated chirp–based model at different valvular split durations. Results Simulated and real heart sounds are processed to highlight the performance of the proposed approach. The algorithm is also validated on real heart sounds of the LGB–IRCM (Laboratoire de Génie biomédical–Institut de recherches cliniques de Montréal) cardiac valve database. The A2–P2 valvular split is accurately detected by processing the obtained RSPWVD representations for both simulated and real data. PMID:23631738

Remote Sensing Image Fusion Method Based on Nonsubsampled Shearlet Transform and Sparse Representation

NASA Astrophysics Data System (ADS)

Moonon, Altan-Ulzii; Hu, Jianwen; Li, Shutao

2015-12-01

The remote sensing image fusion is an important preprocessing technique in remote sensing image processing. In this paper, a remote sensing image fusion method based on the nonsubsampled shearlet transform (NSST) with sparse representation (SR) is proposed. Firstly, the low resolution multispectral (MS) image is upsampled and color space is transformed from Red-Green-Blue (RGB) to Intensity-Hue-Saturation (IHS). Then, the high resolution panchromatic (PAN) image and intensity component of MS image are decomposed by NSST to high and low frequency coefficients. The low frequency coefficients of PAN and the intensity component are fused by the SR with the learned dictionary. The high frequency coefficients of intensity component and PAN image are fused by local energy based fusion rule. Finally, the fused result is obtained by performing inverse NSST and inverse IHS transform. The experimental results on IKONOS and QuickBird satellites demonstrate that the proposed method provides better spectral quality and superior spatial information in the fused image than other remote sensing image fusion methods both in visual effect and object evaluation.

Learning Novel Phonological Representations in Developmental Dyslexia: Associations with Basic Auditory Processing of Rise Time and Phonological Awareness

ERIC Educational Resources Information Center

Thomson, Jennifer M.; Goswami, Usha

2010-01-01

Across languages, children with developmental dyslexia are known to have impaired lexical phonological representations. Here, we explore associations between learning new phonological representations, phonological awareness, and sensitivity to amplitude envelope onsets (rise time). We show that individual differences in learning novel phonological…

Time course of allocentric decay, egocentric decay, and allocentric-to-egocentric conversion in memory-guided reach.

PubMed

Chen, Ying; Byrne, Patrick; Crawford, J Douglas

2011-01-01

Allocentric cues can be used to encode locations in visuospatial memory, but it is not known how and when these representations are converted into egocentric commands for behaviour. Here, we tested the influence of different memory intervals on reach performance toward targets defined in either egocentric or allocentric coordinates, and then compared this to performance in a task where subjects were implicitly free to choose when to convert from allocentric to egocentric representations. Reach and eye positions were measured using Optotrak and Eyelink Systems, respectively, in fourteen subjects. Our results confirm that egocentric representations degrade over a delay of several seconds, whereas allocentric representations remained relatively stable over the same time scale. Moreover, when subjects were free to choose, they converted allocentric representations into egocentric representations as soon as possible, despite the apparent cost in reach precision in our experimental paradigm. This suggests that humans convert allocentric representations into egocentric commands at the first opportunity, perhaps to optimize motor noise and movement timing in real-world conditions. Copyright © 2010 Elsevier Ltd. All rights reserved.

Boltzmann-conserving classical dynamics in quantum time-correlation functions: "Matsubara dynamics".

PubMed

Hele, Timothy J H; Willatt, Michael J; Muolo, Andrea; Althorpe, Stuart C

2015-04-07

We show that a single change in the derivation of the linearized semiclassical-initial value representation (LSC-IVR or "classical Wigner approximation") results in a classical dynamics which conserves the quantum Boltzmann distribution. We rederive the (standard) LSC-IVR approach by writing the (exact) quantum time-correlation function in terms of the normal modes of a free ring-polymer (i.e., a discrete imaginary-time Feynman path), taking the limit that the number of polymer beads N → ∞, such that the lowest normal-mode frequencies take their "Matsubara" values. The change we propose is to truncate the quantum Liouvillian, not explicitly in powers of ħ(2) at ħ(0) (which gives back the standard LSC-IVR approximation), but in the normal-mode derivatives corresponding to the lowest Matsubara frequencies. The resulting "Matsubara" dynamics is inherently classical (since all terms O(ħ(2)) disappear from the Matsubara Liouvillian in the limit N → ∞) and conserves the quantum Boltzmann distribution because the Matsubara Hamiltonian is symmetric with respect to imaginary-time translation. Numerical tests show that the Matsubara approximation to the quantum time-correlation function converges with respect to the number of modes and gives better agreement than LSC-IVR with the exact quantum result. Matsubara dynamics is too computationally expensive to be applied to complex systems, but its further approximation may lead to practical methods.

Task relevance modulates the cortical representation of feature conjunctions in the target template.

PubMed

Reeder, Reshanne R; Hanke, Michael; Pollmann, Stefan

2017-07-03

Little is known about the cortical regions involved in representing task-related content in preparation for visual task performance. Here we used representational similarity analysis (RSA) to investigate the BOLD response pattern similarity between task relevant and task irrelevant feature dimensions during conjunction viewing and target template maintenance prior to visual search. Subjects were cued to search for a spatial frequency (SF) or orientation of a Gabor grating and we measured BOLD signal during cue and delay periods before the onset of a search display. RSA of delay period activity revealed that widespread regions in frontal, posterior parietal, and occipitotemporal cortices showed general representational differences between task relevant and task irrelevant dimensions (e.g., orientation vs. SF). In contrast, RSA of cue period activity revealed sensory-related representational differences between cue images (regardless of task) at the occipital pole and additionally in the frontal pole. Our data show that task and sensory information are represented differently during viewing and during target template maintenance, and that task relevance modulates the representation of visual information across the cortex.

Improved Understanding of the Modeled QBO Using MLS Observations and MERRA Reanalysis

NASA Technical Reports Server (NTRS)

Oman, Luke David; Douglass, Anne Ritger; Hurwitz, Maggie M.; Garfinkel, Chaim I.

2013-01-01

The Quasi-Biennial Oscillation (QBO) dominates the variability of the tropical stratosphere on interannual time scales. The QBO has been shown to extend its influence into the chemical composition of this region through dynamical mechanisms. We have started our analysis using the realistic QBO internally generated by the Goddard Earth Observing System Version 5 (GEOS-5) general circulation model coupled to a comprehensive stratospheric and tropospheric chemical mechanism forced with observed sea surface temperatures over the past 33 years. We will show targeted comparisons with observations from NASAs Aura satellite Microwave Limb Sounder (MLS) and the Modern Era Retrospective-Analysis for Research and Applications (MERRA) reanalysis to provide insight into the simulation of the primary and secondary circulations associated with the QBO. Using frequency spectrum analysis and multiple linear regression we can illuminate the resulting circulations and deduce the strengths and weaknesses in their modeled representation. Inclusion of the QBO in our simulation improves the representation of the subtropical barriers and overall tropical variability. The QBO impact on tropical upwelling is important to quantify when calculating trends in sub-decadal scale datasets.

Complex demodulation in VLBI estimation of high frequency Earth rotation components

NASA Astrophysics Data System (ADS)

Böhm, S.; Brzeziński, A.; Schuh, H.

2012-12-01

The spectrum of high frequency Earth rotation variations contains strong harmonic signal components mainly excited by ocean tides along with much weaker non-harmonic fluctuations driven by irregular processes like the diurnal thermal tides in the atmosphere and oceans. In order to properly investigate non-harmonic phenomena a representation in time domain is inevitable. We present a method, operating in time domain, which is easily applicable within Earth rotation estimation from Very Long Baseline Interferometry (VLBI). It enables the determination of diurnal and subdiurnal variations, and is still effective with merely diurnal parameter sampling. The features of complex demodulation are used in an extended parameterization of polar motion and universal time which was implemented into a dedicated version of the Vienna VLBI Software VieVS. The functionality of the approach was evaluated by comparing amplitudes and phases of harmonic variations at tidal periods (diurnal/semidiurnal), derived from demodulated Earth rotation parameters (ERP), estimated from hourly resolved VLBI ERP time series and taken from a recently published VLBI ERP model to the terms of the conventional model for ocean tidal effects in Earth rotation recommended by the International Earth Rotation and Reference System Service (IERS). The three sets of tidal terms derived from VLBI observations extensively agree among each other within the three-sigma level of the demodulation approach, which is below 6 μas for polar motion and universal time. They also coincide in terms of differences to the IERS model, where significant deviations primarily for several major tidal terms are apparent. An additional spectral analysis of the as well estimated demodulated ERP series of the ter- and quarterdiurnal frequency bands did not reveal any significant signal structure. The complex demodulation applied in VLBI parameter estimation could be demonstrated a suitable procedure for the reliable reproduction of high frequency Earth rotation components and thus represents a qualified tool for future studies of irregular geophysical signals in ERP measured by space geodetic techniques.

Development of a BPM Lock-In Diagnostic System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Richard Dickson

2003-05-12

A system has been developed for the acquisition and analysis of high rate, time coherent BPM data across the Jefferson Lab's Continuous Electron Beam Accelerator Facility (CEBAF). This system will allow the acquisition of Beam Position Monitor (BPM) position and intensity information at a rate in excess 7 KHz for approximately 200 BPMs in a time synchronous manner. By inducing minute sinusoidal transverse beam motion in the CEBAF injector, with known phase relative to the synchronized BPM acquisition, it is possible to derive several types of useful information. Analysis of the BPM intensity data, which is proportional to beam current,more » by beating the signal with an in-phase sinusoidal representation of the transverse kick can localize beam scraping to a particular BPM. Similarly, real-time optics information may be deduced with an analysis of BPM position data. This paper will detail the frequency lock-in technique applied and present status.« less

Sensitivity curves for searches for gravitational-wave backgrounds

NASA Astrophysics Data System (ADS)

Thrane, Eric; Romano, Joseph D.

2013-12-01

We propose a graphical representation of detector sensitivity curves for stochastic gravitational-wave backgrounds that takes into account the increase in sensitivity that comes from integrating over frequency in addition to integrating over time. This method is valid for backgrounds that have a power-law spectrum in the analysis band. We call these graphs “power-law integrated curves.” For simplicity, we consider cross-correlation searches for unpolarized and isotropic stochastic backgrounds using two or more detectors. We apply our method to construct power-law integrated sensitivity curves for second-generation ground-based detectors such as Advanced LIGO, space-based detectors such as LISA and the Big Bang Observer, and timing residuals from a pulsar timing array. The code used to produce these plots is available at https://dcc.ligo.org/LIGO-P1300115/public for researchers interested in constructing similar sensitivity curves.

Design of ground test suspension systems for verification of flexible space structures

NASA Technical Reports Server (NTRS)

Cooley, V. M.; Juang, J. N.; Ghaemmaghami, P.

1988-01-01

A simple model demonstrates the frequency-increasing effects of a simple cable suspension on flexible test article/suspension systems. Two passive suspension designs, namely a negative spring mechanism and a rolling cart mechanism, are presented to alleviate the undesirable frequency-increasing effects. Analysis methods are provided for systems in which the augmentations are applied to both discrete and continuous representations of test articles. The damping analyses are based on friction equivalent viscous damping. Numerical examples are given for comparing the two augmentations with respect to minimizing frequency and damping increases.

Classification of Two Class Motor Imagery Tasks Using Hybrid GA-PSO Based K-Means Clustering.

PubMed

Suraj; Tiwari, Purnendu; Ghosh, Subhojit; Sinha, Rakesh Kumar

2015-01-01

Transferring the brain computer interface (BCI) from laboratory condition to meet the real world application needs BCI to be applied asynchronously without any time constraint. High level of dynamism in the electroencephalogram (EEG) signal reasons us to look toward evolutionary algorithm (EA). Motivated by these two facts, in this work a hybrid GA-PSO based K-means clustering technique has been used to distinguish two class motor imagery (MI) tasks. The proposed hybrid GA-PSO based K-means clustering is found to outperform genetic algorithm (GA) and particle swarm optimization (PSO) based K-means clustering techniques in terms of both accuracy and execution time. The lesser execution time of hybrid GA-PSO technique makes it suitable for real time BCI application. Time frequency representation (TFR) techniques have been used to extract the feature of the signal under investigation. TFRs based features are extracted and relying on the concept of event related synchronization (ERD) and desynchronization (ERD) feature vector is formed.

Classification of Two Class Motor Imagery Tasks Using Hybrid GA-PSO Based K-Means Clustering

PubMed Central

Suraj; Tiwari, Purnendu; Ghosh, Subhojit; Sinha, Rakesh Kumar

2015-01-01

Transferring the brain computer interface (BCI) from laboratory condition to meet the real world application needs BCI to be applied asynchronously without any time constraint. High level of dynamism in the electroencephalogram (EEG) signal reasons us to look toward evolutionary algorithm (EA). Motivated by these two facts, in this work a hybrid GA-PSO based K-means clustering technique has been used to distinguish two class motor imagery (MI) tasks. The proposed hybrid GA-PSO based K-means clustering is found to outperform genetic algorithm (GA) and particle swarm optimization (PSO) based K-means clustering techniques in terms of both accuracy and execution time. The lesser execution time of hybrid GA-PSO technique makes it suitable for real time BCI application. Time frequency representation (TFR) techniques have been used to extract the feature of the signal under investigation. TFRs based features are extracted and relying on the concept of event related synchronization (ERD) and desynchronization (ERD) feature vector is formed. PMID:25972896

Face processing in different brain areas, and critical band masking.

PubMed

Rolls, Edmund T

2008-09-01

Neurophysiological evidence is described showing that some neurons in the macaque inferior temporal visual cortex have responses that are invariant with respect to the position, size, view, and spatial frequency of faces and objects, and that these neurons show rapid processing and rapid learning. Critical band spatial frequency masking is shown to be a property of these face-selective neurons and of the human visual perception of faces. Which face or object is present is encoded using a distributed representation in which each neuron conveys independent information in its firing rate, with little information evident in the relative time of firing of different neurons. This ensemble encoding has the advantages of maximizing the information in the representation useful for discrimination between stimuli using a simple weighted sum of the neuronal firing by the receiving neurons, generalization, and graceful degradation. These invariant representations are ideally suited to provide the inputs to brain regions such as the orbitofrontal cortex and amygdala that learn the reinforcement associations of an individual's face, for then the learning, and the appropriate social and emotional responses generalize to other views of the same face. A theory is described of how such invariant representations may be produced by self-organizing learning in a hierarchically organized set of visual cortical areas with convergent connectivity. The theory utilizes either temporal or spatial continuity with an associative synaptic modification rule. Another population of neurons in the cortex in the superior temporal sulcus encodes other aspects of faces such as face expression, eye-gaze, face view, and whether the head is moving. These neurons thus provide important additional inputs to parts of the brain such as the orbitofrontal cortex and amygdala that are involved in social communication and emotional behaviour. Outputs of these systems reach the amygdala, in which face-selective neurons are found, and also the orbitofrontal cortex, in which some neurons are tuned to face identity and others to face expression. In humans, activation of the orbitofrontal cortex is found when a change of face expression acts as a social signal that behaviour should change; and damage to the human orbitofrontal and pregenual cingulate cortex can impair face and voice expression identification, and also the reversal of emotional behaviour that normally occurs when reinforcers are reversed.

A preliminary study of subjective frequency estimates of words spoken in Cantonese.

PubMed

Yip, M C

2001-06-01

A database is presented of the subjective frequency estimates for a set of 30 Chinese homophones. The estimates are based on analysis of responses from a simple listening task by 120 University students. On the listening task, they are asked to mention the first meaning thought of upon hearing a Chinese homophone by writing down the corresponding Chinese characters. There was correlation of .66 between the frequency of spoken and written words, suggesting distributional information about the lexical representations is generally independent of modality. These subjective frequency counts should be useful in the construction of material sets for research on word recognition using spoken Chinese (Cantonese).

Thalamic input to auditory cortex is locally heterogeneous but globally tonotopic

PubMed Central

Vasquez-Lopez, Sebastian A; Weissenberger, Yves; Lohse, Michael; Keating, Peter; King, Andrew J

2017-01-01

Topographic representation of the receptor surface is a fundamental feature of sensory cortical organization. This is imparted by the thalamus, which relays information from the periphery to the cortex. To better understand the rules governing thalamocortical connectivity and the origin of cortical maps, we used in vivo two-photon calcium imaging to characterize the properties of thalamic axons innervating different layers of mouse auditory cortex. Although tonotopically organized at a global level, we found that the frequency selectivity of individual thalamocortical axons is surprisingly heterogeneous, even in layers 3b/4 of the primary cortical areas, where the thalamic input is dominated by the lemniscal projection. We also show that thalamocortical input to layer 1 includes collaterals from axons innervating layers 3b/4 and is largely in register with the main input targeting those layers. Such locally varied thalamocortical projections may be useful in enabling rapid contextual modulation of cortical frequency representations. PMID:28891466

The role of selected lexical factors on confrontation naming accuracy, speed, and fluency in adults who do and do not stutter.

PubMed

Newman, Rochelle S; Bernstein Ratner, Nan

2007-02-01

The purpose of this study was to investigate whether lexical access in adults who stutter (AWS) differs from that in people who do not stutter. Specifically, the authors examined the role of 3 lexical factors on naming speed, accuracy, and fluency: word frequency, neighborhood density, and neighborhood frequency. If stuttering results from an impairment in lexical access, these factors were hypothesized to differentially affect AWS performance on a confrontation naming task. Twenty-five AWS and 25 normally fluent comparison speakers, matched for age and education, participated in a confrontation naming task designed to explore within-speaker performance on naming accuracy, speed, and fluency based on stimulus word frequency and neighborhood characteristics. Accuracy, fluency, and reaction time (from acoustic waveform analysis) were computed. In general, AWS demonstrated the same effects of lexical factors on their naming as did adults who do not stutter. However, accuracy of naming was reduced for AWS. Stuttering rate was influenced by word frequency but not other factors. Results suggest that AWS could have a fundamental deficit in lexical retrieval, but this deficit is unlikely to be at the level of the word's abstract phonological representation. Implications for further research are discussed.

Time-Lapse Acoustic Impedance Inversion in CO2 Sequestration Study (Weyburn Field, Canada)

NASA Astrophysics Data System (ADS)

Wang, Y.; Morozov, I. B.

2016-12-01

Acoustic-impedance (AI) pseudo-logs are useful for characterising subtle variations of fluid content during seismic monitoring of reservoirs undergoing enhanced oil recovery and/or geologic CO2 sequestration. However, highly accurate AI images are required for time-lapse analysis, which may be difficult to achieve with conventional inversion approaches. In this study, two enhancements of time-lapse AI analysis are proposed. First, a well-known uncertainty of AI inversion is caused by the lack of low-frequency signal in reflection seismic data. To resolve this difficulty, we utilize an integrated AI inversion approach combining seismic data, acoustic well logs and seismic-processing velocities. The use of well logs helps stabilizing the recursive AI inverse, and seismic-processing velocities are used to complement the low-frequency information in seismic records. To derive the low-frequency AI from seismic-processing velocity data, an empirical relation is determined by using the available acoustic logs. This method is simple and does not require subjective choices of parameters and regularization schemes as in the more sophisticated joint inversion methods. The second improvement to accurate time-lapse AI imaging consists in time-variant calibration of reflectivity. Calibration corrections consist of time shifts, amplitude corrections, spectral shaping and phase rotations. Following the calibration, average and differential reflection amplitudes are calculated, from which the average and differential AI are obtained. The approaches are applied to a time-lapse 3-D 3-C dataset from Weyburn CO2 sequestration project in southern Saskatchewan, Canada. High quality time-lapse AI volumes are obtained. Comparisons with traditional recursive and colored AI inversions (obtained without using seismic-processing velocities) show that the new method gives a better representation of spatial AI variations. Although only early stages of monitoring seismic data are available, time-lapse AI variations mapped within and near the reservoir zone suggest correlations with CO2 injection. By extending this procedure to elastic impedances, additional constraints on the variations of physical properties within the reservoir can be obtained.

Temporary hearing loss influences post-stimulus time histogram and single neuron action potential estimates from human compound action potentials

PubMed Central

Lichtenhan, Jeffery T.; Chertoff, Mark E.

2008-01-01

An analytic compound action potential (CAP) obtained by convolving functional representations of the post-stimulus time histogram summed across auditory nerve neurons [P(t)] and a single neuron action potential [U(t)] was fit to human CAPs. The analytic CAP fit to pre- and postnoise-induced temporary hearing threshold shift (TTS) estimated in vivoP(t) and U(t) and the number of neurons contributing to the CAPs (N). The width of P(t) decreased with increasing signal level and was wider at the lowest signal level following noise exposure. P(t) latency decreased with increasing signal level and was shorter at all signal levels following noise exposure. The damping and oscillatory frequency of U(t) increased with signal level. For subjects with large amounts of TTS, U(t) had greater damping than before noise exposure particularly at low signal levels. Additionally, U(t) oscillation was lower in frequency at all click intensities following noise exposure. N increased with signal level and was smaller after noise exposure at the lowest signal level. Collectively these findings indicate that neurons contributing to the CAP during TTS are fewer in number, shorter in latency, and poorer in synchrony than before noise exposure. Moreover, estimates of single neuron action potentials may decay more rapidly and have a lower oscillatory frequency during TTS. PMID:18397026

Deep learning approaches for detection and removal of ghosting artifacts in MR spectroscopy.

PubMed

Kyathanahally, Sreenath P; Döring, André; Kreis, Roland

2018-09-01

To make use of deep learning (DL) methods to detect and remove ghosting artifacts in clinical magnetic resonance spectra of human brain. Deep learning algorithms, including fully connected neural networks, deep-convolutional neural networks, and stacked what-where auto encoders, were implemented to detect and correct MR spectra containing spurious echo ghost signals. The DL methods were trained on a huge database of simulated spectra with and without ghosting artifacts that represent complex variations of ghost-ridden spectra, transformed to time-frequency spectrograms. The trained model was tested on simulated and in vivo spectra. The preliminary results for ghost detection are very promising, reaching almost 100% accuracy, and the DL ghost removal methods show potential in simulated and in vivo spectra, but need further refinement and quantitative testing. Ghosting artifacts in spectroscopy are problematic, as they superimpose with metabolites and lead to inaccurate quantification. Detection and removal of ghosting artifacts using traditional machine learning approaches with feature extraction/selection is difficult, as ghosts appear at different frequencies. Here, we show that DL methods perform extremely well for ghost detection if the spectra are treated as images in the form of time-frequency representations. Further optimization for in vivo spectra will hopefully confirm their "ghostbusting" capacity. Magn Reson Med 80:851-863, 2018. © 2018 International Society for Magnetic Resonance in Medicine. © 2018 International Society for Magnetic Resonance in Medicine.

Space-Time Error Representation and Estimation in Navier-Stokes Calculations

NASA Technical Reports Server (NTRS)

Barth, Timothy J.

2006-01-01

The mathematical framework for a-posteriori error estimation of functionals elucidated by Eriksson et al. [7] and Becker and Rannacher [3] is revisited in a space-time context. Using these theories, a hierarchy of exact and approximate error representation formulas are presented for use in error estimation and mesh adaptivity. Numerical space-time results for simple model problems as well as compressible Navier-Stokes flow at Re = 300 over a 2D circular cylinder are then presented to demonstrate elements of the error representation theory for time-dependent problems.

Twelve months of active musical training in 8- to 10-year-old children enhances the preattentive processing of syllabic duration and voice onset time.

PubMed

Chobert, Julie; François, Clément; Velay, Jean-Luc; Besson, Mireille

2014-04-01

Musical training has been shown to positively influence linguistic abilities. To follow the developmental dynamics of this transfer effect at the preattentive level, we conducted a longitudinal study over 2 school years with nonmusician children randomly assigned to music or to painting training. We recorded the mismatch negativity (MMN), a cortical correlate of preattentive mismatch detection, to syllables that differed in vowel frequency, vowel duration, and voice onset time (VOT), using a test-training-retest procedure and 3 times of testing: before training, after 6 months and after 12 months of training. While no between-group differences were found before training, enhanced preattentive processing of syllabic duration and VOT, as reflected by greater MMN amplitude, but not of frequency, was found after 12 months of training in the music group only. These results demonstrate neuroplasticity in the child brain and suggest that active musical training rather than innate predispositions for music yielded the improvements in musically trained children. These results also highlight the influence of musical training for duration perception in speech and for the development of phonological representations in normally developing children. They support the importance of music-based training programs for children's education and open new remediation strategies for children with language-based learning impairments.

Respiratory sinus arrhythmia: time domain characterization using autoregressive moving average analysis

NASA Technical Reports Server (NTRS)

Triedman, J. K.; Perrott, M. H.; Cohen, R. J.; Saul, J. P.

1995-01-01

Fourier-based techniques are mathematically noncausal and are therefore limited in their application to feedback-containing systems, such as the cardiovascular system. In this study, a mathematically causal time domain technique, autoregressive moving average (ARMA) analysis, was used to parameterize the relations of respiration and arterial blood pressure to heart rate in eight humans before and during total cardiac autonomic blockade. Impulse-response curves thus generated showed the relation of respiration to heart rate to be characterized by an immediate increase in heart rate of 9.1 +/- 1.8 beats.min-1.l-1, followed by a transient mild decrease in heart rate to -1.2 +/- 0.5 beats.min-1.l-1 below baseline. The relation of blood pressure to heart rate was characterized by a slower decrease in heart rate of -0.5 +/- 0.1 beats.min-1.mmHg-1, followed by a gradual return to baseline. Both of these relations nearly disappeared after autonomic blockade, indicating autonomic mediation. Maximum values obtained from the respiration to heart rate impulse responses were also well correlated with frequency domain measures of high-frequency "vagal" heart rate control (r = 0.88). ARMA analysis may be useful as a time domain representation of autonomic heart rate control for cardiovascular modeling.

Numerical Investigation of the Acoustic Damping of Plane Acoustic Waves by Perforated Liners with Bias Flow

NASA Astrophysics Data System (ADS)

Zhao, Dan; Zhong, Zhi Yuan

Perforated liners are extensively used in aero-engines and gas turbine combustors to suppress combustion instabilities. These liners, typically subjected to a low Mach number bias flow (a cooling flow through perforated holes), are fitted along the bounding walls of a combustor to convert acoustic energy into flow energy by generating vorticity at the rims of the perforated apertures. To investigate the acoustic damping of such liners with bias flow on plane acoustic waves, a time-domain numerical model is developed to compute acoustic wave propagation in a cylindrical duct with a single-layer liner attached. The damping mechanism of the liner is characterized in real-time by using a 'compliance', developed especially for this work. It is a rational function representation of the frequency-domain homogeneous compliance adapted from the Rayleigh conductivity of a single aperture with mean bias flow in the z-domain. The liner 'compliance' model is then incorporated into partial differential equations of the duct system, which are solved by using the method of lines. The numerical results are then evaluated by comparing with the numerical results of Eldredge and Dowling's frequency-domain model. Good agreement is observed. This confirms that the model and the approach developed are suitable for real-time characterizing the acoustic damping of perforated liners.

Local air temperature tolerance: a sensible basis for estimating climate variability

NASA Astrophysics Data System (ADS)

Kärner, Olavi; Post, Piia

2016-11-01

The customary representation of climate using sample moments is generally biased due to the noticeably nonstationary behaviour of many climate series. In this study, we introduce a moment-free climate representation based on a statistical model fitted to a long-term daily air temperature anomaly series. This model allows us to separate the climate and weather scale variability in the series. As a result, the climate scale can be characterized using the mean annual cycle of series and local air temperature tolerance, where the latter is computed using the fitted model. The representation of weather scale variability is specified using the frequency and the range of outliers based on the tolerance. The scheme is illustrated using five long-term air temperature records observed by different European meteorological stations.

Meta-analysis of the effect of natural frequencies on Bayesian reasoning.

PubMed

McDowell, Michelle; Jacobs, Perke

2017-12-01

The natural frequency facilitation effect describes the finding that people are better able to solve descriptive Bayesian inference tasks when represented as joint frequencies obtained through natural sampling, known as natural frequencies, than as conditional probabilities. The present meta-analysis reviews 20 years of research seeking to address when, why, and for whom natural frequency formats are most effective. We review contributions from research associated with the 2 dominant theoretical perspectives, the ecological rationality framework and nested-sets theory, and test potential moderators of the effect. A systematic review of relevant literature yielded 35 articles representing 226 performance estimates. These estimates were statistically integrated using a bivariate mixed-effects model that yields summary estimates of average performances across the 2 formats and estimates of the effects of different study characteristics on performance. These study characteristics range from moderators representing individual characteristics (e.g., numeracy, expertise), to methodological differences (e.g., use of incentives, scoring criteria) and features of problem representation (e.g., short menu format, visual aid). Short menu formats (less computationally complex representations showing joint-events) and visual aids demonstrated some of the strongest moderation effects, improving performance for both conditional probability and natural frequency formats. A number of methodological factors (e.g., exposure to both problem formats) were also found to affect performance rates, emphasizing the importance of a systematic approach. We suggest how research on Bayesian reasoning can be strengthened by broadening the definition of successful Bayesian reasoning to incorporate choice and process and by applying different research methodologies. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

An infrared-visible image fusion scheme based on NSCT and compressed sensing

NASA Astrophysics Data System (ADS)

Zhang, Qiong; Maldague, Xavier

2015-05-01

Image fusion, as a research hot point nowadays in the field of infrared computer vision, has been developed utilizing different varieties of methods. Traditional image fusion algorithms are inclined to bring problems, such as data storage shortage and computational complexity increase, etc. Compressed sensing (CS) uses sparse sampling without knowing the priori knowledge and greatly reconstructs the image, which reduces the cost and complexity of image processing. In this paper, an advanced compressed sensing image fusion algorithm based on non-subsampled contourlet transform (NSCT) is proposed. NSCT provides better sparsity than the wavelet transform in image representation. Throughout the NSCT decomposition, the low-frequency and high-frequency coefficients can be obtained respectively. For the fusion processing of low-frequency coefficients of infrared and visible images , the adaptive regional energy weighting rule is utilized. Thus only the high-frequency coefficients are specially measured. Here we use sparse representation and random projection to obtain the required values of high-frequency coefficients, afterwards, the coefficients of each image block can be fused via the absolute maximum selection rule and/or the regional standard deviation rule. In the reconstruction of the compressive sampling results, a gradient-based iterative algorithm and the total variation (TV) method are employed to recover the high-frequency coefficients. Eventually, the fused image is recovered by inverse NSCT. Both the visual effects and the numerical computation results after experiments indicate that the presented approach achieves much higher quality of image fusion, accelerates the calculations, enhances various targets and extracts more useful information.