Digital communications study

NASA Technical Reports Server (NTRS)

Boorstyn, R. R.

1973-01-01

Research is reported dealing with problems of digital data transmission and computer communications networks. The results of four individual studies are presented which include: (1) signal processing with finite state machines, (2) signal parameter estimation from discrete-time observations, (3) digital filtering for radar signal processing applications, and (4) multiple server queues where all servers are not identical.

Discrete linear canonical transforms based on dilated Hermite functions.

PubMed

Pei, Soo-Chang; Lai, Yun-Chiu

2011-08-01

Linear canonical transform (LCT) is very useful and powerful in signal processing and optics. In this paper, discrete LCT (DLCT) is proposed to approximate LCT by utilizing the discrete dilated Hermite functions. The Wigner distribution function is also used to investigate DLCT performances in the time-frequency domain. Compared with the existing digital computation of LCT, our proposed DLCT possess additivity and reversibility properties with no oversampling involved. In addition, the length of input/output signals will not be changed before and after the DLCT transformations, which is consistent with the time-frequency area-preserving nature of LCT; meanwhile, the proposed DLCT has very good approximation of continuous LCT.

Electronic circuit detects left ventricular ejection events in cardiovascular system

NASA Technical Reports Server (NTRS)

Gebben, V. D.; Webb, J. A., Jr.

1972-01-01

Electronic circuit processes arterial blood pressure waveform to produce discrete signals that coincide with beginning and end of left ventricular ejection. Output signals provide timing signals for computers that monitor cardiovascular systems. Circuit operates reliably for heart rates between 50 and 200 beats per minute.

Development of morphogen gradient: The role of dimension and discreteness

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

Teimouri, Hamid; Kolomeisky, Anatoly B.

2014-02-28

The fundamental processes of biological development are governed by multiple signaling molecules that create non-uniform concentration profiles known as morphogen gradients. It is widely believed that the establishment of morphogen gradients is a result of complex processes that involve diffusion and degradation of locally produced signaling molecules. We developed a multi-dimensional discrete-state stochastic approach for investigating the corresponding reaction-diffusion models. It provided a full analytical description for stationary profiles and for important dynamic properties such as local accumulation times, variances, and mean first-passage times. The role of discreteness in developing of morphogen gradients is analyzed by comparing with available continuummore » descriptions. It is found that the continuum models prediction about multiple time scales near the source region in two-dimensional and three-dimensional systems is not supported in our analysis. Using ideas that view the degradation process as an effective potential, the effect of dimensionality on establishment of morphogen gradients is also discussed. In addition, we investigated how these reaction-diffusion processes are modified with changing the size of the source region.« less

Input-output characterization of an ultrasonic testing system by digital signal analysis

NASA Technical Reports Server (NTRS)

Williams, J. H., Jr.; Lee, S. S.; Karagulle, H.

1986-01-01

Ultrasonic test system input-output characteristics were investigated by directly coupling the transmitting and receiving transducers face to face without a test specimen. Some of the fundamentals of digital signal processing were summarized. Input and output signals were digitized by using a digital oscilloscope, and the digitized data were processed in a microcomputer by using digital signal-processing techniques. The continuous-time test system was modeled as a discrete-time, linear, shift-invariant system. In estimating the unit-sample response and frequency response of the discrete-time system, it was necessary to use digital filtering to remove low-amplitude noise, which interfered with deconvolution calculations. A digital bandpass filter constructed with the assistance of a Blackman window and a rectangular time window were used. Approximations of the impulse response and the frequency response of the continuous-time test system were obtained by linearly interpolating the defining points of the unit-sample response and the frequency response of the discrete-time system. The test system behaved as a linear-phase bandpass filter in the frequency range 0.6 to 2.3 MHz. These frequencies were selected in accordance with the criterion that they were 6 dB below the maximum peak of the amplitude of the frequency response. The output of the system to various inputs was predicted and the results were compared with the corresponding measurements on the system.

Discrete-State and Continuous Models of Recognition Memory: Testing Core Properties under Minimal Assumptions

ERIC Educational Resources Information Center

Kellen, David; Klauer, Karl Christoph

2014-01-01

A classic discussion in the recognition-memory literature concerns the question of whether recognition judgments are better described by continuous or discrete processes. These two hypotheses are instantiated by the signal detection theory model (SDT) and the 2-high-threshold model, respectively. Their comparison has almost invariably relied on…

A discrete in continuous mathematical model of cardiac progenitor cells formation and growth as spheroid clusters (Cardiospheres).

PubMed

Di Costanzo, Ezio; Giacomello, Alessandro; Messina, Elisa; Natalini, Roberto; Pontrelli, Giuseppe; Rossi, Fabrizio; Smits, Robert; Twarogowska, Monika

2018-03-14

We propose a discrete in continuous mathematical model describing the in vitro growth process of biophsy-derived mammalian cardiac progenitor cells growing as clusters in the form of spheres (Cardiospheres). The approach is hybrid: discrete at cellular scale and continuous at molecular level. In the present model, cells are subject to the self-organizing collective dynamics mechanism and, additionally, they can proliferate and differentiate, also depending on stochastic processes. The two latter processes are triggered and regulated by chemical signals present in the environment. Numerical simulations show the structure and the development of the clustered progenitors and are in a good agreement with the results obtained from in vitro experiments.

Investigation of charge coupled device correlation techniques

NASA Technical Reports Server (NTRS)

Lampe, D. R.; Lin, H. C.; Shutt, T. J.

1978-01-01

Analog Charge Transfer Devices (CTD's) offer unique advantages to signal processing systems, which often have large development costs, making it desirable to define those devices which can be developed for general system's use. Such devices are best identified and developed early to give system's designers some interchangeable subsystem blocks, not requiring additional individual development for each new signal processing system. The objective of this work is to describe a discrete analog signal processing device with a reasonably broad system use and to implement its design, fabrication, and testing.

The discrete prolate spheroidal filter as a digital signal processing tool

NASA Technical Reports Server (NTRS)

Mathews, J. D.; Breakall, J. K.; Karawas, G. K.

1983-01-01

The discrete prolate spheriodall (DPS) filter is one of the glass of nonrecursive finite impulse response (FIR) filters. The DPS filter is superior to other filters in this class in that it has maximum energy concentration in the frequency passband and minimum ringing in the time domain. A mathematical development of the DPS filter properties is given, along with information required to construct the filter. The properties of this filter were compared with those of the more commonly used filters of the same class. Use of the DPS filter allows for particularly meaningful statements of data time/frequency resolution cell values. The filter forms an especially useful tool for digital signal processing.

Nonlinear Estimation of Discrete-Time Signals Under Random Observation Delay

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

Caballero-Aguila, R.; Jimenez-Lopez, J. D.; Hermoso-Carazo, A.

2008-11-06

This paper presents an approximation to the nonlinear least-squares estimation problem of discrete-time stochastic signals using nonlinear observations with additive white noise which can be randomly delayed by one sampling time. The observation delay is modelled by a sequence of independent Bernoulli random variables whose values, zero or one, indicate that the real observation arrives on time or it is delayed and, hence, the available measurement to estimate the signal is not up-to-date. Assuming that the state-space model generating the signal is unknown and only the covariance functions of the processes involved in the observation equation are ready for use,more » a filtering algorithm based on linear approximations of the real observations is proposed.« less

Approximation of optimal filter for Ornstein-Uhlenbeck process with quantised discrete-time observation

NASA Astrophysics Data System (ADS)

Bania, Piotr; Baranowski, Jerzy

2018-02-01

Quantisation of signals is a ubiquitous property of digital processing. In many cases, it introduces significant difficulties in state estimation and in consequence control. Popular approaches either do not address properly the problem of system disturbances or lead to biased estimates. Our intention was to find a method for state estimation for stochastic systems with quantised and discrete observation, that is free of the mentioned drawbacks. We have formulated a general form of the optimal filter derived by a solution of Fokker-Planck equation. We then propose the approximation method based on Galerkin projections. We illustrate the approach for the Ornstein-Uhlenbeck process, and derive analytic formulae for the approximated optimal filter, also extending the results for the variant with control. Operation is illustrated with numerical experiments and compared with classical discrete-continuous Kalman filter. Results of comparison are substantially in favour of our approach, with over 20 times lower mean squared error. The proposed filter is especially effective for signal amplitudes comparable to the quantisation thresholds. Additionally, it was observed that for high order of approximation, state estimate is very close to the true process value. The results open the possibilities of further analysis, especially for more complex processes.

System and Method for Multi-Wavelength Optical Signal Detection

NASA Technical Reports Server (NTRS)

McGlone, Thomas D. (Inventor)

2017-01-01

The system and method for multi-wavelength optical signal detection enables the detection of optical signal levels significantly below those processed at the discrete circuit level by the use of mixed-signal processing methods implemented with integrated circuit technologies. The present invention is configured to detect and process small signals, which enables the reduction of the optical power required to stimulate detection networks, and lowers the required laser power to make specific measurements. The present invention provides an adaptation of active pixel networks combined with mixed-signal processing methods to provide an integer representation of the received signal as an output. The present invention also provides multi-wavelength laser detection circuits for use in various systems, such as a differential absorption light detection and ranging system.

Nonuniform sampling and non-Fourier signal processing methods in multidimensional NMR

PubMed Central

Mobli, Mehdi; Hoch, Jeffrey C.

2017-01-01

Beginning with the introduction of Fourier Transform NMR by Ernst and Anderson in 1966, time domain measurement of the impulse response (the free induction decay, FID) consisted of sampling the signal at a series of discrete intervals. For compatibility with the discrete Fourier transform (DFT), the intervals are kept uniform, and the Nyquist theorem dictates the largest value of the interval sufficient to avoid aliasing. With the proposal by Jeener of parametric sampling along an indirect time dimension, extension to multidimensional experiments employed the same sampling techniques used in one dimension, similarly subject to the Nyquist condition and suitable for processing via the discrete Fourier transform. The challenges of obtaining high-resolution spectral estimates from short data records using the DFT were already well understood, however. Despite techniques such as linear prediction extrapolation, the achievable resolution in the indirect dimensions is limited by practical constraints on measuring time. The advent of non-Fourier methods of spectrum analysis capable of processing nonuniformly sampled data has led to an explosion in the development of novel sampling strategies that avoid the limits on resolution and measurement time imposed by uniform sampling. The first part of this review discusses the many approaches to data sampling in multidimensional NMR, the second part highlights commonly used methods for signal processing of such data, and the review concludes with a discussion of other approaches to speeding up data acquisition in NMR. PMID:25456315

Directional dual-tree rational-dilation complex wavelet transform.

PubMed

Serbes, Gorkem; Gulcur, Halil Ozcan; Aydin, Nizamettin

2014-01-01

Dyadic discrete wavelet transform (DWT) has been used successfully in processing signals having non-oscillatory transient behaviour. However, due to the low Q-factor property of their wavelet atoms, the dyadic DWT is less effective in processing oscillatory signals such as embolic signals (ESs). ESs are extracted from quadrature Doppler signals, which are the output of Doppler ultrasound systems. In order to process ESs, firstly, a pre-processing operation known as phase filtering for obtaining directional signals from quadrature Doppler signals must be employed. Only then, wavelet based methods can be applied to these directional signals for further analysis. In this study, a directional dual-tree rational-dilation complex wavelet transform, which can be applied directly to quadrature signals and has the ability of extracting directional information during analysis, is introduced.

Input-output characterization of an ultrasonic testing system by digital signal analysis

NASA Technical Reports Server (NTRS)

Karaguelle, H.; Lee, S. S.; Williams, J., Jr.

1984-01-01

The input/output characteristics of an ultrasonic testing system used for stress wave factor measurements were studied. The fundamentals of digital signal processing are summarized. The inputs and outputs are digitized and processed in a microcomputer using digital signal processing techniques. The entire ultrasonic test system, including transducers and all electronic components, is modeled as a discrete-time linear shift-invariant system. Then the impulse response and frequency response of the continuous time ultrasonic test system are estimated by interpolating the defining points in the unit sample response and frequency response of the discrete time system. It is found that the ultrasonic test system behaves as a linear phase bandpass filter. Good results were obtained for rectangular pulse inputs of various amplitudes and durations and for tone burst inputs whose center frequencies are within the passband of the test system and for single cycle inputs of various amplitudes. The input/output limits on the linearity of the system are determined.

Energy and Timing Measurement with Time-Based Detector Readout for PET Applications: Principle and Validation with Discrete Circuit Components

PubMed Central

Sun, Xishan; Lan, Allan K.; Bircher, Chad; Deng, Zhi; Liu, Yinong; Shao, Yiping

2011-01-01

A new signal processing method for PET application has been developed, with discrete circuit components to measure energy and timing of a gamma interaction based solely on digital timing processing without using an amplitude-to-digital convertor (ADC) or a constant fraction discriminator (CFD). A single channel discrete component time-based readout (TBR) circuit was implemented in a PC board. Initial circuit functionality and performance evaluations have been conducted. Accuracy and linearity of signal amplitude measurement were excellent, as measured with test pulses. The measured timing accuracy from test pulses reached to less than 300 ps, a value limited mainly by the timing jitter of the prototype electronics circuit. Both suitable energy and coincidence timing resolutions (~18% and ~1.0 ns) have been achieved with 3 × 3 × 20 mm3 LYSO scintillator and photomultiplier tube-based detectors. With its relatively simple circuit and low cost, TBR is expected to be a suitable front-end signal readout electronics for compact PET or other radiation detectors requiring the reading of a large number of detector channels and demanding high performance for energy and timing measurement. PMID:21743761

Spectrum Control through Discrete Frequency Diffraction in the Presence of Photonic Gauge Potentials

NASA Astrophysics Data System (ADS)

Qin, Chengzhi; Zhou, Feng; Peng, Yugui; Sounas, Dimitrios; Zhu, Xuefeng; Wang, Bing; Dong, Jianji; Zhang, Xinliang; Alù; , Andrea; Lu, Peixiang

2018-03-01

By using optical phase modulators in a fiber-optical circuit, we theoretically and experimentally demonstrate large control over the spectrum of an impinging signal, which may evolve analogously to discrete diffraction in spatial waveguide arrays. The modulation phase acts as a photonic gauge potential in the frequency dimension, realizing efficient control of the central frequency and bandwidth of frequency combs. We experimentally achieve a 50 GHz frequency shift and threefold bandwidth expansion of an impinging comb, as well as the frequency analogue of various refraction phenomena, including negative refraction and perfect focusing in the frequency domain, both for discrete and continuous incident spectra. Our study paves a promising way towards versatile frequency management for optical communications and signal processing using time modulation schemes.

A VHDL Core for Intrinsic Evolution of Discrete Time Filters with Signal Feedback

NASA Technical Reports Server (NTRS)

Gwaltney, David A.; Dutton, Kenneth

2005-01-01

The design of an Evolvable Machine VHDL Core is presented, representing a discrete-time processing structure capable of supporting control system applications. This VHDL Core is implemented in an FPGA and is interfaced with an evolutionary algorithm implemented in firmware on a Digital Signal Processor (DSP) to create an evolvable system platform. The salient features of this architecture are presented. The capability to implement IIR filter structures is presented along with the results of the intrinsic evolution of a filter. The robustness of the evolved filter design is tested and its unique characteristics are described.

Nonuniform sampling and non-Fourier signal processing methods in multidimensional NMR.

PubMed

Mobli, Mehdi; Hoch, Jeffrey C

2014-11-01

Beginning with the introduction of Fourier Transform NMR by Ernst and Anderson in 1966, time domain measurement of the impulse response (the free induction decay, FID) consisted of sampling the signal at a series of discrete intervals. For compatibility with the discrete Fourier transform (DFT), the intervals are kept uniform, and the Nyquist theorem dictates the largest value of the interval sufficient to avoid aliasing. With the proposal by Jeener of parametric sampling along an indirect time dimension, extension to multidimensional experiments employed the same sampling techniques used in one dimension, similarly subject to the Nyquist condition and suitable for processing via the discrete Fourier transform. The challenges of obtaining high-resolution spectral estimates from short data records using the DFT were already well understood, however. Despite techniques such as linear prediction extrapolation, the achievable resolution in the indirect dimensions is limited by practical constraints on measuring time. The advent of non-Fourier methods of spectrum analysis capable of processing nonuniformly sampled data has led to an explosion in the development of novel sampling strategies that avoid the limits on resolution and measurement time imposed by uniform sampling. The first part of this review discusses the many approaches to data sampling in multidimensional NMR, the second part highlights commonly used methods for signal processing of such data, and the review concludes with a discussion of other approaches to speeding up data acquisition in NMR. Copyright © 2014 Elsevier B.V. All rights reserved.

Condensing Raman spectrum for single-cell phenotype analysis.

PubMed

Sun, Shiwei; Wang, Xuetao; Gao, Xin; Ren, Lihui; Su, Xiaoquan; Bu, Dongbo; Ning, Kang

2015-01-01

In recent years, high throughput and non-invasive Raman spectrometry technique has matured as an effective approach to identification of individual cells by species, even in complex, mixed populations. Raman profiling is an appealing optical microscopic method to achieve this. To fully utilize Raman proling for single-cell analysis, an extensive understanding of Raman spectra is necessary to answer questions such as which filtering methodologies are effective for pre-processing of Raman spectra, what strains can be distinguished by Raman spectra, and what features serve best as Raman-based biomarkers for single-cells, etc. In this work, we have proposed an approach called rDisc to discretize the original Raman spectrum into only a few (usually less than 20) representative peaks (Raman shifts). The approach has advantages in removing noises, and condensing the original spectrum. In particular, effective signal processing procedures were designed to eliminate noise, utilising wavelet transform denoising, baseline correction, and signal normalization. In the discretizing process, representative peaks were selected to signicantly decrease the Raman data size. More importantly, the selected peaks are chosen as suitable to serve as key biological markers to differentiate species and other cellular features. Additionally, the classication performance of discretized spectra was found to be comparable to full spectrum having more than 1000 Raman shifts. Overall, the discretized spectrum needs about 5storage space of a full spectrum and the processing speed is considerably faster. This makes rDisc clearly superior to other methods for single-cell classication.

Double Density Dual Tree Discrete Wavelet Transform implementation for Degraded Image Enhancement

NASA Astrophysics Data System (ADS)

Vimala, C.; Aruna Priya, P.

2018-04-01

Wavelet transform is a main tool for image processing applications in modern existence. A Double Density Dual Tree Discrete Wavelet Transform is used and investigated for image denoising. Images are considered for the analysis and the performance is compared with discrete wavelet transform and the Double Density DWT. Peak Signal to Noise Ratio values and Root Means Square error are calculated in all the three wavelet techniques for denoised images and the performance has evaluated. The proposed techniques give the better performance when comparing other two wavelet techniques.

Coherent-Phase Monitoring Of Cavitation In Turbomachines

NASA Technical Reports Server (NTRS)

Jong, Jen-Yi

1996-01-01

Digital electronic signal-processing system analyzes outputs of accelerometers mounted on turbomachine to detect vibrations characteristic of cavitation. Designed to overcome limitation imposed by interference from discrete components. System digitally implements technique called "coherent-phase wide-band demodulation" (CPWBD), using phase-only (PO) filtering along envelope detection to search for unique coherent-phase relationship associated with cavitation and to minimize influence of large-amplitude discrete components.

Real-Time and Memory Correlation via Acousto-Optic Processing,

DTIC Science & Technology

1978-06-01

acousto - optic technology as an answer to these requirements appears very attractive. Three fundamental signal-processing schemes using the acousto ... optic interaction have been investigated: (i) real-time correlation and convolution, (ii) Fourier and discrete Fourier transformation, and (iii

Fast transient digitizer

DOEpatents

Villa, Francesco

1982-01-01

Method and apparatus for sequentially scanning a plurality of target elements with an electron scanning beam modulated in accordance with variations in a high-frequency analog signal to provide discrete analog signal samples representative of successive portions of the analog signal; coupling the discrete analog signal samples from each of the target elements to a different one of a plurality of high speed storage devices; converting the discrete analog signal samples to equivalent digital signals; and storing the digital signals in a digital memory unit for subsequent measurement or display.

Axial mesendoderm refines rostrocaudal pattern in the chick nervous system.

PubMed

Rowan, A M; Stern, C D; Storey, K G

1999-07-01

There has long been controversy concerning the role of the axial mesoderm in the induction and rostrocaudal patterning of the vertebrate nervous system. Here we investigate the neural inducing and regionalising properties of defined rostrocaudal regions of head process/prospective notochord in the chick embryo by juxtaposing these tissues with extraembryonic epiblast or neural plate explants. We localise neural inducing signals to the emerging head process and using a large panel of region-specific neural markers, show that different rostrocaudal levels of the head process derived from headfold stage embryos can induce discrete regions of the central nervous system. However, we also find that rostral and caudal head process do not induce expression of any of these molecular markers in explants of the neural plate. During normal development the head process emerges beneath previously induced neural plate, which we show has already acquired some rostrocaudal character. Our findings therefore indicate that discrete regions of axial mesendoderm at headfold stages are not normally responsible for the establishment of rostrocaudal pattern in the neural plate. Strikingly however, we do find that caudal head process inhibits expression of rostral genes in neural plate explants. These findings indicate that despite the ability to induce specific rostrocaudal regions of the CNS de novo, signals provided by the discrete regions of axial mesendoderm do not appear to establish regional differences, but rather refine the rostrocaudal character of overlying neuroepithelium.

Discrete-Time Demodulator Architectures for Free-Space Broadband Optical Pulse-Position Modulation

NASA Technical Reports Server (NTRS)

Gray, A. A.; Lee, C.

2004-01-01

The objective of this work is to develop discrete-time demodulator architectures for broadband optical pulse-position modulation (PPM) that are capable of processing Nyquist or near-Nyquist data rates. These architectures are motivated by the numerous advantages of realizing communications demodulators in digital very large scale integrated (VLSI) circuits. The architectures are developed within a framework that encompasses a large body of work in optical communications, synchronization, and multirate discrete-time signal processing and are constrained by the limitations of the state of the art in digital hardware. This work attempts to create a bridge between theoretical communication algorithms and analysis for deep-space optical PPM and modern digital VLSI. The primary focus of this work is on the synthesis of discrete-time processing architectures for accomplishing the most fundamental functions required in PPM demodulators, post-detection filtering, synchronization, and decision processing. The architectures derived are capable of closely approximating the theoretical performance of the continuous-time algorithms from which they are derived. The work concludes with an outline of the development path that leads to hardware.

Discrete Walsh Hadamard transform based visible watermarking technique for digital color images

NASA Astrophysics Data System (ADS)

Santhi, V.; Thangavelu, Arunkumar

2011-10-01

As the size of the Internet is growing enormously the illegal manipulation of digital multimedia data become very easy with the advancement in technology tools. In order to protect those multimedia data from unauthorized access the digital watermarking system is used. In this paper a new Discrete walsh Hadamard Transform based visible watermarking system is proposed. As the watermark is embedded in transform domain, the system is robust to many signal processing attacks. Moreover in this proposed method the watermark is embedded in tiling manner in all the range of frequencies to make it robust to compression and cropping attack. The robustness of the algorithm is tested against noise addition, cropping, compression, Histogram equalization and resizing attacks. The experimental results show that the algorithm is robust to common signal processing attacks and the observed peak signal to noise ratio (PSNR) of watermarked image is varying from 20 to 30 db depends on the size of the watermark.

Two-dimensional signal processing with application to image restoration

NASA Technical Reports Server (NTRS)

Assefi, T.

1974-01-01

A recursive technique for modeling and estimating a two-dimensional signal contaminated by noise is presented. A two-dimensional signal is assumed to be an undistorted picture, where the noise introduces the distortion. Both the signal and the noise are assumed to be wide-sense stationary processes with known statistics. Thus, to estimate the two-dimensional signal is to enhance the picture. The picture representing the two-dimensional signal is converted to one dimension by scanning the image horizontally one line at a time. The scanner output becomes a nonstationary random process due to the periodic nature of the scanner operation. Procedures to obtain a dynamical model corresponding to the autocorrelation function of the scanner output are derived. Utilizing the model, a discrete Kalman estimator is designed to enhance the image.

Discrete roles and bifurcation of PTEN signaling and mTORC1-mediated anabolic metabolism underlie IL-7–driven B lymphopoiesis

PubMed Central

Zeng, Hu; Yu, Mei; Tan, Haiyan; Li, Yuxin; Su, Wei; Shi, Hao; Dhungana, Yogesh; Guy, Cliff; Neale, Geoffrey; Cloer, Caryn; Peng, Junmin; Wang, Demin; Chi, Hongbo

2018-01-01

Interleukin-7 (IL-7) drives early B lymphopoiesis, but the underlying molecular circuits remain poorly understood, especially how Stat5 (signal transducer and activator of transcription 5)–dependent and Stat5-independent pathways contribute to this process. Combining transcriptome and proteome analyses and mouse genetic models, we show that IL-7 promotes anabolic metabolism and biosynthetic programs in pro-B cells. IL-7–mediated activation of mTORC1 (mechanistic target of rapamycin complex 1) supported cell proliferation and metabolism in a Stat5-independent, Myc-dependent manner but was largely dispensable for cell survival or Rag1 and Rag2 gene expression. mTORC1 was also required for Myc-driven lymphomagenesis. PI3K (phosphatidylinositol 3-kinase) and mTORC1 had discrete effects on Stat5 signaling and independently controlled B cell development. PI3K was actively suppressed by PTEN (phosphatase and tensin homolog) in pro-B cells to ensure proper IL-7R expression, Stat5 activation, heavy chain rearrangement, and cell survival, suggesting the unexpected bifurcation of the classical PI3K-mTOR signaling. Together, our integrative analyses establish IL-7R–mTORC1–Myc and PTEN-mediated PI3K suppression as discrete signaling axes driving B cell development, with differential effects on IL-7R–Stat5 signaling. PMID:29399633

Automated wavelet denoising of photoacoustic signals for circulating melanoma cell detection and burn image reconstruction.

PubMed

Holan, Scott H; Viator, John A

2008-06-21

Photoacoustic image reconstruction may involve hundreds of point measurements, each of which contributes unique information about the subsurface absorbing structures under study. For backprojection imaging, two or more point measurements of photoacoustic waves induced by irradiating a biological sample with laser light are used to produce an image of the acoustic source. Each of these measurements must undergo some signal processing, such as denoising or system deconvolution. In order to process the numerous signals, we have developed an automated wavelet algorithm for denoising signals. We appeal to the discrete wavelet transform for denoising photoacoustic signals generated in a dilute melanoma cell suspension and in thermally coagulated blood. We used 5, 9, 45 and 270 melanoma cells in the laser beam path as test concentrations. For the burn phantom, we used coagulated blood in 1.6 mm silicon tube submerged in Intralipid. Although these two targets were chosen as typical applications for photoacoustic detection and imaging, they are of independent interest. The denoising employs level-independent universal thresholding. In order to accommodate nonradix-2 signals, we considered a maximal overlap discrete wavelet transform (MODWT). For the lower melanoma cell concentrations, as the signal-to-noise ratio approached 1, denoising allowed better peak finding. For coagulated blood, the signals were denoised to yield a clean photoacoustic resulting in an improvement of 22% in the reconstructed image. The entire signal processing technique was automated so that minimal user intervention was needed to reconstruct the images. Such an algorithm may be used for image reconstruction and signal extraction for applications such as burn depth imaging, depth profiling of vascular lesions in skin and the detection of single cancer cells in blood samples.

Uncertainty relation for the discrete Fourier transform.

PubMed

Massar, Serge; Spindel, Philippe

2008-05-16

We derive an uncertainty relation for two unitary operators which obey a commutation relation of the form UV=e(i phi) VU. Its most important application is to constrain how much a quantum state can be localized simultaneously in two mutually unbiased bases related by a discrete fourier transform. It provides an uncertainty relation which smoothly interpolates between the well-known cases of the Pauli operators in two dimensions and the continuous variables position and momentum. This work also provides an uncertainty relation for modular variables, and could find applications in signal processing. In the finite dimensional case the minimum uncertainty states, discrete analogues of coherent and squeezed states, are minimum energy solutions of Harper's equation, a discrete version of the harmonic oscillator equation.

Online frequency estimation with applications to engine and generator sets

NASA Astrophysics Data System (ADS)

Manngård, Mikael; Böling, Jari M.

2017-07-01

Frequency and spectral analysis based on the discrete Fourier transform is a fundamental task in signal processing and machine diagnostics. This paper aims at presenting computationally efficient methods for real-time estimation of stationary and time-varying frequency components in signals. A brief survey of the sliding time window discrete Fourier transform and Goertzel filter is presented, and two filter banks consisting of: (i) sliding time window Goertzel filters (ii) infinite impulse response narrow bandpass filters are proposed for estimating instantaneous frequencies. The proposed methods show excellent results on both simulation studies and on a case study using angular speed data measurements of the crankshaft of a marine diesel engine-generator set.

Analog Module Architecture for Space-Qualified Field-Programmable Mixed-Signal Arrays

NASA Technical Reports Server (NTRS)

Edwards, R. Timothy; Strohbehn, Kim; Jaskulek, Steven E.; Katz, Richard

1999-01-01

Spacecraft require all manner of both digital and analog circuits. Onboard digital systems are constructed almost exclusively from field-programmable gate array (FPGA) circuits providing numerous advantages over discrete design including high integration density, high reliability, fast turn-around design cycle time, lower mass, volume, and power consumption, and lower parts acquisition and flight qualification costs. Analog and mixed-signal circuits perform tasks ranging from housekeeping to signal conditioning and processing. These circuits are painstakingly designed and built using discrete components due to a lack of options for field-programmability. FPAA (Field-Programmable Analog Array) and FPMA (Field-Programmable Mixed-signal Array) parts exist but not in radiation-tolerant technology and not necessarily in an architecture optimal for the design of analog circuits for spaceflight applications. This paper outlines an architecture proposed for an FPAA fabricated in an existing commercial digital CMOS process used to make radiation-tolerant antifuse-based FPGA devices. The primary concerns are the impact of the technology and the overall array architecture on the flexibility of programming, the bandwidth available for high-speed analog circuits, and the accuracy of the components for high-performance applications.

A new stationary gridline artifact suppression method based on the 2D discrete wavelet transform

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

Tang, Hui, E-mail: corinna@seu.edu.cn; Key Laboratory of Computer Network and Information Integration; Centre de Recherche en Information Biomédicale sino-français, Laboratoire International Associé, Inserm, Université de Rennes 1, Rennes 35000

2015-04-15

Purpose: In digital x-ray radiography, an antiscatter grid is inserted between the patient and the image receptor to reduce scattered radiation. If the antiscatter grid is used in a stationary way, gridline artifacts will appear in the final image. In most of the gridline removal image processing methods, the useful information with spatial frequencies close to that of the gridline is usually lost or degraded. In this study, a new stationary gridline suppression method is designed to preserve more of the useful information. Methods: The method is as follows. The input image is first recursively decomposed into several smaller subimagesmore » using a multiscale 2D discrete wavelet transform. The decomposition process stops when the gridline signal is found to be greater than a threshold in one or several of these subimages using a gridline detection module. An automatic Gaussian band-stop filter is then applied to the detected subimages to remove the gridline signal. Finally, the restored image is achieved using the corresponding 2D inverse discrete wavelet transform. Results: The processed images show that the proposed method can remove the gridline signal efficiently while maintaining the image details. The spectra of a 1D Fourier transform of the processed images demonstrate that, compared with some existing gridline removal methods, the proposed method has better information preservation after the removal of the gridline artifacts. Additionally, the performance speed is relatively high. Conclusions: The experimental results demonstrate the efficiency of the proposed method. Compared with some existing gridline removal methods, the proposed method can preserve more information within an acceptable execution time.« less

Study of interhemispheric asymmetries in electroencephalographic signals by frequency analysis

NASA Astrophysics Data System (ADS)

Zapata, J. F.; Garzón, J.

2011-01-01

This study provides a new method for the detection of interhemispheric asymmetries in patients with continuous video-electroencephalography (EEG) monitoring at Intensive Care Unit (ICU), using wavelet energy. We obtained the registration of EEG signals in 42 patients with different pathologies, and then we proceeded to perform signal processing using the Matlab program, we compared the abnormalities recorded in the report by the neurophysiologist, the images of each patient and the result of signals analysis with the Discrete Wavelet Transform (DWT). Conclusions: there exists correspondence between the abnormalities found in the processing of the signal with the clinical reports of findings in patients; according to previous conclusion, the methodology used can be a useful tool for diagnosis and early quantitative detection of interhemispheric asymmetries.

Application of simulation models for the optimization of business processes

NASA Astrophysics Data System (ADS)

Jašek, Roman; Sedláček, Michal; Chramcov, Bronislav; Dvořák, Jiří

2016-06-01

The paper deals with the applications of modeling and simulation tools in the optimization of business processes, especially in solving an optimization of signal flow in security company. As a modeling tool was selected Simul8 software that is used to process modeling based on discrete event simulation and which enables the creation of a visual model of production and distribution processes.

Optical signal processing of spatially distributed sensor data in smart structures

NASA Technical Reports Server (NTRS)

Bennett, K. D.; Claus, R. O.; Murphy, K. A.; Goette, A. M.

1989-01-01

Smart structures which contain dense two- or three-dimensional arrays of attached or embedded sensor elements inherently require signal multiplexing and processing capabilities to permit good spatial data resolution as well as the adequately short calculation times demanded by real time active feedback actuator drive circuitry. This paper reports the implementation of an in-line optical signal processor and its application in a structural sensing system which incorporates multiple discrete optical fiber sensor elements. The signal processor consists of an array of optical fiber couplers having tailored s-parameters and arranged to allow gray code amplitude scaling of sensor inputs. The use of this signal processor in systems designed to indicate the location of distributed strain and damage in composite materials, as well as to quantitatively characterize that damage, is described. Extension of similar signal processing methods to more complicated smart materials and structures applications are discussed.

Bayesian estimation of the discrete coefficient of determination.

PubMed

Chen, Ting; Braga-Neto, Ulisses M

2016-12-01

The discrete coefficient of determination (CoD) measures the nonlinear interaction between discrete predictor and target variables and has had far-reaching applications in Genomic Signal Processing. Previous work has addressed the inference of the discrete CoD using classical parametric and nonparametric approaches. In this paper, we introduce a Bayesian framework for the inference of the discrete CoD. We derive analytically the optimal minimum mean-square error (MMSE) CoD estimator, as well as a CoD estimator based on the Optimal Bayesian Predictor (OBP). For the latter estimator, exact expressions for its bias, variance, and root-mean-square (RMS) are given. The accuracy of both Bayesian CoD estimators with non-informative and informative priors, under fixed or random parameters, is studied via analytical and numerical approaches. We also demonstrate the application of the proposed Bayesian approach in the inference of gene regulatory networks, using gene-expression data from a previously published study on metastatic melanoma.

Discrete dynamic modeling of cellular signaling networks.

PubMed

Albert, Réka; Wang, Rui-Sheng

2009-01-01

Understanding signal transduction in cellular systems is a central issue in systems biology. Numerous experiments from different laboratories generate an abundance of individual components and causal interactions mediating environmental and developmental signals. However, for many signal transduction systems there is insufficient information on the overall structure and the molecular mechanisms involved in the signaling network. Moreover, lack of kinetic and temporal information makes it difficult to construct quantitative models of signal transduction pathways. Discrete dynamic modeling, combined with network analysis, provides an effective way to integrate fragmentary knowledge of regulatory interactions into a predictive mathematical model which is able to describe the time evolution of the system without the requirement for kinetic parameters. This chapter introduces the fundamental concepts of discrete dynamic modeling, particularly focusing on Boolean dynamic models. We describe this method step-by-step in the context of cellular signaling networks. Several variants of Boolean dynamic models including threshold Boolean networks and piecewise linear systems are also covered, followed by two examples of successful application of discrete dynamic modeling in cell biology.

Design and application of discrete wavelet packet transform based multiresolution controller for liquid level system.

PubMed

Paul, Rimi; Sengupta, Anindita

2017-11-01

A new controller based on discrete wavelet packet transform (DWPT) for liquid level system (LLS) has been presented here. This controller generates control signal using node coefficients of the error signal which interprets many implicit phenomena such as process dynamics, measurement noise and effect of external disturbances. Through simulation results on LLS problem, this controller is shown to perform faster than both the discrete wavelet transform based controller and conventional proportional integral controller. Also, it is more efficient in terms of its ability to provide better noise rejection. To overcome the wind up phenomenon by considering the saturation due to presence of actuator, anti-wind up technique is applied to the conventional PI controller and compared to the wavelet packet transform based controller. In this case also, packet controller is found better than the other ones. This similar work has been extended for analogous first order RC plant as well as second order plant also. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Discrete Dynamics Model for the Speract-Activated Ca2+ Signaling Network Relevant to Sperm Motility

PubMed Central

Espinal, Jesús; Aldana, Maximino; Guerrero, Adán; Wood, Christopher

2011-01-01

Understanding how spermatozoa approach the egg is a central biological issue. Recently a considerable amount of experimental evidence has accumulated on the relation between oscillations in intracellular calcium ion concentration ([Ca]) in the sea urchin sperm flagellum, triggered by peptides secreted from the egg, and sperm motility. Determination of the structure and dynamics of the signaling pathway leading to these oscillations is a fundamental problem. However, a biochemically based formulation for the comprehension of the molecular mechanisms operating in the axoneme as a response to external stimulus is still lacking. Based on experiments on the S. purpuratus sea urchin spermatozoa, we propose a signaling network model where nodes are discrete variables corresponding to the pathway elements and the signal transmission takes place at discrete time intervals according to logical rules. The validity of this model is corroborated by reproducing previous empirically determined signaling features. Prompted by the model predictions we performed experiments which identified novel characteristics of the signaling pathway. We uncovered the role of a high voltage-activated channel as a regulator of the delay in the onset of fluctuations after activation of the signaling cascade. This delay time has recently been shown to be an important regulatory factor for sea urchin sperm reorientation. Another finding is the participation of a voltage-dependent calcium-activated channel in the determination of the period of the fluctuations. Furthermore, by analyzing the spread of network perturbations we find that it operates in a dynamically critical regime. Our work demonstrates that a coarse-grained approach to the dynamics of the signaling pathway is capable of revealing regulatory sperm navigation elements and provides insight, in terms of criticality, on the concurrence of the high robustness and adaptability that the reproduction processes are predicted to have developed throughout evolution. PMID:21857937

Digital color representation

DOEpatents

White, James M.; Faber, Vance; Saltzman, Jeffrey S.

1992-01-01

An image population having a large number of attributes is processed to form a display population with a predetermined smaller number of attributes which represent the larger number of attributes. In a particular application, the color values in an image are compressed for storage in a discrete lookup table (LUT) where an 8-bit data signal is enabled to form a display of 24-bit color values. The LUT is formed in a sampling and averaging process from the image color values with no requirement to define discrete Voronoi regions for color compression. Image color values are assigned 8-bit pointers to their closest LUT value whereby data processing requires only the 8-bit pointer value to provide 24-bit color values from the LUT.

Experimental phase synchronization detection in non-phase coherent chaotic systems by using the discrete complex wavelet approach

NASA Astrophysics Data System (ADS)

Ferreira, Maria Teodora; Follmann, Rosangela; Domingues, Margarete O.; Macau, Elbert E. N.; Kiss, István Z.

2017-08-01

Phase synchronization may emerge from mutually interacting non-linear oscillators, even under weak coupling, when phase differences are bounded, while amplitudes remain uncorrelated. However, the detection of this phenomenon can be a challenging problem to tackle. In this work, we apply the Discrete Complex Wavelet Approach (DCWA) for phase assignment, considering signals from coupled chaotic systems and experimental data. The DCWA is based on the Dual-Tree Complex Wavelet Transform (DT-CWT), which is a discrete transformation. Due to its multi-scale properties in the context of phase characterization, it is possible to obtain very good results from scalar time series, even with non-phase-coherent chaotic systems without state space reconstruction or pre-processing. The method correctly predicts the phase synchronization for a chemical experiment with three locally coupled, non-phase-coherent chaotic processes. The impact of different time-scales is demonstrated on the synchronization process that outlines the advantages of DCWA for analysis of experimental data.

75 FR 68177 - Airworthiness Directives; The Boeing Company Model 757 and 767 Airplanes

Federal Register 2010, 2011, 2012, 2013, 2014

2010-11-05

... and FUEL CONFIG discrete signals from the fuel quantity processor unit, and alerts the flightcrew of a... the FUEL CONFIG discrete signal, which disables both the FUEL CONFIG and LOW FUEL messages. Such... depleted below the minimum of 2,200 pounds. The EICAS receives both the LOW FUEL and FUEL CONFIG discrete...

The application of the analog signal to discrete time interval converter to the signal conditioner power supplies

NASA Technical Reports Server (NTRS)

Schoenfeld, A. D.; Yu, Y.

1973-01-01

The Analog Signal to Discrete Time Interval Converter microminiaturized module was utilized to control the signal conditioner power supplies. The multi-loop control provides outstanding static and dynamic performance characteristics, exceeding those generally associated with single-loop regulators. Eight converter boards, each containing three independent dc to dc converter, were built, tested, and delivered.

Properties of the Magnitude Terms of Orthogonal Scaling Functions.

PubMed

Tay, Peter C; Havlicek, Joseph P; Acton, Scott T; Hossack, John A

2010-09-01

The spectrum of the convolution of two continuous functions can be determined as the continuous Fourier transform of the cross-correlation function. The same can be said about the spectrum of the convolution of two infinite discrete sequences, which can be determined as the discrete time Fourier transform of the cross-correlation function of the two sequences. In current digital signal processing, the spectrum of the contiuous Fourier transform and the discrete time Fourier transform are approximately determined by numerical integration or by densely taking the discrete Fourier transform. It has been shown that all three transforms share many analogous properties. In this paper we will show another useful property of determining the spectrum terms of the convolution of two finite length sequences by determining the discrete Fourier transform of the modified cross-correlation function. In addition, two properties of the magnitude terms of orthogonal wavelet scaling functions are developed. These properties are used as constraints for an exhaustive search to determine an robust lower bound on conjoint localization of orthogonal scaling functions.

Recruitment of discrete regions of the psoas major and quadratus lumborum muscles is changed in specific sitting postures in individuals with recurrent low back pain.

PubMed

Park, Rachel J; Tsao, Henry; Claus, Andrew; Cresswell, Andrew G; Hodges, Paul W

2013-11-01

Cross-sectional controlled laboratory study. To investigate potential changes in the function of discrete regions of the psoas major (PM) and quadratus lumborum (QL) with changes in spinal curvatures and hip positions in sitting, in people with recurrent low back pain (LBP). Although the PM and QL contribute to control of spinal curvature in sitting, whether activity of these muscles is changed in individuals with LBP is unknown. Ten volunteers with recurrent LBP (pain free at the time of testing) and 9 pain-free individuals in a comparison group participated. Participants with LBP were grouped into those with high and low erector spinae (ES) electromyographic (EMG) signal amplitude, recorded when sitting with a lumbar lordosis. Data were recorded as participants assumed 3 sitting postures. Fine-wire electrodes were inserted with ultrasound guidance into fascicles of the PM arising from the transverse process and vertebral body, and the anterior and posterior layers of the QL. When data from those with recurrent LBP were analyzed as 1 group, PM and QL EMG signal amplitudes did not differ between groups in any of the sitting postures. However, when subgrouped, those with low ES EMG had greater EMG signal amplitude of the PM vertebral body and QL posterior layer in flat posture and greater EMG signal amplitude of the QL posterior layer in short lordotic posture, compared to those in the pain-free group. For the group with high ES EMG, the PM transverse process and PM vertebral body EMG was less than that of the other LBP group in short lordotic posture. The findings suggest a redistribution of activity between muscles that have a potential extensor moment in individuals with LBP. The modification of EMG of discrete fascicles of the PM and QL was related to changes in ES EMG signal amplitude recorded in sitting.

Rapid update of discrete Fourier transform for real-time signal processing

NASA Astrophysics Data System (ADS)

Sherlock, Barry G.; Kakad, Yogendra P.

2001-10-01

In many identification and target recognition applications, the incoming signal will have properties that render it amenable to analysis or processing in the Fourier domain. In such applications, however, it is usually essential that the identification or target recognition be performed in real time. An important constraint upon real-time processing in the Fourier domain is the time taken to perform the Discrete Fourier Transform (DFT). Ideally, a new Fourier transform should be obtained after the arrival of every new data point. However, the Fast Fourier Transform (FFT) algorithm requires on the order of N log2 N operations, where N is the length of the transform, and this usually makes calculation of the transform for every new data point computationally prohibitive. In this paper, we develop an algorithm to update the existing DFT to represent the new data series that results when a new signal point is received. Updating the DFT in this way uses less computational order by a factor of log2 N. The algorithm can be modified to work in the presence of data window functions. This is a considerable advantage, because windowing is often necessary to reduce edge effects that occur because the implicit periodicity of the Fourier transform is not exhibited by the real-world signal. Versions are developed in this paper for use with the boxcar window, the split triangular, Hanning, Hamming, and Blackman windows. Generalization of these results to 2D is also presented.

Collaborative Wideband Compressed Signal Detection in Interplanetary Internet

NASA Astrophysics Data System (ADS)

Wang, Yulin; Zhang, Gengxin; Bian, Dongming; Gou, Liang; Zhang, Wei

2014-07-01

As the development of autonomous radio in deep space network, it is possible to actualize communication between explorers, aircrafts, rovers and satellites, e.g. from different countries, adopting different signal modes. The first mission to enforce the autonomous radio is to detect signals of the explorer autonomously without disturbing the original communication. This paper develops a collaborative wideband compressed signal detection approach for InterPlaNetary (IPN) Internet where there exist sparse active signals in the deep space environment. Compressed sensing (CS) can be utilized by exploiting the sparsity of IPN Internet communication signal, whose useful frequency support occupies only a small portion of an entirely wide spectrum. An estimate of the signal spectrum can be obtained by using reconstruction algorithms. Against deep space shadowing and channel fading, multiple satellites collaboratively sense and make a final decision according to certain fusion rule to gain spatial diversity. A couple of novel discrete cosine transform (DCT) and walsh-hadamard transform (WHT) based compressed spectrum detection methods are proposed which significantly improve the performance of spectrum recovery and signal detection. Finally, extensive simulation results are presented to show the effectiveness of our proposed collaborative scheme for signal detection in IPN Internet. Compared with the conventional discrete fourier transform (DFT) based method, our DCT and WHT based methods reduce computational complexity, decrease processing time, save energy and enhance probability of detection.

Maximum likelihood estimation of signal-to-noise ratio and combiner weight

NASA Technical Reports Server (NTRS)

Kalson, S.; Dolinar, S. J.

1986-01-01

An algorithm for estimating signal to noise ratio and combiner weight parameters for a discrete time series is presented. The algorithm is based upon the joint maximum likelihood estimate of the signal and noise power. The discrete-time series are the sufficient statistics obtained after matched filtering of a biphase modulated signal in additive white Gaussian noise, before maximum likelihood decoding is performed.

A discrete cell model with adaptive signalling for aggregation of Dictyostelium discoideum.

PubMed Central

Dallon, J C; Othmer, H G

1997-01-01

Dictyostelium discoideum (Dd) is a widely studied model system from which fundamental insights into cell movement, chemotaxis, aggregation and pattern formation can be gained. In this system aggregation results from the chemotactic response by dispersed amoebae to a travelling wave of the chemoattractant cAMP. We have developed a model in which the cells are treated as discrete points in a continuum field of the chemoattractant, and transduction of the extracellular cAMP signal into the intracellular signal is based on the G protein model developed by Tang & Othmer. The model reproduces a number of experimental observations and gives further insight into the aggregation process. We investigate different rules for cell movement the factors that influence stream formation the effect on aggregation of noise in the choice of the direction of movement and when spiral waves of chemoattractant and cell density are likely to occur. Our results give new insight into the origin of spiral waves and suggest that streaming is due to a finite amplitude instability. PMID:9134569

Discrete wavelet transform: a tool in smoothing kinematic data.

PubMed

Ismail, A R; Asfour, S S

1999-03-01

Motion analysis systems typically introduce noise to the displacement data recorded. Butterworth digital filters have been used to smooth the displacement data in order to obtain smoothed velocities and accelerations. However, this technique does not yield satisfactory results, especially when dealing with complex kinematic motions that occupy the low- and high-frequency bands. The use of the discrete wavelet transform, as an alternative to digital filters, is presented in this paper. The transform passes the original signal through two complementary low- and high-pass FIR filters and decomposes the signal into an approximation function and a detail function. Further decomposition of the signal results in transforming the signal into a hierarchy set of orthogonal approximation and detail functions. A reverse process is employed to perfectly reconstruct the signal (inverse transform) back from its approximation and detail functions. The discrete wavelet transform was applied to the displacement data recorded by Pezzack et al., 1977. The smoothed displacement data were twice differentiated and compared to Pezzack et al.'s acceleration data in order to choose the most appropriate filter coefficients and decomposition level on the basis of maximizing the percentage of retained energy (PRE) and minimizing the root mean square error (RMSE). Daubechies wavelet of the fourth order (Db4) at the second decomposition level showed better results than both the biorthogonal and Coiflet wavelets (PRE = 97.5%, RMSE = 4.7 rad s-2). The Db4 wavelet was then used to compress complex displacement data obtained from a noisy mathematically generated function. Results clearly indicate superiority of this new smoothing approach over traditional filters.

Simplified signal processing for impedance spectroscopy with spectrally sparse sequences

NASA Astrophysics Data System (ADS)

Annus, P.; Land, R.; Reidla, M.; Ojarand, J.; Mughal, Y.; Min, M.

2013-04-01

Classical method for measurement of the electrical bio-impedance involves excitation with sinusoidal waveform. Sinusoidal excitation at fixed frequency points enables wide variety of signal processing options, most general of them being Fourier transform. Multiplication with two quadrature waveforms at desired frequency could be easily accomplished both in analogue and in digital domains, even simplest quadrature square waves can be considered, which reduces signal processing task in analogue domain to synchronous switching followed by low pass filter, and in digital domain requires only additions. So called spectrally sparse excitation sequences (SSS), which have been recently introduced into bio-impedance measurement domain, are very reasonable choice when simultaneous multifrequency excitation is required. They have many good properties, such as ease of generation and good crest factor compared to similar multisinusoids. Typically, the usage of discrete or fast Fourier transform in signal processing step is considered so far. Usage of simplified methods nevertheless would reduce computational burden, and enable simpler, less costly and less energy hungry signal processing platforms. Accuracy of the measurement with SSS excitation when using different waveforms for quadrature demodulation will be compared in order to evaluate the feasibility of the simplified signal processing. Sigma delta modulated sinusoid (binary signal) is considered to be a good alternative for a synchronous demodulation.

BPSK Demodulation Using Digital Signal Processing

NASA Technical Reports Server (NTRS)

Garcia, Thomas R.

1996-01-01

A digital communications signal is a sinusoidal waveform that is modified by a binary (digital) information signal. The sinusoidal waveform is called the carrier. The carrier may be modified in amplitude, frequency, phase, or a combination of these. In this project a binary phase shift keyed (BPSK) signal is the communication signal. In a BPSK signal the phase of the carrier is set to one of two states, 180 degrees apart, by a binary (i.e., 1 or 0) information signal. A digital signal is a sampled version of a "real world" time continuous signal. The digital signal is generated by sampling the continuous signal at discrete points in time. The rate at which the signal is sampled is called the sampling rate (f(s)). The device that performs this operation is called an analog-to-digital (A/D) converter or a digitizer. The digital signal is composed of the sequence of individual values of the sampled BPSK signal. Digital signal processing (DSP) is the modification of the digital signal by mathematical operations. A device that performs this processing is called a digital signal processor. After processing, the digital signal may then be converted back to an analog signal using a digital-to-analog (D/A) converter. The goal of this project is to develop a system that will recover the digital information from a BPSK signal using DSP techniques. The project is broken down into the following steps: (1) Development of the algorithms required to demodulate the BPSK signal; (2) Simulation of the system; and (3) Implementation a BPSK receiver using digital signal processing hardware.

Analysis of sEMG signals using discrete wavelet transform for muscle fatigue detection

NASA Astrophysics Data System (ADS)

Flórez-Prias, L. A.; Contreras-Ortiz, S. H.

2017-11-01

The purpose of the present article is to characterize sEMG signals to determine muscular fatigue levels. To do this, the signal is decomposed using the discrete wavelet transform, which offers noise filtering features, simplicity and efficiency. sEMG signals on the forearm were acquired and analyzed during the execution of cyclic muscular contractions in the presence and absence of fatigue. When the muscle fatigues, the sEMG signal shows a more erratic behavior of the signal as more energy is required to maintain the effort levels.

Mathematical model of macrophage-facilitated breast cancer cells invasion.

PubMed

Knútsdóttir, Hildur; Pálsson, Eirikur; Edelstein-Keshet, Leah

2014-09-21

Mortality from breast cancer stems from its tendency to invade into surrounding tissues and organs. Experiments have shown that this metastatic process is facilitated by macrophages in a short-ranged chemical signalling loop. Macrophages secrete epidermal growth factor, EGF, and respond to the colony stimulating factor 1, CSF-1. Tumor cells secrete CSF-1 and respond to EGF. In this way, the cells coordinate aggregation and cooperative migration. Here we investigate this process in a model for in vitro interactions using two distinct but related mathematical approaches. In the first, we analyze and simulate a set of partial differential equations to determine conditions for aggregation. In the second, we use a cell-based discrete 3D simulation to follow the fates and motion of individual cells during aggregation. Linear stability analysis of the PDE model reveals that decreasing the chemical secretion, chemotaxis coefficients or density of cells or increasing the chemical degradation in the model could eliminate the spontaneous aggregation of cells. Simulations with the discrete model show that the ratio between tumor cells and macrophages in aggregates increases when the EGF secretion parameter is increased. The results also show how CSF-1/CSF-1R autocrine signalling in tumor cells affects the ratio between the two cell types. Comparing the continuum results with simulations of a discrete cell-based model, we find good qualitative agreement. Copyright © 2014 Elsevier Ltd. All rights reserved.

Aerospace Applications Conference, Steamboat Springs, CO, Feb. 1-8, 1986, Digest

NASA Astrophysics Data System (ADS)

The present conference considers topics concerning the projected NASA Space Station's systems, digital signal and data processing applications, and space science and microwave applications. Attention is given to Space Station video and audio subsystems design, clock error, jitter, phase error and differential time-of-arrival in satellite communications, automation and robotics in space applications, target insertion into synthetic background scenes, and a novel scheme for the computation of the discrete Fourier transform on a systolic processor. Also discussed are a novel signal parameter measurement system employing digital signal processing, EEPROMS for spacecraft applications, a unique concurrent processor architecture for high speed simulation of dynamic systems, a dual polarization flat plate antenna, Fresnel diffraction, and ultralinear TWTs for high efficiency satellite communications.

Ramanujan sums for signal processing of low-frequency noise.

PubMed

Planat, Michel; Rosu, Haret; Perrine, Serge

2002-11-01

An aperiodic (low-frequency) spectrum may originate from the error term in the mean value of an arithmetical function such as Möbius function or Mangoldt function, which are coding sequences for prime numbers. In the discrete Fourier transform the analyzing wave is periodic and not well suited to represent the low-frequency regime. In place we introduce a different signal processing tool based on the Ramanujan sums c(q)(n), well adapted to the analysis of arithmetical sequences with many resonances p/q. The sums are quasiperiodic versus the time n and aperiodic versus the order q of the resonance. Different results arise from the use of this Ramanujan-Fourier transform in the context of arithmetical and experimental signals.

Ramanujan sums for signal processing of low-frequency noise

NASA Astrophysics Data System (ADS)

Planat, Michel; Rosu, Haret; Perrine, Serge

2002-11-01

An aperiodic (low-frequency) spectrum may originate from the error term in the mean value of an arithmetical function such as Möbius function or Mangoldt function, which are coding sequences for prime numbers. In the discrete Fourier transform the analyzing wave is periodic and not well suited to represent the low-frequency regime. In place we introduce a different signal processing tool based on the Ramanujan sums cq(n), well adapted to the analysis of arithmetical sequences with many resonances p/q. The sums are quasiperiodic versus the time n and aperiodic versus the order q of the resonance. Different results arise from the use of this Ramanujan-Fourier transform in the context of arithmetical and experimental signals.

SIG-VISA: Signal-based Vertically Integrated Seismic Monitoring

NASA Astrophysics Data System (ADS)

Moore, D.; Mayeda, K. M.; Myers, S. C.; Russell, S.

2013-12-01

Traditional seismic monitoring systems rely on discrete detections produced by station processing software; however, while such detections may constitute a useful summary of station activity, they discard large amounts of information present in the original recorded signal. We present SIG-VISA (Signal-based Vertically Integrated Seismic Analysis), a system for seismic monitoring through Bayesian inference on seismic signals. By directly modeling the recorded signal, our approach incorporates additional information unavailable to detection-based methods, enabling higher sensitivity and more accurate localization using techniques such as waveform matching. SIG-VISA's Bayesian forward model of seismic signal envelopes includes physically-derived models of travel times and source characteristics as well as Gaussian process (kriging) statistical models of signal properties that combine interpolation of historical data with extrapolation of learned physical trends. Applying Bayesian inference, we evaluate the model on earthquakes as well as the 2009 DPRK test event, demonstrating a waveform matching effect as part of the probabilistic inference, along with results on event localization and sensitivity. In particular, we demonstrate increased sensitivity from signal-based modeling, in which the SIGVISA signal model finds statistical evidence for arrivals even at stations for which the IMS station processing failed to register any detection.

A preferential design approach for energy-efficient and robust implantable neural signal processing hardware.

PubMed

Narasimhan, Seetharam; Chiel, Hillel J; Bhunia, Swarup

2009-01-01

For implantable neural interface applications, it is important to compress data and analyze spike patterns across multiple channels in real time. Such a computational task for online neural data processing requires an innovative circuit-architecture level design approach for low-power, robust and area-efficient hardware implementation. Conventional microprocessor or Digital Signal Processing (DSP) chips would dissipate too much power and are too large in size for an implantable system. In this paper, we propose a novel hardware design approach, referred to as "Preferential Design" that exploits the nature of the neural signal processing algorithm to achieve a low-voltage, robust and area-efficient implementation using nanoscale process technology. The basic idea is to isolate the critical components with respect to system performance and design them more conservatively compared to the noncritical ones. This allows aggressive voltage scaling for low power operation while ensuring robustness and area efficiency. We have applied the proposed approach to a neural signal processing algorithm using the Discrete Wavelet Transform (DWT) and observed significant improvement in power and robustness over conventional design.

Signaling added response-independent reinforcement to assess Pavlovian processes in resistance to change and relapse.

PubMed

Podlesnik, Christopher A; Fleet, James D

2014-09-01

Behavioral momentum theory asserts Pavlovian stimulus-reinforcer relations govern the persistence of operant behavior. Specifically, resistance to conditions of disruption (e.g., extinction, satiation) reflects the relation between discriminative stimuli and the prevailing reinforcement conditions. The present study assessed whether Pavlovian stimulus-reinforcer relations govern resistance to disruption in pigeons by arranging both response-dependent and -independent food reinforcers in two components of a multiple schedule. In one component, discrete-stimulus changes preceded response-independent reinforcers, paralleling methods that reduce Pavlovian conditioned responding to contextual stimuli. Compared to the control component with no added stimuli preceding response-independent reinforcement, response rates increased as discrete-stimulus duration increased (0, 5, 10, and 15 s) across conditions. Although resistance to extinction decreased as stimulus duration increased in the component with the added discrete stimulus, further tests revealed no effect of discrete stimuli, including other disrupters (presession food, intercomponent food, modified extinction) and reinstatement designed to control for generalization decrement. These findings call into question a straightforward conception that the stimulus-reinforcer relations governing resistance to disruption reflect the same processes as Pavlovian conditioning, as asserted by behavioral momentum theory. © Society for the Experimental Analysis of Behavior.

A method for compression of intra-cortically-recorded neural signals dedicated to implantable brain-machine interfaces.

PubMed

Shaeri, Mohammad Ali; Sodagar, Amir M

2015-05-01

This paper proposes an efficient data compression technique dedicated to implantable intra-cortical neural recording devices. The proposed technique benefits from processing neural signals in the Discrete Haar Wavelet Transform space, a new spike extraction approach, and a novel data framing scheme to telemeter the recorded neural information to the outside world. Based on the proposed technique, a 64-channel neural signal processor was designed and prototyped as a part of a wireless implantable extra-cellular neural recording microsystem. Designed in a 0.13- μ m standard CMOS process, the 64-channel neural signal processor reported in this paper occupies ∼ 0.206 mm(2) of silicon area, and consumes 94.18 μW when operating under a 1.2-V supply voltage at a master clock frequency of 1.28 MHz.

A 2D multi-term time and space fractional Bloch-Torrey model based on bilinear rectangular finite elements

NASA Astrophysics Data System (ADS)

Qin, Shanlin; Liu, Fawang; Turner, Ian W.

2018-03-01

The consideration of diffusion processes in magnetic resonance imaging (MRI) signal attenuation is classically described by the Bloch-Torrey equation. However, many recent works highlight the distinct deviation in MRI signal decay due to anomalous diffusion, which motivates the fractional order generalization of the Bloch-Torrey equation. In this work, we study the two-dimensional multi-term time and space fractional diffusion equation generalized from the time and space fractional Bloch-Torrey equation. By using the Galerkin finite element method with a structured mesh consisting of rectangular elements to discretize in space and the L1 approximation of the Caputo fractional derivative in time, a fully discrete numerical scheme is derived. A rigorous analysis of stability and error estimation is provided. Numerical experiments in the square and L-shaped domains are performed to give an insight into the efficiency and reliability of our method. Then the scheme is applied to solve the multi-term time and space fractional Bloch-Torrey equation, which shows that the extra time derivative terms impact the relaxation process.

Designing for Compressive Sensing: Compressive Art, Camouflage, Fonts, and Quick Response Codes

DTIC Science & Technology

2018-01-01

an example where the signal is non-sparse in the standard basis, but sparse in the discrete cosine basis . The top plot shows the signal from the...previous example, now used as sparse discrete cosine transform (DCT) coefficients . The next plot shows the non-sparse signal in the standard...Romberg JK, Tao T. Stable signal recovery from incomplete and inaccurate measurements. Commun Pure Appl Math . 2006;59(8):1207–1223. 3. Donoho DL

Modeling discrete and rhythmic movements through motor primitives: a review.

PubMed

Degallier, Sarah; Ijspeert, Auke

2010-10-01

Rhythmic and discrete movements are frequently considered separately in motor control, probably because different techniques are commonly used to study and model them. Yet the increasing interest in finding a comprehensive model for movement generation requires bridging the different perspectives arising from the study of those two types of movements. In this article, we consider discrete and rhythmic movements within the framework of motor primitives, i.e., of modular generation of movements. In this way we hope to gain an insight into the functional relationships between discrete and rhythmic movements and thus into a suitable representation for both of them. Within this framework we can define four possible categories of modeling for discrete and rhythmic movements depending on the required command signals and on the spinal processes involved in the generation of the movements. These categories are first discussed in terms of biological concepts such as force fields and central pattern generators and then illustrated by several mathematical models based on dynamical system theory. A discussion on the plausibility of theses models concludes the work.

A Parallel Framework with Block Matrices of a Discrete Fourier Transform for Vector-Valued Discrete-Time Signals.

PubMed

Soto-Quiros, Pablo

2015-01-01

This paper presents a parallel implementation of a kind of discrete Fourier transform (DFT): the vector-valued DFT. The vector-valued DFT is a novel tool to analyze the spectra of vector-valued discrete-time signals. This parallel implementation is developed in terms of a mathematical framework with a set of block matrix operations. These block matrix operations contribute to analysis, design, and implementation of parallel algorithms in multicore processors. In this work, an implementation and experimental investigation of the mathematical framework are performed using MATLAB with the Parallel Computing Toolbox. We found that there is advantage to use multicore processors and a parallel computing environment to minimize the high execution time. Additionally, speedup increases when the number of logical processors and length of the signal increase.

Border effect-based precise measurement of any frequency signal

NASA Astrophysics Data System (ADS)

Bai, Li-Na; Ye, Bo; Xuan, Mei-Na; Jin, Yu-Zhen; Zhou, Wei

2015-12-01

Limited detection resolution leads to fuzzy areas during the measurement, and the discrimination of the border of a fuzzy area helps to use the resolution stability. In this way, measurement precision is greatly improved, hence this phenomenon is named the border effect. The resolution fuzzy area and its application should be studied to realize high-resolution measurement. During the measurement of any frequency signal, the fuzzy areas of phase-coincidence detection are always discrete and irregular. In this paper the difficulty in capturing the border information of discrete fuzzy areas is overcome and extra-high resolution measurement is implemented. Measurement precision of any frequency-signal can easily reach better than 1 × 10-11/s in a wide range of frequencies, showing the great importance of the border effect. An in-depth study of this issue has great significance for frequency standard comparison, signal processing, telecommunication, and fundamental subjects. Project supported by the National Natural Science Foundation of China (Grant Nos. 10978017 and 61201288), the Natural Science Foundation of Research Plan Projects of Shaanxi Province, China (Grant No. 2014JM2-6128), and the Sino-Poland Science and Technology Cooperation Projects (Grant No. 36-33).

Experimental testing of the noise-canceling processor.

PubMed

Collins, Michael D; Baer, Ralph N; Simpson, Harry J

2011-09-01

Signal-processing techniques for localizing an acoustic source buried in noise are tested in a tank experiment. Noise is generated using a discrete source, a bubble generator, and a sprinkler. The experiment has essential elements of a realistic scenario in matched-field processing, including complex source and noise time series in a waveguide with water, sediment, and multipath propagation. The noise-canceling processor is found to outperform the Bartlett processor and provide the correct source range for signal-to-noise ratios below -10 dB. The multivalued Bartlett processor is found to outperform the Bartlett processor but not the noise-canceling processor. © 2011 Acoustical Society of America

Detection and Modeling of High-Dimensional Thresholds for Fault Detection and Diagnosis

NASA Technical Reports Server (NTRS)

He, Yuning

2015-01-01

Many Fault Detection and Diagnosis (FDD) systems use discrete models for detection and reasoning. To obtain categorical values like oil pressure too high, analog sensor values need to be discretized using a suitablethreshold. Time series of analog and discrete sensor readings are processed and discretized as they come in. This task isusually performed by the wrapper code'' of the FDD system, together with signal preprocessing and filtering. In practice,selecting the right threshold is very difficult, because it heavily influences the quality of diagnosis. If a threshold causesthe alarm trigger even in nominal situations, false alarms will be the consequence. On the other hand, if threshold settingdoes not trigger in case of an off-nominal condition, important alarms might be missed, potentially causing hazardoussituations. In this paper, we will in detail describe the underlying statistical modeling techniques and algorithm as well as the Bayesian method for selecting the most likely shape and its parameters. Our approach will be illustrated by several examples from the Aerospace domain.

Window and Overlap Processing Effects on Power Estimates from Spectra

NASA Astrophysics Data System (ADS)

Trethewey, M. W.

2000-03-01

Fast Fourier transform (FFT) spectral processing is based on the assumption of stationary ergodic data. In engineering practice, the assumption is often violated and non-stationary data processed. Data windows are commonly used to reduce leakage by decreasing the signal amplitudes near the boundaries of the discrete samples. With certain combinations of non-stationary signals and windows, the temporal weighting may attenuate important signal characteristics to adversely affect any subsequent processing. In other words, the window artificially reduces a significant section of the time signal. Consequently, spectra and overall power estimated from the affected samples are unreliable. FFT processing can be particularly problematic when the signal consists of randomly occurring transients superimposed on a more continuous signal. Overlap processing is commonly used in this situation to improve the estimates. However, the results again depend on the temporal character of the signal in relation to the window weighting. A worst-case scenario, a short-duration half sine pulse, is used to illustrate the relationship between overlap percentage and resulting power estimates. The power estimates are shown to depend on the temporal behaviour of the square of overlapped window segments. An analysis shows that power estimates may be obtained to within 0.27 dB for the following windows and overlap combinations: rectangular (0% overlap), Hanning (62.5% overlap), Hamming (60.35% overlap) and flat-top (82.25% overlap).

Signal Propagation in Proteins and Relation to Equilibrium Fluctuations

PubMed Central

Chennubhotla, Chakra; Bahar, Ivet

2007-01-01

Elastic network (EN) models have been widely used in recent years for describing protein dynamics, based on the premise that the motions naturally accessible to native structures are relevant to biological function. We posit that equilibrium motions also determine communication mechanisms inherent to the network architecture. To this end, we explore the stochastics of a discrete-time, discrete-state Markov process of information transfer across the network of residues. We measure the communication abilities of residue pairs in terms of hit and commute times, i.e., the number of steps it takes on an average to send and receive signals. Functionally active residues are found to possess enhanced communication propensities, evidenced by their short hit times. Furthermore, secondary structural elements emerge as efficient mediators of communication. The present findings provide us with insights on the topological basis of communication in proteins and design principles for efficient signal transduction. While hit/commute times are information-theoretic concepts, a central contribution of this work is to rigorously show that they have physical origins directly relevant to the equilibrium fluctuations of residues predicted by EN models. PMID:17892319

Encoder fault analysis system based on Moire fringe error signal

NASA Astrophysics Data System (ADS)

Gao, Xu; Chen, Wei; Wan, Qiu-hua; Lu, Xin-ran; Xie, Chun-yu

2018-02-01

Aiming at the problem of any fault and wrong code in the practical application of photoelectric shaft encoder, a fast and accurate encoder fault analysis system is researched from the aspect of Moire fringe photoelectric signal processing. DSP28335 is selected as the core processor and high speed serial A/D converter acquisition card is used. And temperature measuring circuit using AD7420 is designed. Discrete data of Moire fringe error signal is collected at different temperatures and it is sent to the host computer through wireless transmission. The error signal quality index and fault type is displayed on the host computer based on the error signal identification method. The error signal quality can be used to diagnosis the state of error code through the human-machine interface.

Hands-free device control using sound picked up in the ear canal

NASA Astrophysics Data System (ADS)

Chhatpar, Siddharth R.; Ngia, Lester; Vlach, Chris; Lin, Dong; Birkhimer, Craig; Juneja, Amit; Pruthi, Tarun; Hoffman, Orin; Lewis, Tristan

2008-04-01

Hands-free control of unmanned ground vehicles is essential for soldiers, bomb disposal squads, and first responders. Having their hands free for other equipment and tasks allows them to be safer and more mobile. Currently, the most successful hands-free control devices are speech-command based. However, these devices use external microphones, and in field environments, e.g., war zones and fire sites, their performance suffers because of loud ambient noise: typically above 90dBA. This paper describes the development of technology using the ear as an output source that can provide excellent command recognition accuracy even in noisy environments. Instead of picking up speech radiating from the mouth, this technology detects speech transmitted internally through the ear canal. Discreet tongue movements also create air pressure changes within the ear canal, and can be used for stealth control. A patented earpiece was developed with a microphone pointed into the ear canal that captures these signals generated by tongue movements and speech. The signals are transmitted from the earpiece to an Ultra-Mobile Personal Computer (UMPC) through a wired connection. The UMPC processes the signals and utilizes them for device control. The processing can include command recognition, ambient noise cancellation, acoustic echo cancellation, and speech equalization. Successful control of an iRobot PackBot has been demonstrated with both speech (13 discrete commands) and tongue (5 discrete commands) signals. In preliminary tests, command recognition accuracy was 95% with speech control and 85% with tongue control.

A Comparative Analysis for Selection of Appropriate Mother Wavelet for Detection of Stationary Disturbances

NASA Astrophysics Data System (ADS)

Kamble, Saurabh Prakash; Thawkar, Shashank; Gaikwad, Vinayak G.; Kothari, D. P.

2017-12-01

Detection of disturbances is the first step of mitigation. Power electronics plays a crucial role in modern power system which makes system operation efficient but it also bring stationary disturbances in the power system and added impurities to the supply. It happens because of the non-linear loads used in modern day power system which inject disturbances like harmonic disturbances, flickers, sag etc. in power grid. These impurities can damage equipments so it is necessary to mitigate these impurities present in the supply very quickly. So, digital signal processing techniques are incorporated for detection purpose. Signal processing techniques like fast Fourier transform, short-time Fourier transform, Wavelet transform etc. are widely used for the detection of disturbances. Among all, wavelet transform is widely used because of its better detection capabilities. But, which mother wavelet has to use for detection is still a mystery. Depending upon the periodicity, the disturbances are classified as stationary and non-stationary disturbances. This paper presents the importance of selection of mother wavelet for analyzing stationary disturbances using discrete wavelet transform. Signals with stationary disturbances of various frequencies are generated using MATLAB. The analysis of these signals is done using various mother wavelets like Daubechies and bi-orthogonal wavelets and the measured root mean square value of stationary disturbance is obtained. The measured value obtained by discrete wavelet transform is compared with the exact RMS value of the frequency component and the percentage differences are presented which helps to select optimum mother wavelet.

Analysis of embolic signals with directional dual tree rational dilation wavelet transform.

PubMed

Serbes, Gorkem; Aydin, Nizamettin

2016-08-01

The dyadic discrete wavelet transform (dyadic-DWT), which is based on fixed integer sampling factor, has been used before for processing piecewise smooth biomedical signals. However, the dyadic-DWT has poor frequency resolution due to the low-oscillatory nature of its wavelet bases and therefore, it is less effective in processing embolic signals (ESs). To process ESs more effectively, a wavelet transform having better frequency resolution than the dyadic-DWT is needed. Therefore, in this study two ESs, containing micro-emboli and artifact waveforms, are analyzed with the Directional Dual Tree Rational-Dilation Wavelet Transform (DDT-RADWT). The DDT-RADWT, which can be directly applied to quadrature signals, is based on rational dilation factors and has adjustable frequency resolution. The analyses are done for both low and high Q-factors. It is proved that, when high Q-factor filters are employed in the DDT-RADWT, clearer representations of ESs can be attained in decomposed sub-bands and artifacts can be successfully separated.

SIG. Signal Processing, Analysis, & Display

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

Hernandez, J.; Lager, D.; Azevedo, S.

1992-01-22

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. Two user interfaces are provided in SIG; a menu mode for the unfamiliar user and a command mode for more experienced users. In both modes errors are detected as early as possible and are indicated by friendly, meaningful messages. An on-line HELP package is also included. A variety of operations can be performed on time and frequency-domain signals includingmore » operations on the samples of a signal, operations on the entire signal, and operations on two or more signals. Signal processing operations that can be performed are digital filtering (median, Bessel, Butterworth, and Chebychev), ensemble average, resample, auto and cross spectral density, transfer function and impulse response, trend removal, convolution, Fourier transform and inverse window functions (Hamming, Kaiser-Bessel), simulation (ramp, sine, pulsetrain, random), and read/write signals. User definable signal processing algorithms are also featured. SIG has many options including multiple commands per line, command files with arguments, commenting lines, defining commands, and automatic execution for each item in a `repeat` sequence. Graphical operations on signals and spectra include: x-y plots of time signals; real, imaginary, magnitude, and phase plots of spectra; scaling of spectra for continuous or discrete domain; cursor zoom; families of curves; and multiple viewports.« less

SIG. Signal Processing, Analysis, & Display

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

Hernandez, J.; Lager, D.; Azevedo, S.

1992-01-22

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. Two user interfaces are provided in SIG - a menu mode for the unfamiliar user and a command mode for more experienced users. In both modes errors are detected as early as possible and are indicated by friendly, meaningful messages. An on-line HELP package is also included. A variety of operations can be performed on time and frequency-domain signals includingmore » operations on the samples of a signal, operations on the entire signal, and operations on two or more signals. Signal processing operations that can be performed are digital filtering (median, Bessel, Butterworth, and Chebychev), ensemble average, resample, auto and cross spectral density, transfer function and impulse response, trend removal, convolution, Fourier transform and inverse window functions (Hamming, Kaiser-Bessel), simulation (ramp, sine, pulsetrain, random), and read/write signals. User definable signal processing algorithms are also featured. SIG has many options including multiple commands per line, command files with arguments, commenting lines, defining commands, and automatic execution for each item in a repeat sequence. Graphical operations on signals and spectra include: x-y plots of time signals; real, imaginary, magnitude, and phase plots of spectra; scaling of spectra for continuous or discrete domain; cursor zoom; families of curves; and multiple viewports.« less

High resolution signal-processing method for extrinsic Fabry-Perot interferometric sensors

NASA Astrophysics Data System (ADS)

Xie, Jiehui; Wang, Fuyin; Pan, Yao; Wang, Junjie; Hu, Zhengliang; Hu, Yongming

2015-03-01

In this paper, a signal-processing method for optical fiber extrinsic Fabry-Perot interferometric sensors is presented. It achieves both high resolution and absolute measurement of the dynamic change of cavity length with low sampling points in wavelength domain. In order to improve the demodulation accuracy, the reflected interference spectrum is cleared by Discrete Wavelet Transform and adjusted by the Hilbert transform. Then the cavity length is interrogated by the cross correlation algorithm. The continuous tests show the resolution of cavity length is only 36.7 pm. Moreover, the corresponding resolution of cavity length is only 1 pm on the low frequency range below 420 Hz, and the corresponding power spectrum shows the possibility of detecting the ultra-low frequency signals based on spectra detection.

Discrete Ramanujan transform for distinguishing the protein coding regions from other regions.

PubMed

Hua, Wei; Wang, Jiasong; Zhao, Jian

2014-01-01

Based on the study of Ramanujan sum and Ramanujan coefficient, this paper suggests the concepts of discrete Ramanujan transform and spectrum. Using Voss numerical representation, one maps a symbolic DNA strand as a numerical DNA sequence, and deduces the discrete Ramanujan spectrum of the numerical DNA sequence. It is well known that of discrete Fourier power spectrum of protein coding sequence has an important feature of 3-base periodicity, which is widely used for DNA sequence analysis by the technique of discrete Fourier transform. It is performed by testing the signal-to-noise ratio at frequency N/3 as a criterion for the analysis, where N is the length of the sequence. The results presented in this paper show that the property of 3-base periodicity can be only identified as a prominent spike of the discrete Ramanujan spectrum at period 3 for the protein coding regions. The signal-to-noise ratio for discrete Ramanujan spectrum is defined for numerical measurement. Therefore, the discrete Ramanujan spectrum and the signal-to-noise ratio of a DNA sequence can be used for distinguishing the protein coding regions from the noncoding regions. All the exon and intron sequences in whole chromosomes 1, 2, 3 and 4 of Caenorhabditis elegans have been tested and the histograms and tables from the computational results illustrate the reliability of our method. In addition, we have analyzed theoretically and gotten the conclusion that the algorithm for calculating discrete Ramanujan spectrum owns the lower computational complexity and higher computational accuracy. The computational experiments show that the technique by using discrete Ramanujan spectrum for classifying different DNA sequences is a fast and effective method. Copyright © 2014 Elsevier Ltd. All rights reserved.

A Discussion of the Discrete Fourier Transform Execution on a Typical Desktop PC

NASA Technical Reports Server (NTRS)

White, Michael J.

2006-01-01

This paper will discuss and compare the execution times of three examples of the Discrete Fourier Transform (DFT). The first two examples will demonstrate the direct implementation of the algorithm. In the first example, the Fourier coefficients are generated at the execution of the DFT. In the second example, the coefficients are generated prior to execution and the DFT coefficients are indexed at execution. The last example will demonstrate the Cooley- Tukey algorithm, better known as the Fast Fourier Transform. All examples were written in C executed on a PC using a Pentium 4 running at 1.7 Ghz. As a function of N, the total complex data size, the direct implementation DFT executes, as expected at order of N2 and the FFT executes at order of N log2 N. At N=16K, there is an increase in processing time beyond what is expected. This is not caused by implementation but is a consequence of the effect that machine architecture and memory hierarchy has on implementation. This paper will include a brief overview of digital signal processing, along with a discussion of contemporary work with discrete Fourier processing.

Signal Processing, Analysis, & Display

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

Lager, Darrell; Azevado, Stephen

1986-06-01

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. Two user interfaces are provided in SIG - a menu mode for the unfamiliar user and a command mode for more experienced users. In both modes errors are detected as early as possible and are indicated by friendly, meaningful messages. An on-line HELP package is also included. A variety of operations can be performed on time- and frequency-domain signalsmore » including operations on the samples of a signal, operations on the entire signal, and operations on two or more signals. Signal processing operations that can be performed are digital filtering (median, Bessel, Butterworth, and Chebychev), ensemble average, resample, auto and cross spectral density, transfer function and impulse response, trend removal, convolution, Fourier transform and inverse window functions (Hamming, Kaiser-Bessel), simulation (ramp, sine, pulsetrain, random), and read/write signals. User definable signal processing algorithms are also featured. SIG has many options including multiple commands per line, command files with arguments,commenting lines, defining commands, and automatic execution for each item in a repeat sequence. Graphical operations on signals and spectra include: x-y plots of time signals; real, imaginary, magnitude, and phase plots of spectra; scaling of spectra for continuous or discrete domain; cursor zoom; families of curves; and multiple viewports.« less

SIG. Signal Processing, Analysis, & Display

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

Hernandez, J.; Lager, D.; Azevedo, S.

1992-01-22

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. Two user interfaces are provided in SIG - a menu mode for the unfamiliar user and a command mode for more experienced users. In both modes errors are detected as early as possible and are indicated by friendly, meaningful messages. An on-line HELP package is also included. A variety of operations can be performed on time- and frequency-domain signalsmore » including operations on the samples of a signal, operations on the entire signal, and operations on two or more signals. Signal processing operations that can be performed are digital filtering (median, Bessel, Butterworth, and Chebychev), ensemble average, resample, auto and cross spectral density, transfer function and impulse response, trend removal, convolution, Fourier transform and inverse window functions (Hamming, Kaiser-Bessel), simulation (ramp, sine, pulsetrain, random), and read/write signals. User definable signal processing algorithms are also featured. SIG has many options including multiple commands per line, command files with arguments,commenting lines, defining commands, and automatic execution for each item in a repeat sequence. Graphical operations on signals and spectra include: x-y plots of time signals; real, imaginary, magnitude, and phase plots of spectra; scaling of spectra for continuous or discrete domain; cursor zoom; families of curves; and multiple viewports.« less

Adaptive Microwave Staring Correlated Imaging for Targets Appearing in Discrete Clusters.

PubMed

Tian, Chao; Jiang, Zheng; Chen, Weidong; Wang, Dongjin

2017-10-21

Microwave staring correlated imaging (MSCI) can achieve ultra-high resolution in real aperture staring radar imaging using the correlated imaging process (CIP) under all-weather and all-day circumstances. The CIP must combine the received echo signal with the temporal-spatial stochastic radiation field. However, a precondition of the CIP is that the continuous imaging region must be discretized to a fine grid, and the measurement matrix should be accurately computed, which makes the imaging process highly complex when the MSCI system observes a wide area. This paper proposes an adaptive imaging approach for the targets in discrete clusters to reduce the complexity of the CIP. The approach is divided into two main stages. First, as discrete clustered targets are distributed in different range strips in the imaging region, the transmitters of the MSCI emit narrow-pulse waveforms to separate the echoes of the targets in different strips in the time domain; using spectral entropy, a modified method robust against noise is put forward to detect the echoes of the discrete clustered targets, based on which the strips with targets can be adaptively located. Second, in a strip with targets, the matched filter reconstruction algorithm is used to locate the regions with targets, and only the regions of interest are discretized to a fine grid; sparse recovery is used, and the band exclusion is used to maintain the non-correlation of the dictionary. Simulation results are presented to demonstrate that the proposed approach can accurately and adaptively locate the regions with targets and obtain high-quality reconstructed images.

Discrete photon statistics from continuous microwave measurements

NASA Astrophysics Data System (ADS)

Virally, Stéphane; Simoneau, Jean Olivier; Lupien, Christian; Reulet, Bertrand

2016-04-01

Photocount statistics are an important tool for the characterization of electromagnetic fields, especially for fields with an irrelevant phase. In the microwave domain, continuous rather than discrete measurements are the norm. Using a different approach, we recover discrete photon statistics from the cumulants of a continuous distribution of field quadrature measurements. The use of cumulants allows the separation between the signal of interest and experimental noise. Using a parametric amplifier as the first stage of the amplification chain, we extract useful data from up to the sixth cumulant of the continuous distribution of a coherent field, hence recovering up to the third moment of the discrete statistics associated with a signal with much less than one average photon.

Multipath interference test method using synthesized chirped signal from directly modulated DFB-LD with digital-signal-processing technique.

PubMed

Aida, Kazuo; Sugie, Toshihiko

2011-12-12

We propose a method of testing transmission fiber lines and distributed amplifiers. Multipath interference (MPI) is detected as a beat spectrum between a multipath signal and a direct signal using a synthesized chirped test signal with lightwave frequencies of f(1) and f(2) periodically emitted from a distributed feedback laser diode (DFB-LD). This chirped test pulse is generated using a directly modulated DFB-LD with a drive signal calculated using a digital signal processing technique (DSP). A receiver consisting of a photodiode and an electrical spectrum analyzer (ESA) detects a baseband power spectrum peak appearing at the frequency of the test signal frequency deviation (f(1)-f(2)) as a beat spectrum of self-heterodyne detection. Multipath interference is converted from the spectrum peak power. This method improved the minimum detectable MPI to as low as -78 dB. We discuss the detailed design and performance of the proposed test method, including a DFB-LD drive signal calculation algorithm with DSP for synthesis of the chirped test signal and experiments on single-mode fibers with discrete reflections. © 2011 Optical Society of America

Extracellular Electrophysiological Measurements of Cooperative Signals in Astrocytes Populations

PubMed Central

Mestre, Ana L. G.; Inácio, Pedro M. C.; Elamine, Youssef; Asgarifar, Sanaz; Lourenço, Ana S.; Cristiano, Maria L. S.; Aguiar, Paulo; Medeiros, Maria C. R.; Araújo, Inês M.; Ventura, João; Gomes, Henrique L.

2017-01-01

Astrocytes are neuroglial cells that exhibit functional electrical properties sensitive to neuronal activity and capable of modulating neurotransmission. Thus, electrophysiological recordings of astroglial activity are very attractive to study the dynamics of glial signaling. This contribution reports on the use of ultra-sensitive planar electrodes combined with low noise and low frequency amplifiers that enable the detection of extracellular signals produced by primary cultures of astrocytes isolated from mouse cerebral cortex. Recorded activity is characterized by spontaneous bursts comprised of discrete signals with pronounced changes on the signal rate and amplitude. Weak and sporadic signals become synchronized and evolve with time to higher amplitude signals with a quasi-periodic behavior, revealing a cooperative signaling process. The methodology presented herewith enables the study of ionic fluctuations of population of cells, complementing the single cells observation by calcium imaging as well as by patch-clamp techniques. PMID:29109679

Extracellular Electrophysiological Measurements of Cooperative Signals in Astrocytes Populations.

PubMed

Mestre, Ana L G; Inácio, Pedro M C; Elamine, Youssef; Asgarifar, Sanaz; Lourenço, Ana S; Cristiano, Maria L S; Aguiar, Paulo; Medeiros, Maria C R; Araújo, Inês M; Ventura, João; Gomes, Henrique L

2017-01-01

Astrocytes are neuroglial cells that exhibit functional electrical properties sensitive to neuronal activity and capable of modulating neurotransmission. Thus, electrophysiological recordings of astroglial activity are very attractive to study the dynamics of glial signaling. This contribution reports on the use of ultra-sensitive planar electrodes combined with low noise and low frequency amplifiers that enable the detection of extracellular signals produced by primary cultures of astrocytes isolated from mouse cerebral cortex. Recorded activity is characterized by spontaneous bursts comprised of discrete signals with pronounced changes on the signal rate and amplitude. Weak and sporadic signals become synchronized and evolve with time to higher amplitude signals with a quasi-periodic behavior, revealing a cooperative signaling process. The methodology presented herewith enables the study of ionic fluctuations of population of cells, complementing the single cells observation by calcium imaging as well as by patch-clamp techniques.

Engineering information on an Analog Signal to Discrete Time Interval Converter (ASDT-IC)

NASA Technical Reports Server (NTRS)

Schwarz, F. C.

1974-01-01

An electronic control system for nondissipative dc power converters is presented which improves (1) the routinely attainable static output voltage accuracy to the order of + or - 1% for ambient temperatures from -55 to 100 C and (2) the dynamic stability by utilizing approximately one tenth of the feedback gain needed otherwise. Performance is due to a functional philosophy of deterministic pulse modulation based on pulse area control and to an autocompensated signal processing principle. The system can be implemented with commercially available unselected components.

High-speed event detector for embedded nanopore bio-systems.

PubMed

Huang, Yiyun; Magierowski, Sebastian; Ghafar-Zadeh, Ebrahim; Wang, Chengjie

2015-08-01

Biological measurements of microscopic phenomena often deal with discrete-event signals. The ability to automatically carry out such measurements at high-speed in a miniature embedded system is desirable but compromised by high-frequency noise along with practical constraints on filter quality and sampler resolution. This paper presents a real-time event-detection method in the context of nanopore sensing that helps to mitigate these drawbacks and allows accurate signal processing in an embedded system. Simulations show at least a 10× improvement over existing on-line detection methods.

A study of MRI gradient echo signals from discrete magnetic particles with considerations of several parameters in simulations.

PubMed

Kokeny, Paul; Cheng, Yu-Chung N; Xie, He

2018-05-01

Modeling MRI signal behaviors in the presence of discrete magnetic particles is important, as magnetic particles appear in nanoparticle labeled cells, contrast agents, and other biological forms of iron. Currently, many models that take into account the discrete particle nature in a system have been used to predict magnitude signal decays in the form of R2* or R2' from one single voxel. Little work has been done for predicting phase signals. In addition, most calculations of phase signals rely on the assumption that a system containing discrete particles behaves as a continuous medium. In this work, numerical simulations are used to investigate MRI magnitude and phase signals from discrete particles, without diffusion effects. Factors such as particle size, number density, susceptibility, volume fraction, particle arrangements for their randomness, and field of view have been considered in simulations. The results are compared to either a ground truth model, theoretical work based on continuous mediums, or previous literature. Suitable parameters used to model particles in several voxels that lead to acceptable magnetic field distributions around particle surfaces and accurate MR signals are identified. The phase values as a function of echo time from a central voxel filled by particles can be significantly different from those of a continuous cubic medium. However, a completely random distribution of particles can lead to an R2' value which agrees with the prediction from the static dephasing theory. A sphere with a radius of at least 4 grid points used in simulations is found to be acceptable to generate MR signals equivalent from a larger sphere. Increasing number of particles with a fixed volume fraction in simulations reduces the resulting variance in the phase behavior, and converges to almost the same phase value for different particle numbers at each echo time. The variance of phase values is also reduced when increasing the number of particles in a fixed voxel. These results indicate that MRI signals from voxels containing discrete particles, even with a sufficient number of particles per voxel, cannot be properly modeled by a continuous medium with an equivalent susceptibility value in the voxel. Copyright © 2017 Elsevier Inc. All rights reserved.

Frequency division multiplexed multi-color fluorescence microscope system

NASA Astrophysics Data System (ADS)

Le, Vu Nam; Yang, Huai Dong; Zhang, Si Chun; Zhang, Xin Rong; Jin, Guo Fan

2017-10-01

Grayscale camera can only obtain gray scale image of object, while the multicolor imaging technology can obtain the color information to distinguish the sample structures which have the same shapes but in different colors. In fluorescence microscopy, the current method of multicolor imaging are flawed. Problem of these method is affecting the efficiency of fluorescence imaging, reducing the sampling rate of CCD etc. In this paper, we propose a novel multiple color fluorescence microscopy imaging method which based on the Frequency division multiplexing (FDM) technology, by modulating the excitation lights and demodulating the fluorescence signal in frequency domain. This method uses periodic functions with different frequency to modulate amplitude of each excitation lights, and then combine these beams for illumination in a fluorescence microscopy imaging system. The imaging system will detect a multicolor fluorescence image by a grayscale camera. During the data processing, the signal obtained by each pixel of the camera will be processed with discrete Fourier transform, decomposed by color in the frequency domain and then used inverse discrete Fourier transform. After using this process for signals from all of the pixels, monochrome images of each color on the image plane can be obtained and multicolor image is also acquired. Based on this method, this paper has constructed and set up a two-color fluorescence microscope system with two excitation wavelengths of 488 nm and 639 nm. By using this system to observe the linearly movement of two kinds of fluorescent microspheres, after the data processing, we obtain a two-color fluorescence dynamic video which is consistent with the original image. This experiment shows that the dynamic phenomenon of multicolor fluorescent biological samples can be generally observed by this method. Compared with the current methods, this method can obtain the image signals of each color at the same time, and the color video's frame rate is consistent with the frame rate of the camera. The optical system is simpler and does not need extra color separation element. In addition, this method has a good filtering effect on the ambient light or other light signals which are not affected by the modulation process.

Distributed fault detection over sensor networks with Markovian switching topologies

NASA Astrophysics Data System (ADS)

Ge, Xiaohua; Han, Qing-Long

2014-05-01

This paper deals with the distributed fault detection for discrete-time Markov jump linear systems over sensor networks with Markovian switching topologies. The sensors are scatteredly deployed in the sensor field and the fault detectors are physically distributed via a communication network. The system dynamics changes and sensing topology variations are modeled by a discrete-time Markov chain with incomplete mode transition probabilities. Each of these sensor nodes firstly collects measurement outputs from its all underlying neighboring nodes, processes these data in accordance with the Markovian switching topologies, and then transmits the processed data to the remote fault detector node. Network-induced delays and accumulated data packet dropouts are incorporated in the data transmission between the sensor nodes and the distributed fault detector nodes through the communication network. To generate localized residual signals, mode-independent distributed fault detection filters are proposed. By means of the stochastic Lyapunov functional approach, the residual system performance analysis is carried out such that the overall residual system is stochastically stable and the error between each residual signal and the fault signal is made as small as possible. Furthermore, a sufficient condition on the existence of the mode-independent distributed fault detection filters is derived in the simultaneous presence of incomplete mode transition probabilities, Markovian switching topologies, network-induced delays, and accumulated data packed dropouts. Finally, a stirred-tank reactor system is given to show the effectiveness of the developed theoretical results.

Vestibular blueprint in early vertebrates.

PubMed

Straka, Hans; Baker, Robert

2013-11-19

Central vestibular neurons form identifiable subgroups within the boundaries of classically outlined octavolateral nuclei in primitive vertebrates that are distinct from those processing lateral line, electrosensory, and auditory signals. Each vestibular subgroup exhibits a particular morpho-physiological property that receives origin-specific sensory inputs from semicircular canal and otolith organs. Behaviorally characterized phenotypes send discrete axonal projections to extraocular, spinal, and cerebellar targets including other ipsi- and contralateral vestibular nuclei. The anatomical locations of vestibuloocular and vestibulospinal neurons correlate with genetically defined hindbrain compartments that are well conserved throughout vertebrate evolution though some variability exists in fossil and extant vertebrate species. The different vestibular subgroups exhibit a robust sensorimotor signal processing complemented with a high degree of vestibular and visual adaptive plasticity.

Interpretation of the Lempel-Ziv complexity measure in the context of biomedical signal analysis.

PubMed

Aboy, Mateo; Hornero, Roberto; Abásolo, Daniel; Alvarez, Daniel

2006-11-01

Lempel-Ziv complexity (LZ) and derived LZ algorithms have been extensively used to solve information theoretic problems such as coding and lossless data compression. In recent years, LZ has been widely used in biomedical applications to estimate the complexity of discrete-time signals. Despite its popularity as a complexity measure for biosignal analysis, the question of LZ interpretability and its relationship to other signal parameters and to other metrics has not been previously addressed. We have carried out an investigation aimed at gaining a better understanding of the LZ complexity itself, especially regarding its interpretability as a biomedical signal analysis technique. Our results indicate that LZ is particularly useful as a scalar metric to estimate the bandwidth of random processes and the harmonic variability in quasi-periodic signals.

Discrete mathematics for spatial data classification and understanding

NASA Astrophysics Data System (ADS)

Mussio, Luigi; Nocera, Rossella; Poli, Daniela

1998-12-01

Data processing, in the field of information technology, requires new tools, involving discrete mathematics, like data compression, signal enhancement, data classification and understanding, hypertexts and multimedia (considering educational aspects too), because the mass of data implies automatic data management and doesn't permit any a priori knowledge. The methodologies and procedures used in this class of problems concern different kinds of segmentation techniques and relational strategies, like clustering, parsing, vectorization, formalization, fitting and matching. On the other hand, the complexity of this approach imposes to perform optimal sampling and outlier detection just at the beginning, in order to define the set of data to be processed: rough data supply very poor information. For these reasons, no hypotheses about the distribution behavior of the data can be generally done and a judgment should be acquired by distribution-free inference only.

Input-output identification of controlled discrete manufacturing systems

NASA Astrophysics Data System (ADS)

Estrada-Vargas, Ana Paula; López-Mellado, Ernesto; Lesage, Jean-Jacques

2014-03-01

The automated construction of discrete event models from observations of external system's behaviour is addressed. This problem, often referred to as system identification, allows obtaining models of ill-known (or even unknown) systems. In this article, an identification method for discrete event systems (DESs) controlled by a programmable logic controller is presented. The method allows processing a large quantity of observed long sequences of input/output signals generated by the controller and yields an interpreted Petri net model describing the closed-loop behaviour of the automated DESs. The proposed technique allows the identification of actual complex systems because it is sufficiently efficient and well adapted to cope with both the technological characteristics of industrial controllers and data collection requirements. Based on polynomial-time algorithms, the method is implemented as an efficient software tool which constructs and draws the model automatically; an overview of this tool is given through a case study dealing with an automated manufacturing system.

A discrete structure of the brain waves.

NASA Astrophysics Data System (ADS)

Dabaghian, Yuri; Perotti, Luca; oscillons in biological rhythms Collaboration; physics of biological rhythms Team

A physiological interpretation of the biological rhythms, e.g., of the local field potentials (LFP) depends on the mathematical approaches used for the analysis. Most existing mathematical methods are based on decomposing the signal into a set of ``primitives,'' e.g., sinusoidal harmonics, and correlating them with different cognitive and behavioral phenomena. A common feature of all these methods is that the decomposition semantics is presumed from the onset, and the goal of the subsequent analysis reduces merely to identifying the combination that best reproduces the original signal. We propose a fundamentally new method in which the decomposition components are discovered empirically, and demonstrate that it is more flexible and more sensitive to the signal's structure than the standard Fourier method. Applying this method to the rodent LFP signals reveals a fundamentally new structure of these ``brain waves.'' In particular, our results suggest that the LFP oscillations consist of a superposition of a small, discrete set of frequency modulated oscillatory processes, which we call ``oscillons''. Since these structures are discovered empirically, we hypothesize that they may capture the signal's actual physical structure, i.e., the pattern of synchronous activity in neuronal ensembles. Proving this hypothesis will help to advance our principal understanding of the neuronal synchronization mechanisms and reveal new structure within the LFPs and other biological oscillations. NSF 1422438 Grant, Houston Bioinformatics Endowment Fund.

Discrete Logic Modelling Optimization to Contextualize Prior Knowledge Networks Using PRUNET

PubMed Central

Androsova, Ganna; del Sol, Antonio

2015-01-01

High-throughput technologies have led to the generation of an increasing amount of data in different areas of biology. Datasets capturing the cell’s response to its intra- and extra-cellular microenvironment allows such data to be incorporated as signed and directed graphs or influence networks. These prior knowledge networks (PKNs) represent our current knowledge of the causality of cellular signal transduction. New signalling data is often examined and interpreted in conjunction with PKNs. However, different biological contexts, such as cell type or disease states, may have distinct variants of signalling pathways, resulting in the misinterpretation of new data. The identification of inconsistencies between measured data and signalling topologies, as well as the training of PKNs using context specific datasets (PKN contextualization), are necessary conditions to construct reliable, predictive models, which are current challenges in the systems biology of cell signalling. Here we present PRUNET, a user-friendly software tool designed to address the contextualization of a PKNs to specific experimental conditions. As the input, the algorithm takes a PKN and the expression profile of two given stable steady states or cellular phenotypes. The PKN is iteratively pruned using an evolutionary algorithm to perform an optimization process. This optimization rests in a match between predicted attractors in a discrete logic model (Boolean) and a Booleanized representation of the phenotypes, within a population of alternative subnetworks that evolves iteratively. We validated the algorithm applying PRUNET to four biological examples and using the resulting contextualized networks to predict missing expression values and to simulate well-characterized perturbations. PRUNET constitutes a tool for the automatic curation of a PKN to make it suitable for describing biological processes under particular experimental conditions. The general applicability of the implemented algorithm makes PRUNET suitable for a variety of biological processes, for instance cellular reprogramming or transitions between healthy and disease states. PMID:26058016

Performance on perceptual word identification is mediated by discrete states.

PubMed

Swagman, April R; Province, Jordan M; Rouder, Jeffrey N

2015-02-01

We contrast predictions from discrete-state models of all-or-none information loss with signal-detection models of graded strength for the identification of briefly flashed English words. Previous assessments have focused on whether ROC curves are straight or not, which is a test of a discrete-state model where detection leads to the highest confidence response with certainty. We along with many others argue this certainty assumption is too constraining, and, consequently, the straight-line ROC test is too stringent. Instead, we assess a core property of discrete-state models, conditional independence, where the pattern of responses depends only on which state is entered. The conditional independence property implies that confidence ratings are a mixture of detect and guess state responses, and that stimulus strength factors, the duration of the flashed word in this report, affect only the probability of entering a state and not responses conditional on a state. To assess this mixture property, 50 participants saw words presented briefly on a computer screen at three variable flash durations followed by either a two-alternative confidence ratings task or a yes-no confidence ratings task. Comparable discrete-state and signal-detection models were fit to the data for each participant and task. The discrete-state models outperformed the signal detection models for 90 % of participants in the two-alternative task and for 68 % of participants in the yes-no task. We conclude discrete-state models are viable for predicting performance across stimulus conditions in a perceptual word identification task.

Cargo-mediated regulation of a rapid Rab4-dependent recycling pathway.

PubMed

Yudowski, Guillermo A; Puthenveedu, Manojkumar A; Henry, Anastasia G; von Zastrow, Mark

2009-06-01

Membrane trafficking is well known to regulate receptor-mediated signaling processes, but less is known about whether signaling receptors conversely regulate the membrane trafficking machinery. We investigated this question by focusing on the beta-2 adrenergic receptor (B2AR), a G protein-coupled receptor whose cellular signaling activity is controlled by ligand-induced endocytosis followed by recycling. We used total internal reflection fluorescence microscopy (TIR-FM) and tagging with a pH-sensitive GFP variant to image discrete membrane trafficking events mediating B2AR endo- and exocytosis. Within several minutes after initiating rapid endocytosis of B2ARs by the adrenergic agonist isoproterenol, we observed bright "puffs" of locally increased surface fluorescence intensity representing discrete Rab4-dependent recycling events. These events reached a constant frequency in the continuous presence of isoproterenol, and agonist removal produced a rapid (observed within 1 min) and pronounced (approximately twofold) increase in recycling event frequency. This regulation required receptor signaling via the cAMP-dependent protein kinase (PKA) and a specific PKA consensus site located in the carboxyl-terminal cytoplasmic tail of the B2AR itself. B2AR-mediated regulation was not restricted to this membrane cargo, however, as transferrin receptors packaged in the same population of recycling vesicles were similarly affected. In contrast, net recycling measured over a longer time interval (10 to 30 min) was not detectably regulated by B2AR signaling. These results identify rapid regulation of a specific recycling pathway by a signaling receptor cargo.

Reconstruction of finite-valued sparse signals

NASA Astrophysics Data System (ADS)

Keiper, Sandra; Kutyniok, Gitta; Lee, Dae Gwan; Pfander, Götz

2017-08-01

The need of reconstructing discrete-valued sparse signals from few measurements, that is solving an undetermined system of linear equations, appears frequently in science and engineering. Those signals appear, for example, in error correcting codes as well as massive Multiple-Input Multiple-Output (MIMO) channel and wideband spectrum sensing. A particular example is given by wireless communications, where the transmitted signals are sequences of bits, i.e., with entries in f0; 1g. Whereas classical compressed sensing algorithms do not incorporate the additional knowledge of the discrete nature of the signal, classical lattice decoding approaches do not utilize sparsity constraints. In this talk, we present an approach that incorporates a discrete values prior into basis pursuit. In particular, we address finite-valued sparse signals, i.e., sparse signals with entries in a finite alphabet. We will introduce an equivalent null space characterization and show that phase transition takes place earlier than when using the classical basis pursuit approach. We will further discuss robustness of the algorithm and show that the nonnegative case is very different from the bipolar one. One of our findings is that the positioning of the zero in the alphabet - i.e., whether it is a boundary element or not - is crucial.

A labview-based GUI for the measurement of otoacoustic emissions.

PubMed

Wu, Ye; McNamara, D M; Ziarani, A K

2006-01-01

This paper presents the outcome of a software development project aimed at creating a stand-alone user-friendly signal processing algorithm for the estimation of distortion product otoacoustic emission (OAE) signals. OAE testing is one of the most commonly used methods of first screening of newborns' hearing. Most of the currently available commercial devices rely upon averaging long strings of data and subsequent discrete Fourier analysis to estimate low level OAE signals from within the background noise in the presence of the strong stimuli. The main shortcoming of the presently employed technology is the need for long measurement time and its low noise immunity. The result of the software development project presented here is a graphical user interface (GUI) module that implements a recently introduced adaptive technique of OAE signal estimation. This software module is easy to use and is freely disseminated on the Internet for the use of the hearing research community. This GUI module allows loading of the a priori recorded OAE signals into the workspace, and provides the user with interactive instructions for the OAE signal estimation. Moreover, the user can generate simulated OAE signals to objectively evaluate the performance capability of the implemented signal processing technique.

SCOUT: A Fast Monte-Carlo Modeling Tool of Scintillation Camera Output

PubMed Central

Hunter, William C. J.; Barrett, Harrison H.; Lewellen, Thomas K.; Miyaoka, Robert S.; Muzi, John P.; Li, Xiaoli; McDougald, Wendy; MacDonald, Lawrence R.

2011-01-01

We have developed a Monte-Carlo photon-tracking and readout simulator called SCOUT to study the stochastic behavior of signals output from a simplified rectangular scintillation-camera design. SCOUT models the salient processes affecting signal generation, transport, and readout. Presently, we compare output signal statistics from SCOUT to experimental results for both a discrete and a monolithic camera. We also benchmark the speed of this simulation tool and compare it to existing simulation tools. We find this modeling tool to be relatively fast and predictive of experimental results. Depending on the modeled camera geometry, we found SCOUT to be 4 to 140 times faster than other modeling tools. PMID:22072297

SCOUT: a fast Monte-Carlo modeling tool of scintillation camera output†

PubMed Central

Hunter, William C J; Barrett, Harrison H.; Muzi, John P.; McDougald, Wendy; MacDonald, Lawrence R.; Miyaoka, Robert S.; Lewellen, Thomas K.

2013-01-01

We have developed a Monte-Carlo photon-tracking and readout simulator called SCOUT to study the stochastic behavior of signals output from a simplified rectangular scintillation-camera design. SCOUT models the salient processes affecting signal generation, transport, and readout of a scintillation camera. Presently, we compare output signal statistics from SCOUT to experimental results for both a discrete and a monolithic camera. We also benchmark the speed of this simulation tool and compare it to existing simulation tools. We find this modeling tool to be relatively fast and predictive of experimental results. Depending on the modeled camera geometry, we found SCOUT to be 4 to 140 times faster than other modeling tools. PMID:23640136

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

Parallel Processing of Broad-Band PPM Signals

NASA Technical Reports Server (NTRS)

Gray, Andrew; Kang, Edward; Lay, Norman; Vilnrotter, Victor; Srinivasan, Meera; Lee, Clement

2010-01-01

A parallel-processing algorithm and a hardware architecture to implement the algorithm have been devised for timeslot synchronization in the reception of pulse-position-modulated (PPM) optical or radio signals. As in the cases of some prior algorithms and architectures for parallel, discrete-time, digital processing of signals other than PPM, an incoming broadband signal is divided into multiple parallel narrower-band signals by means of sub-sampling and filtering. The number of parallel streams is chosen so that the frequency content of the narrower-band signals is low enough to enable processing by relatively-low speed complementary metal oxide semiconductor (CMOS) electronic circuitry. The algorithm and architecture are intended to satisfy requirements for time-varying time-slot synchronization and post-detection filtering, with correction of timing errors independent of estimation of timing errors. They are also intended to afford flexibility for dynamic reconfiguration and upgrading. The architecture is implemented in a reconfigurable CMOS processor in the form of a field-programmable gate array. The algorithm and its hardware implementation incorporate three separate time-varying filter banks for three distinct functions: correction of sub-sample timing errors, post-detection filtering, and post-detection estimation of timing errors. The design of the filter bank for correction of timing errors, the method of estimating timing errors, and the design of a feedback-loop filter are governed by a host of parameters, the most critical one, with regard to processing very broadband signals with CMOS hardware, being the number of parallel streams (equivalently, the rate-reduction parameter).

γ-radiation of excited nuclear discrete levels in peripheral heavy ion collisions

NASA Astrophysics Data System (ADS)

Korotkikh, V. L.; Chikin, K. A.

A new process of a nuclear excitation to discrete states in peripheral heavy ion collisions is studied. High-energy photons are emitted by the exited nuclei with energies up to a few tens of GeV at angles of a few hundred microradians with respect to the beam direction. We show that a two-stage process, where an electron-positron pair is produced by virtual photons emitted by nuclei and then the electron or positron excites the nucleus, has a large cross-section. It is equal to about 5 b for CaCa collisions. On the one hand, it produces a significant γ-rays background in the nuclear fragmentation region but, on the other hand, it could be used for monitoring the nuclear beam intensity at the LHC. These secondary nuclear photons could be a good signal for triggering peripheral nuclear collisions.

Vectorized Rebinning Algorithm for Fast Data Down-Sampling

NASA Technical Reports Server (NTRS)

Dean, Bruce; Aronstein, David; Smith, Jeffrey

2013-01-01

A vectorized rebinning (down-sampling) algorithm, applicable to N-dimensional data sets, has been developed that offers a significant reduction in computer run time when compared to conventional rebinning algorithms. For clarity, a two-dimensional version of the algorithm is discussed to illustrate some specific details of the algorithm content, and using the language of image processing, 2D data will be referred to as "images," and each value in an image as a "pixel." The new approach is fully vectorized, i.e., the down-sampling procedure is done as a single step over all image rows, and then as a single step over all image columns. Data rebinning (or down-sampling) is a procedure that uses a discretely sampled N-dimensional data set to create a representation of the same data, but with fewer discrete samples. Such data down-sampling is fundamental to digital signal processing, e.g., for data compression applications.

Damage localization by statistical evaluation of signal-processed mode shapes

NASA Astrophysics Data System (ADS)

Ulriksen, M. D.; Damkilde, L.

2015-07-01

Due to their inherent, ability to provide structural information on a local level, mode shapes and t.lieir derivatives are utilized extensively for structural damage identification. Typically, more or less advanced mathematical methods are implemented to identify damage-induced discontinuities in the spatial mode shape signals, hereby potentially facilitating damage detection and/or localization. However, by being based on distinguishing damage-induced discontinuities from other signal irregularities, an intrinsic deficiency in these methods is the high sensitivity towards measurement, noise. The present, article introduces a damage localization method which, compared to the conventional mode shape-based methods, has greatly enhanced robustness towards measurement, noise. The method is based on signal processing of spatial mode shapes by means of continuous wavelet, transformation (CWT) and subsequent, application of a generalized discrete Teager-Kaiser energy operator (GDTKEO) to identify damage-induced mode shape discontinuities. In order to evaluate whether the identified discontinuities are in fact, damage-induced, outlier analysis of principal components of the signal-processed mode shapes is conducted on the basis of T2-statistics. The proposed method is demonstrated in the context, of analytical work with a free-vibrating Euler-Bernoulli beam under noisy conditions.

Bayesian Inference for Signal-Based Seismic Monitoring

NASA Astrophysics Data System (ADS)

Moore, D.

2015-12-01

Traditional seismic monitoring systems rely on discrete detections produced by station processing software, discarding significant information present in the original recorded signal. SIG-VISA (Signal-based Vertically Integrated Seismic Analysis) is a system for global seismic monitoring through Bayesian inference on seismic signals. By modeling signals directly, our forward model is able to incorporate a rich representation of the physics underlying the signal generation process, including source mechanisms, wave propagation, and station response. This allows inference in the model to recover the qualitative behavior of recent geophysical methods including waveform matching and double-differencing, all as part of a unified Bayesian monitoring system that simultaneously detects and locates events from a global network of stations. We demonstrate recent progress in scaling up SIG-VISA to efficiently process the data stream of global signals recorded by the International Monitoring System (IMS), including comparisons against existing processing methods that show increased sensitivity from our signal-based model and in particular the ability to locate events (including aftershock sequences that can tax analyst processing) precisely from waveform correlation effects. We also provide a Bayesian analysis of an alleged low-magnitude event near the DPRK test site in May 2010 [1] [2], investigating whether such an event could plausibly be detected through automated processing in a signal-based monitoring system. [1] Zhang, Miao and Wen, Lianxing. "Seismological Evidence for a Low-Yield Nuclear Test on 12 May 2010 in North Korea". Seismological Research Letters, January/February 2015. [2] Richards, Paul. "A Seismic Event in North Korea on 12 May 2010". CTBTO SnT 2015 oral presentation, video at https://video-archive.ctbto.org/index.php/kmc/preview/partner_id/103/uiconf_id/4421629/entry_id/0_ymmtpps0/delivery/http

A systems approach for data compression and latency reduction in cortically controlled brain machine interfaces.

PubMed

Oweiss, Karim G

2006-07-01

This paper suggests a new approach for data compression during extracutaneous transmission of neural signals recorded by high-density microelectrode array in the cortex. The approach is based on exploiting the temporal and spatial characteristics of the neural recordings in order to strip the redundancy and infer the useful information early in the data stream. The proposed signal processing algorithms augment current filtering and amplification capability and may be a viable replacement to on chip spike detection and sorting currently employed to remedy the bandwidth limitations. Temporal processing is devised by exploiting the sparseness capabilities of the discrete wavelet transform, while spatial processing exploits the reduction in the number of physical channels through quasi-periodic eigendecomposition of the data covariance matrix. Our results demonstrate that substantial improvements are obtained in terms of lower transmission bandwidth, reduced latency and optimized processor utilization. We also demonstrate the improvements qualitatively in terms of superior denoising capabilities and higher fidelity of the obtained signals.

A high precision position sensor design and its signal processing algorithm for a maglev train.

PubMed

Xue, Song; Long, Zhiqiang; He, Ning; Chang, Wensen

2012-01-01

High precision positioning technology for a kind of high speed maglev train with an electromagnetic suspension (EMS) system is studied. At first, the basic structure and functions of the position sensor are introduced and some key techniques to enhance the positioning precision are designed. Then, in order to further improve the positioning signal quality and the fault-tolerant ability of the sensor, a new kind of discrete-time tracking differentiator (TD) is proposed based on nonlinear optimal control theory. This new TD has good filtering and differentiating performances and a small calculation load. It is suitable for real-time signal processing. The stability, convergence property and frequency characteristics of the TD are studied and analyzed thoroughly. The delay constant of the TD is figured out and an effective time delay compensation algorithm is proposed. Based on the TD technology, a filtering process is introduced in to improve the positioning signal waveform when the sensor is under bad working conditions, and a two-sensor switching algorithm is designed to eliminate the positioning errors caused by the joint gaps of the long stator. The effectiveness and stability of the sensor and its signal processing algorithms are proved by the experiments on a test train during a long-term test run.

A High Precision Position Sensor Design and Its Signal Processing Algorithm for a Maglev Train

PubMed Central

Xue, Song; Long, Zhiqiang; He, Ning; Chang, Wensen

2012-01-01

High precision positioning technology for a kind of high speed maglev train with an electromagnetic suspension (EMS) system is studied. At first, the basic structure and functions of the position sensor are introduced and some key techniques to enhance the positioning precision are designed. Then, in order to further improve the positioning signal quality and the fault-tolerant ability of the sensor, a new kind of discrete-time tracking differentiator (TD) is proposed based on nonlinear optimal control theory. This new TD has good filtering and differentiating performances and a small calculation load. It is suitable for real-time signal processing. The stability, convergence property and frequency characteristics of the TD are studied and analyzed thoroughly. The delay constant of the TD is figured out and an effective time delay compensation algorithm is proposed. Based on the TD technology, a filtering process is introduced in to improve the positioning signal waveform when the sensor is under bad working conditions, and a two-sensor switching algorithm is designed to eliminate the positioning errors caused by the joint gaps of the long stator. The effectiveness and stability of the sensor and its signal processing algorithms are proved by the experiments on a test train during a long-term test run. PMID:22778582

The Roadmaker's algorithm for the discrete pulse transform.

PubMed

Laurie, Dirk P

2011-02-01

The discrete pulse transform (DPT) is a decomposition of an observed signal into a sum of pulses, i.e., signals that are constant on a connected set and zero elsewhere. Originally developed for 1-D signal processing, the DPT has recently been generalized to more dimensions. Applications in image processing are currently being investigated. The time required to compute the DPT as originally defined via the successive application of LULU operators (members of a class of minimax filters studied by Rohwer) has been a severe drawback to its applicability. This paper introduces a fast method for obtaining such a decomposition, called the Roadmaker's algorithm because it involves filling pits and razing bumps. It acts selectively only on those features actually present in the signal, flattening them in order of increasing size by subtracing an appropriate positive or negative pulse, which is then appended to the decomposition. The implementation described here covers 1-D signal as well as two and 3-D image processing in a single framework. This is achieved by considering the signal or image as a function defined on a graph, with the geometry specified by the edges of the graph. Whenever a feature is flattened, nodes in the graph are merged, until eventually only one node remains. At that stage, a new set of edges for the same nodes as the graph, forming a tree structure, defines the obtained decomposition. The Roadmaker's algorithm is shown to be equivalent to the DPT in the sense of obtaining the same decomposition. However, its simpler operators are not in general equivalent to the LULU operators in situations where those operators are not applied successively. A by-product of the Roadmaker's algorithm is that it yields a proof of the so-called Highlight Conjecture, stated as an open problem in 2006. We pay particular attention to algorithmic details and complexity, including a demonstration that in the 1-D case, and also in the case of a complete graph, the Roadmaker's algorithm has optimal complexity: it runs in time O(m), where m is the number of arcs in the graph.

A Novel Signal Modeling Approach for Classification of Seizure and Seizure-Free EEG Signals.

PubMed

Gupta, Anubha; Singh, Pushpendra; Karlekar, Mandar

2018-05-01

This paper presents a signal modeling-based new methodology of automatic seizure detection in EEG signals. The proposed method consists of three stages. First, a multirate filterbank structure is proposed that is constructed using the basis vectors of discrete cosine transform. The proposed filterbank decomposes EEG signals into its respective brain rhythms: delta, theta, alpha, beta, and gamma. Second, these brain rhythms are statistically modeled with the class of self-similar Gaussian random processes, namely, fractional Brownian motion and fractional Gaussian noises. The statistics of these processes are modeled using a single parameter called the Hurst exponent. In the last stage, the value of Hurst exponent and autoregressive moving average parameters are used as features to design a binary support vector machine classifier to classify pre-ictal, inter-ictal (epileptic with seizure free interval), and ictal (seizure) EEG segments. The performance of the classifier is assessed via extensive analysis on two widely used data set and is observed to provide good accuracy on both the data set. Thus, this paper proposes a novel signal model for EEG data that best captures the attributes of these signals and hence, allows to boost the classification accuracy of seizure and seizure-free epochs.

Discretization analysis of bifurcation based nonlinear amplifiers

NASA Astrophysics Data System (ADS)

Feldkord, Sven; Reit, Marco; Mathis, Wolfgang

2017-09-01

Recently, for modeling biological amplification processes, nonlinear amplifiers based on the supercritical Andronov-Hopf bifurcation have been widely analyzed analytically. For technical realizations, digital systems have become the most relevant systems in signal processing applications. The underlying continuous-time systems are transferred to the discrete-time domain using numerical integration methods. Within this contribution, effects on the qualitative behavior of the Andronov-Hopf bifurcation based systems concerning numerical integration methods are analyzed. It is shown exemplarily that explicit Runge-Kutta methods transform the truncated normalform equation of the Andronov-Hopf bifurcation into the normalform equation of the Neimark-Sacker bifurcation. Dependent on the order of the integration method, higher order terms are added during this transformation.A rescaled normalform equation of the Neimark-Sacker bifurcation is introduced that allows a parametric design of a discrete-time system which corresponds to the rescaled Andronov-Hopf system. This system approximates the characteristics of the rescaled Hopf-type amplifier for a large range of parameters. The natural frequency and the peak amplitude are preserved for every set of parameters. The Neimark-Sacker bifurcation based systems avoid large computational effort that would be caused by applying higher order integration methods to the continuous-time normalform equations.

Sparse gammatone signal model optimized for English speech does not match the human auditory filters.

PubMed

Strahl, Stefan; Mertins, Alfred

2008-07-18

Evidence that neurosensory systems use sparse signal representations as well as improved performance of signal processing algorithms using sparse signal models raised interest in sparse signal coding in the last years. For natural audio signals like speech and environmental sounds, gammatone atoms have been derived as expansion functions that generate a nearly optimal sparse signal model (Smith, E., Lewicki, M., 2006. Efficient auditory coding. Nature 439, 978-982). Furthermore, gammatone functions are established models for the human auditory filters. Thus far, a practical application of a sparse gammatone signal model has been prevented by the fact that deriving the sparsest representation is, in general, computationally intractable. In this paper, we applied an accelerated version of the matching pursuit algorithm for gammatone dictionaries allowing real-time and large data set applications. We show that a sparse signal model in general has advantages in audio coding and that a sparse gammatone signal model encodes speech more efficiently in terms of sparseness than a sparse modified discrete cosine transform (MDCT) signal model. We also show that the optimal gammatone parameters derived for English speech do not match the human auditory filters, suggesting for signal processing applications to derive the parameters individually for each applied signal class instead of using psychometrically derived parameters. For brain research, it means that care should be taken with directly transferring findings of optimality for technical to biological systems.

Novel structures for Discrete Hartley Transform based on first-order moments

NASA Astrophysics Data System (ADS)

Xiong, Jun; Zheng, Wenjuan; Wang, Hao; Liu, Jianguo

2018-03-01

Discrete Hartley Transform (DHT) is an important tool in digital signal processing. In the present paper, the DHT is firstly transformed into the first-order moments-based form, then a new fast algorithm is proposed to calculate the first-order moments without multiplication. Based on the algorithm theory, the corresponding hardware architecture for DHT is proposed, which only contains shift operations and additions with no need for multipliers and large memory. To verify the availability and effectiveness, the proposed design is implemented with hardware description language and synthesized by Synopsys Design Compiler with 0.18-μm SMIC library. A series of experiments have proved that the proposed architecture has better performance in terms of the product of the hardware consumption and computation time.

Quantum cryptography with finite resources: unconditional security bound for discrete-variable protocols with one-way postprocessing.

PubMed

Scarani, Valerio; Renner, Renato

2008-05-23

We derive a bound for the security of quantum key distribution with finite resources under one-way postprocessing, based on a definition of security that is composable and has an operational meaning. While our proof relies on the assumption of collective attacks, unconditional security follows immediately for standard protocols such as Bennett-Brassard 1984 and six-states protocol. For single-qubit implementations of such protocols, we find that the secret key rate becomes positive when at least N approximately 10(5) signals are exchanged and processed. For any other discrete-variable protocol, unconditional security can be obtained using the exponential de Finetti theorem, but the additional overhead leads to very pessimistic estimates.

Design, implementation and application of distributed order PI control.

PubMed

Zhou, Fengyu; Zhao, Yang; Li, Yan; Chen, YangQuan

2013-05-01

In this paper, a series of distributed order PI controller design methods are derived and applied to the robust control of wheeled service robots, which can tolerate more structural and parametric uncertainties than the corresponding fractional order PI control. A practical discrete incremental distributed order PI control strategy is proposed basing on the discretization method and the frequency criterions, which can be commonly used in many fields of fractional order system, control and signal processing. Besides, an auto-tuning strategy and the genetic algorithm are applied to the distributed order PI control as well. A number of experimental results are provided to show the advantages and distinguished features of the discussed methods in fairways. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.

Comments on `Area and power efficient DCT architecture for image compression' by Dhandapani and Ramachandran

NASA Astrophysics Data System (ADS)

Cintra, Renato J.; Bayer, Fábio M.

2017-12-01

In [Dhandapani and Ramachandran, "Area and power efficient DCT architecture for image compression", EURASIP Journal on Advances in Signal Processing 2014, 2014:180] the authors claim to have introduced an approximation for the discrete cosine transform capable of outperforming several well-known approximations in literature in terms of additive complexity. We could not verify the above results and we offer corrections for their work.

Discrete diffusion models to study the effects of Mg2+ concentration on the PhoPQ signal transduction system

PubMed Central

2010-01-01

Background The challenge today is to develop a modeling and simulation paradigm that integrates structural, molecular and genetic data for a quantitative understanding of physiology and behavior of biological processes at multiple scales. This modeling method requires techniques that maintain a reasonable accuracy of the biological process and also reduces the computational overhead. This objective motivates the use of new methods that can transform the problem from energy and affinity based modeling to information theory based modeling. To achieve this, we transform all dynamics within the cell into a random event time, which is specified through an information domain measure like probability distribution. This allows us to use the “in silico” stochastic event based modeling approach to find the molecular dynamics of the system. Results In this paper, we present the discrete event simulation concept using the example of the signal transduction cascade triggered by extra-cellular Mg2+ concentration in the two component PhoPQ regulatory system of Salmonella Typhimurium. We also present a model to compute the information domain measure of the molecular transport process by estimating the statistical parameters of inter-arrival time between molecules/ions coming to a cell receptor as external signal. This model transforms the diffusion process into the information theory measure of stochastic event completion time to get the distribution of the Mg2+ departure events. Using these molecular transport models, we next study the in-silico effects of this external trigger on the PhoPQ system. Conclusions Our results illustrate the accuracy of the proposed diffusion models in explaining the molecular/ionic transport processes inside the cell. Also, the proposed simulation framework can incorporate the stochasticity in cellular environments to a certain degree of accuracy. We expect that this scalable simulation platform will be able to model more complex biological systems with reasonable accuracy to understand their temporal dynamics. PMID:21143785

Discrete diffusion models to study the effects of Mg2+ concentration on the PhoPQ signal transduction system.

PubMed

Ghosh, Preetam; Ghosh, Samik; Basu, Kalyan; Das, Sajal K; Zhang, Chaoyang

2010-12-01

The challenge today is to develop a modeling and simulation paradigm that integrates structural, molecular and genetic data for a quantitative understanding of physiology and behavior of biological processes at multiple scales. This modeling method requires techniques that maintain a reasonable accuracy of the biological process and also reduces the computational overhead. This objective motivates the use of new methods that can transform the problem from energy and affinity based modeling to information theory based modeling. To achieve this, we transform all dynamics within the cell into a random event time, which is specified through an information domain measure like probability distribution. This allows us to use the "in silico" stochastic event based modeling approach to find the molecular dynamics of the system. In this paper, we present the discrete event simulation concept using the example of the signal transduction cascade triggered by extra-cellular Mg2+ concentration in the two component PhoPQ regulatory system of Salmonella Typhimurium. We also present a model to compute the information domain measure of the molecular transport process by estimating the statistical parameters of inter-arrival time between molecules/ions coming to a cell receptor as external signal. This model transforms the diffusion process into the information theory measure of stochastic event completion time to get the distribution of the Mg2+ departure events. Using these molecular transport models, we next study the in-silico effects of this external trigger on the PhoPQ system. Our results illustrate the accuracy of the proposed diffusion models in explaining the molecular/ionic transport processes inside the cell. Also, the proposed simulation framework can incorporate the stochasticity in cellular environments to a certain degree of accuracy. We expect that this scalable simulation platform will be able to model more complex biological systems with reasonable accuracy to understand their temporal dynamics.

Security of a discretely signaled continuous variable quantum key distribution protocol for high rate systems.

PubMed

Zhang, Zheshen; Voss, Paul L

2009-07-06

We propose a continuous variable based quantum key distribution protocol that makes use of discretely signaled coherent light and reverse error reconciliation. We present a rigorous security proof against collective attacks with realistic lossy, noisy quantum channels, imperfect detector efficiency, and detector electronic noise. This protocol is promising for convenient, high-speed operation at link distances up to 50 km with the use of post-selection.

Cluster synchronization transmission of different external signals in discrete uncertain network

NASA Astrophysics Data System (ADS)

Li, Chengren; Lü, Ling; Chen, Liansong; Hong, Yixuan; Zhou, Shuang; Yang, Yiming

2018-07-01

We research cluster synchronization transmissions of different external signals in discrete uncertain network. Based on the Lyapunov theorem, the network controller and the identification law of uncertain adjustment parameter are designed, and they are efficiently used to achieve the cluster synchronization and the identification of uncertain adjustment parameter. In our technical scheme, the network nodes in each cluster and the transmitted external signal can be different, and they allow the presence of uncertain parameters in the network. Especially, we are free to choose the clustering topologies, the cluster number and the node number in each cluster.

Elevated cAMP improves signal-to-noise ratio in amphibian rod photoreceptors

PubMed Central

Govardovskii, Victor I.

2017-01-01

The absolute sensitivity of vertebrate retinas is set by a background noise, called dark noise, which originates from several different cell types and is generated by different molecular mechanisms. The major share of dark noise is produced by photoreceptors and consists of two components, discrete and continuous. Discrete noise is generated by spontaneous thermal activations of visual pigment. These events are undistinguishable from real single-photon responses (SPRs) and might be considered an equivalent of the signal. Continuous noise is produced by spontaneous fluctuations of the catalytic activity of the cGMP phosphodiesterase. This masks both SPR and spontaneous SPR-like responses. Circadian rhythms affect photoreceptors, among other systems by periodically increasing intracellular cAMP levels ([cAMP]in), which increases the size and changes the shape of SPRs. Here, we show that forskolin, a tool that increases [cAMP]in, affects the magnitude and frequency spectrum of the continuous and discrete components of dark noise in photoreceptors. By changing both components of rod signaling, the signal and the noise, cAMP is able to increase the photoreceptor signal-to-noise ratio by twofold. We propose that this results in a substantial improvement of signal detection, without compromising noise rejection, at the rod bipolar cell synapse. PMID:28611079

Application of process monitoring to anomaly detection in nuclear material processing systems via system-centric event interpretation of data from multiple sensors of varying reliability

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

Garcia, Humberto E.; Simpson, Michael F.; Lin, Wen-Chiao

In this paper, we apply an advanced safeguards approach and associated methods for process monitoring to a hypothetical nuclear material processing system. The assessment regarding the state of the processing facility is conducted at a systemcentric level formulated in a hybrid framework. This utilizes architecture for integrating both time- and event-driven data and analysis for decision making. While the time-driven layers of the proposed architecture encompass more traditional process monitoring methods based on time series data and analysis, the event-driven layers encompass operation monitoring methods based on discrete event data and analysis. By integrating process- and operation-related information and methodologiesmore » within a unified framework, the task of anomaly detection is greatly improved. This is because decision-making can benefit from not only known time-series relationships among measured signals but also from known event sequence relationships among generated events. This available knowledge at both time series and discrete event layers can then be effectively used to synthesize observation solutions that optimally balance sensor and data processing requirements. The application of the proposed approach is then implemented on an illustrative monitored system based on pyroprocessing and results are discussed.« less

Long Noncoding RNAs: a New Regulatory Code in Metabolic Control

PubMed Central

Zhao, Xu-Yun; Lin, Jiandie D.

2015-01-01

Long noncoding RNAs (lncRNAs) are emerging as an integral part of the regulatory information encoded in the genome. LncRNAs possess the unique capability to interact with nucleic acids and proteins and exert discrete effects on numerous biological processes. Recent studies have delineated multiple lncRNA pathways that control metabolic tissue development and function. The expansion of the regulatory code that links nutrient and hormonal signals to tissue metabolism gives new insights into the genetic and pathogenic mechanisms underlying metabolic disease. This review discusses lncRNA biology with a focus on its role in the development, signaling, and function of key metabolic tissues. PMID:26410599

A wideband, high-resolution spectrum analyzer

NASA Technical Reports Server (NTRS)

Quirk, M. P.; Wilck, H. C.; Garyantes, M. F.; Grimm, M. J.

1988-01-01

A two-million-channel, 40 MHz bandwidth, digital spectrum analyzer under development at the Jet Propulsion Laboratory is described. The analyzer system will serve as a prototype processor for the sky survey portion of NASA's Search for Extraterrestrial Intelligence program and for other applications in the Deep Space Network. The analyzer digitizes an analog input, performs a 2 (sup 21) point Discrete Fourier Transform, accumulates the output power, normalizes the output to remove frequency-dependent gain, and automates simple signal detection algorithms. Due to its built-in frequency-domain processing functions and configuration flexibility, the analyzer is a very powerful tool for real-time signal analysis.

A wide-band high-resolution spectrum analyzer.

PubMed

Quirk, M P; Garyantes, M F; Wilck, H C; Grimm, M J

1988-12-01

This paper describes a two-million-channel 40-MHz-bandwidth, digital spectrum analyzer under development at the Jet Propulsion Laboratory. The analyzer system will serve as a prototype processor for the sky survey portion of NASA's Search for Extraterrestrial Intelligence program and for other applications in the Deep Space Network. The analyzer digitizes an analog input, performs a 2(21)-point, Discrete Fourier Transform, accumulates the output power, normalizes the output to remove frequency-dependent gain, and automates simple signal detection algorithms. Due to its built-in frequency-domain processing functions and configuration flexibility, the analyzer is a very powerful tool for real-time signal analysis and detection.

Flt-1 (VEGFR-1) coordinates discrete stages of blood vessel formation

PubMed Central

Chappell, John C.; Cluceru, Julia G.; Nesmith, Jessica E.; Mouillesseaux, Kevin P.; Bradley, Vanessa B.; Hartland, Caitlin M.; Hashambhoy-Ramsay, Yasmin L.; Walpole, Joseph; Peirce, Shayn M.; Mac Gabhann, Feilim; Bautch, Victoria L.

2016-01-01

Aims In developing blood vessel networks, the overall level of vessel branching often correlates with angiogenic sprout initiations, but in some pathological situations, increased sprout initiations paradoxically lead to reduced vessel branching and impaired vascular function. We examine the hypothesis that defects in the discrete stages of angiogenesis can uniquely contribute to vessel branching outcomes. Methods and results Time-lapse movies of mammalian blood vessel development were used to define and quantify the dynamics of angiogenic sprouting. We characterized the formation of new functional conduits by classifying discrete sequential stages—sprout initiation, extension, connection, and stability—that are differentially affected by manipulation of vascular endothelial growth factor-A (VEGF-A) signalling via genetic loss of the receptor flt-1 (vegfr1). In mouse embryonic stem cell-derived vessels genetically lacking flt-1, overall branching is significantly decreased while sprout initiations are significantly increased. Flt-1−/− mutant sprouts are less likely to retract, and they form increased numbers of connections with other vessels. However, loss of flt-1 also leads to vessel collapse, which reduces the number of new stable conduits. Computational simulations predict that loss of flt-1 results in ectopic Flk-1 signalling in connecting sprouts post-fusion, causing protrusion of cell processes into avascular gaps and collapse of branches. Thus, defects in stabilization of new vessel connections offset increased sprout initiations and connectivity in flt-1−/− vascular networks, with an overall outcome of reduced numbers of new conduits. Conclusions These results show that VEGF-A signalling has stage-specific effects on vascular morphogenesis, and that understanding these effects on dynamic stages of angiogenesis and how they integrate to expand a vessel network may suggest new therapeutic strategies. PMID:27142980

Data-Driven Process Discovery: A Discrete Time Algebra for Relational Signal Analysis

DTIC Science & Technology

1996-12-01

would also like to thank Dr. Mark Oxley for his assistance in developing this abstract algebra and the mathematical notation found herein. Lastly, I... Mathematical Result.. 4-13 4.4. Demostration of Coefficient Signature Additon ........................ 4-14 4.5. Multivariate Relational Discovery...spaces with the recognition of cues in a specific space" [21]. Up to now, most of the Artificial Intelligence (Al) ’discovery’ work has emphasized one

The Limits of Special Operations Forces

DTIC Science & Technology

2016-12-07

counterin- surgency operations as well as the projection of discrete and discriminate force.2 Yet, despite the current enthusiasm, special operations...terms of signaling commitment and capa- bility through discrete operations. But absent other supporting elements—whether military, diplomatic, or

A toolbox for discrete modelling of cell signalling dynamics.

PubMed

Paterson, Yasmin Z; Shorthouse, David; Pleijzier, Markus W; Piterman, Nir; Bendtsen, Claus; Hall, Benjamin A; Fisher, Jasmin

2018-06-18

In an age where the volume of data regarding biological systems exceeds our ability to analyse it, many researchers are looking towards systems biology and computational modelling to help unravel the complexities of gene and protein regulatory networks. In particular, the use of discrete modelling allows generation of signalling networks in the absence of full quantitative descriptions of systems, which are necessary for ordinary differential equation (ODE) models. In order to make such techniques more accessible to mainstream researchers, tools such as the BioModelAnalyzer (BMA) have been developed to provide a user-friendly graphical interface for discrete modelling of biological systems. Here we use the BMA to build a library of discrete target functions of known canonical molecular interactions, translated from ordinary differential equations (ODEs). We then show that these BMA target functions can be used to reconstruct complex networks, which can correctly predict many known genetic perturbations. This new library supports the accessibility ethos behind the creation of BMA, providing a toolbox for the construction of complex cell signalling models without the need for extensive experience in computer programming or mathematical modelling, and allows for construction and simulation of complex biological systems with only small amounts of quantitative data.

Research of generalized wavelet transformations of Haar correctness in remote sensing of the Earth

NASA Astrophysics Data System (ADS)

Kazaryan, Maretta; Shakhramanyan, Mihail; Nedkov, Roumen; Richter, Andrey; Borisova, Denitsa; Stankova, Nataliya; Ivanova, Iva; Zaharinova, Mariana

2017-10-01

In this paper, Haar's generalized wavelet functions are applied to the problem of ecological monitoring by the method of remote sensing of the Earth. We study generalized Haar wavelet series and suggest the use of Tikhonov's regularization method for investigating them for correctness. In the solution of this problem, an important role is played by classes of functions that were introduced and described in detail by I.M. Sobol for studying multidimensional quadrature formulas and it contains functions with rapidly convergent series of wavelet Haar. A theorem on the stability and uniform convergence of the regularized summation function of the generalized wavelet-Haar series of a function from this class with approximate coefficients is proved. The article also examines the problem of using orthogonal transformations in Earth remote sensing technologies for environmental monitoring. Remote sensing of the Earth allows to receive from spacecrafts information of medium, high spatial resolution and to conduct hyperspectral measurements. Spacecrafts have tens or hundreds of spectral channels. To process the images, the device of discrete orthogonal transforms, and namely, wavelet transforms, was used. The aim of the work is to apply the regularization method in one of the problems associated with remote sensing of the Earth and subsequently to process the satellite images through discrete orthogonal transformations, in particular, generalized Haar wavelet transforms. General methods of research. In this paper, Tikhonov's regularization method, the elements of mathematical analysis, the theory of discrete orthogonal transformations, and methods for decoding of satellite images are used. Scientific novelty. The task of processing of archival satellite snapshots (images), in particular, signal filtering, was investigated from the point of view of an incorrectly posed problem. The regularization parameters for discrete orthogonal transformations were determined.

High Productivity Computing Systems Analysis and Performance

DTIC Science & Technology

2005-07-01

cubic grid Discrete Math Global Updates per second (GUP/S) RandomAccess Paper & Pencil Contact Bob Lucas (ISI) Multiple Precision none...can be found at the web site. One of the HPCchallenge codes, RandomAccess, is derived from the HPCS discrete math benchmarks that we released, and...Kernels Discrete Math … Graph Analysis … Linear Solvers … Signal Processi ng Execution Bounds Execution Indicators 6 Scalable Compact

The transfer function of neuron spike.

PubMed

Palmieri, Igor; Monteiro, Luiz H A; Miranda, Maria D

2015-08-01

The mathematical modeling of neuronal signals is a relevant problem in neuroscience. The complexity of the neuron behavior, however, makes this problem a particularly difficult task. Here, we propose a discrete-time linear time-invariant (LTI) model with a rational function in order to represent the neuronal spike detected by an electrode located in the surroundings of the nerve cell. The model is presented as a cascade association of two subsystems: one that generates an action potential from an input stimulus, and one that represents the medium between the cell and the electrode. The suggested approach employs system identification and signal processing concepts, and is dissociated from any considerations about the biophysical processes of the neuronal cell, providing a low-complexity alternative to model the neuronal spike. The model is validated by using in vivo experimental readings of intracellular and extracellular signals. A computational simulation of the model is presented in order to assess its proximity to the neuronal signal and to observe the variability of the estimated parameters. The implications of the results are discussed in the context of spike sorting. Copyright © 2015 Elsevier Ltd. All rights reserved.

The isolation of spatial patterning modes in a mathematical model of juxtacrine cell signalling.

PubMed

O'Dea, R D; King, J R

2013-06-01

Juxtacrine signalling mechanisms are known to be crucial in tissue and organ development, leading to spatial patterns in gene expression. We investigate the patterning behaviour of a discrete model of juxtacrine cell signalling due to Owen & Sherratt (1998, Mathematical modelling of juxtacrine cell signalling. Math. Biosci., 153, 125-150) in which ligand molecules, unoccupied receptors and bound ligand-receptor complexes are modelled. Feedback between the ligand and receptor production and the level of bound receptors is incorporated. By isolating two parameters associated with the feedback strength and employing numerical simulation, linear stability and bifurcation analysis, the pattern-forming behaviour of the model is analysed under regimes corresponding to lateral inhibition and induction. Linear analysis of this model fails to capture the patterning behaviour exhibited in numerical simulations. Via bifurcation analysis, we show that since the majority of periodic patterns fold subcritically from the homogeneous steady state, a wide variety of stable patterns exists at a given parameter set, providing an explanation for this failure. The dominant pattern is isolated via numerical simulation. Additionally, by sampling patterns of non-integer wavelength on a discrete mesh, we highlight a disparity between the continuous and discrete representations of signalling mechanisms: in the continuous case, patterns of arbitrary wavelength are possible, while sampling such patterns on a discrete mesh leads to longer wavelength harmonics being selected where the wavelength is rational; in the irrational case, the resulting aperiodic patterns exhibit 'local periodicity', being constructed from distorted stable shorter wavelength patterns. This feature is consistent with experimentally observed patterns, which typically display approximate short-range periodicity with defects.

Single- and multiple-pulse noncoherent detection statistics associated with partially developed speckle.

PubMed

Osche, G R

2000-08-20

Single- and multiple-pulse detection statistics are presented for aperture-averaged direct detection optical receivers operating against partially developed speckle fields. A partially developed speckle field arises when the probability density function of the received intensity does not follow negative exponential statistics. The case of interest here is the target surface that exhibits diffuse as well as specular components in the scattered radiation. An approximate expression is derived for the integrated intensity at the aperture, which leads to single- and multiple-pulse discrete probability density functions for the case of a Poisson signal in Poisson noise with an additive coherent component. In the absence of noise, the single-pulse discrete density function is shown to reduce to a generalized negative binomial distribution. The radar concept of integration loss is discussed in the context of direct detection optical systems where it is shown that, given an appropriate set of system parameters, multiple-pulse processing can be more efficient than single-pulse processing over a finite range of the integration parameter n.

EnvironmentalWaveletTool: Continuous and discrete wavelet analysis and filtering for environmental time series

NASA Astrophysics Data System (ADS)

Galiana-Merino, J. J.; Pla, C.; Fernandez-Cortes, A.; Cuezva, S.; Ortiz, J.; Benavente, D.

2014-10-01

A MATLAB-based computer code has been developed for the simultaneous wavelet analysis and filtering of several environmental time series, particularly focused on the analyses of cave monitoring data. The continuous wavelet transform, the discrete wavelet transform and the discrete wavelet packet transform have been implemented to provide a fast and precise time-period examination of the time series at different period bands. Moreover, statistic methods to examine the relation between two signals have been included. Finally, the entropy of curves and splines based methods have also been developed for segmenting and modeling the analyzed time series. All these methods together provide a user-friendly and fast program for the environmental signal analysis, with useful, practical and understandable results.

A 24 km fiber-based discretely signaled continuous variable quantum key distribution system.

PubMed

Dinh Xuan, Quyen; Zhang, Zheshen; Voss, Paul L

2009-12-21

We report a continuous variable key distribution system that achieves a final secure key rate of 3.45 kilobits/s over a distance of 24.2 km of optical fiber. The protocol uses discrete signaling and post-selection to improve reconciliation speed and quantifies security by means of quantum state tomography. Polarization multiplexing and a frequency translation scheme permit transmission of a continuous wave local oscillator and suppression of noise from guided acoustic wave Brillouin scattering by more than 27 dB.

Implementation of Adaptive Digital Controllers on Programmable Logic Devices

NASA Technical Reports Server (NTRS)

Gwaltney, David A.; King, Kenneth D.; Smith, Keary J.; Ormsby, John (Technical Monitor)

2002-01-01

Much has been made of the capabilities of FPGA's (Field Programmable Gate Arrays) in the hardware implementation of fast digital signal processing (DSP) functions. Such capability also makes and FPGA a suitable platform for the digital implementation of closed loop controllers. There are myriad advantages to utilizing an FPGA for discrete-time control functions which include the capability for reconfiguration when SRAM- based FPGA's are employed, fast parallel implementation of multiple control loops and implementations that can meet space level radiation tolerance in a compact form-factor. Other researchers have presented the notion that a second order digital filter with proportional-integral-derivative (PID) control functionality can be implemented in an FPGA. At Marshall Space Flight Center, the Control Electronics Group has been studying adaptive discrete-time control of motor driven actuator systems using digital signal processor (DSF) devices. Our goal is to create a fully digital, flight ready controller design that utilizes an FPGA for implementation of signal conditioning for control feedback signals, generation of commands to the controlled system, and hardware insertion of adaptive control algorithm approaches. While small form factor, commercial DSP devices are now available with event capture, data conversion, pulse width modulated outputs and communication peripherals, these devices are not currently available in designs and packages which meet space level radiation requirements. Meeting our goals requires alternative compact implementation of such functionality to withstand the harsh environment encountered on spacecraft. Radiation tolerant FPGA's are a feasible option for reaching these goals.

Tool Condition Monitoring in Micro-End Milling using wavelets

NASA Astrophysics Data System (ADS)

Dubey, N. K.; Roushan, A.; Rao, U. S.; Sandeep, K.; Patra, K.

2018-04-01

In this work, Tool Condition Monitoring (TCM) strategy is developed for micro-end milling of titanium alloy and mild steel work-pieces. Full immersion slot milling experiments are conducted using a solid tungsten carbide end mill for more than 1900 s to have reasonable amount of tool wear. During the micro-end milling process, cutting force and vibration signals are acquired using Kistler piezo-electric 3-component force dynamometer (9256C2) and accelerometer (NI cDAQ-9188) respectively. The force components and the vibration signals are processed using Discrete Wavelet Transformation (DWT) in both time and frequency window. 5-level wavelet packet decomposition using Db-8 wavelet is carried out and the detailed coefficients D1 to D5 for each of the signals are obtained. The results of the wavelet transformation are correlated with the tool wear. In case of vibration signals, de-noising is done for higher frequency components (D1) and force signals were de-noised for lower frequency components (D5). Increasing value of MAD (Mean Absolute Deviation) of the detail coefficients for successive channels depicted tool wear. The predictions of the tool wear are confirmed from the actual wear observed in the SEM of the worn tool.

Analysis of automobile engine cylinder pressure and rotation speed from engine body vibration signal

NASA Astrophysics Data System (ADS)

Wang, Yuhua; Cheng, Xiang; Tan, Haishu

2016-01-01

In order to improve the engine vibration signal process method for the engine cylinder pressure and engine revolution speed measurement instrument, the engine cylinder pressure varying with the engine working cycle process has been regarded as the main exciting force for the engine block forced vibration. The forced vibration caused by the engine cylinder pressure presents as a low frequency waveform which varies with the cylinder pressure synchronously and steadily in time domain and presents as low frequency high energy discrete humorous spectrum lines in frequency domain. The engine cylinder pressure and the rotation speed can been extract form the measured engine block vibration signal by low-pass filtering analysis in time domain or by FFT analysis in frequency domain, the low-pass filtering analysis in time domain is not only suitable for the engine in uniform revolution condition but also suitable for the engine in uneven revolution condition. That provides a practical and convenient way to design motor revolution rate and cylinder pressure measurement instrument.

Analyzing a stochastic time series obeying a second-order differential equation.

PubMed

Lehle, B; Peinke, J

2015-06-01

The stochastic properties of a Langevin-type Markov process can be extracted from a given time series by a Markov analysis. Also processes that obey a stochastically forced second-order differential equation can be analyzed this way by employing a particular embedding approach: To obtain a Markovian process in 2N dimensions from a non-Markovian signal in N dimensions, the system is described in a phase space that is extended by the temporal derivative of the signal. For a discrete time series, however, this derivative can only be calculated by a differencing scheme, which introduces an error. If the effects of this error are not accounted for, this leads to systematic errors in the estimation of the drift and diffusion functions of the process. In this paper we will analyze these errors and we will propose an approach that correctly accounts for them. This approach allows an accurate parameter estimation and, additionally, is able to cope with weak measurement noise, which may be superimposed to a given time series.

A hybrid continuous-discrete method for stochastic reaction-diffusion processes.

PubMed

Lo, Wing-Cheong; Zheng, Likun; Nie, Qing

2016-09-01

Stochastic fluctuations in reaction-diffusion processes often have substantial effect on spatial and temporal dynamics of signal transductions in complex biological systems. One popular approach for simulating these processes is to divide the system into small spatial compartments assuming that molecules react only within the same compartment and jump between adjacent compartments driven by the diffusion. While the approach is convenient in terms of its implementation, its computational cost may become prohibitive when diffusive jumps occur significantly more frequently than reactions, as in the case of rapid diffusion. Here, we present a hybrid continuous-discrete method in which diffusion is simulated using continuous approximation while reactions are based on the Gillespie algorithm. Specifically, the diffusive jumps are approximated as continuous Gaussian random vectors with time-dependent means and covariances, allowing use of a large time step, even for rapid diffusion. By considering the correlation among diffusive jumps, the approximation is accurate for the second moment of the diffusion process. In addition, a criterion is obtained for identifying the region in which such diffusion approximation is required to enable adaptive calculations for better accuracy. Applications to a linear diffusion system and two nonlinear systems of morphogens demonstrate the effectiveness and benefits of the new hybrid method.

Signal processing of white-light interferometric low-finesse fiber-optic Fabry-Perot sensors.

PubMed

Ma, Cheng; Wang, Anbo

2013-01-10

Signal processing for low-finesse fiber-optic Fabry-Perot sensors based on white-light interferometry is investigated. The problem is demonstrated as analogous to the parameter estimation of a noisy, real, discrete harmonic of finite length. The Cramer-Rao bounds for the estimators are given, and three algorithms are evaluated and proven to approach the bounds. A long-standing problem with these types of sensors is the unpredictable jumps in the phase estimation. Emphasis is made on the property and mechanism of the "total phase" estimator in reducing the estimation error, and a varying phase term in the total phase is identified to be responsible for the unwanted demodulation jumps. The theories are verified by simulation and experiment. A solution to reducing the probability of jump is demonstrated. © 2013 Optical Society of America

Development of a Chemically Reacting Flow Solver on the Graphic Processing Units

DTIC Science & Technology

2011-05-10

been implemented on the GPU by Schive et al. (2010). The outcome of their work is the GAMER code for astrophysical simulation. Thibault and...Euler equations at each cell. For simplification, consider the Euler equations in one dimension with no source terms; the discretized form of the...is known to be more diffusive than the other fluxes due to the large bound of the numerical signal velocities: b+, b-. 3.4 Time Marching Methods

[A NEW APPROACH FOR FOOD PREFERENCE TESTING IN ANIMAL EXPERIMENTATION].

PubMed

Albertin, S V

2015-10-01

An article describes the original method allowing to study a mechanism of food preference related to the sensory properties of foods in animals. The method gives a good possibility to select the role of visual and orosensory signaling in food preference as well as to model the processes of physiological and pathological food and drug dependence in animal experiments. The role of discrete food presentation in the formation of the current motivations and food preferences was discussed.

Frequency domain measurement systems

NASA Technical Reports Server (NTRS)

Eischer, M. C.

1978-01-01

Stable frequency sources and signal processing blocks were characterized by their noise spectra, both discrete and random, in the frequency domain. Conventional measures are outlined, and systems for performing the measurements are described. Broad coverage of system configurations which were found useful is given. Their functioning and areas of application are discussed briefly. Particular attention is given to some of the potential error sources in the measurement procedures, system configurations, double-balanced-mixer-phase-detectors, and application of measuring instruments.

Noncoherent parallel optical processor for discrete two-dimensional linear transformations.

PubMed

Glaser, I

1980-10-01

We describe a parallel optical processor, based on a lenslet array, that provides general linear two-dimensional transformations using noncoherent light. Such a processor could become useful in image- and signal-processing applications in which the throughput requirements cannot be adequately satisfied by state-of-the-art digital processors. Experimental results that illustrate the feasibility of the processor by demonstrating its use in parallel optical computation of the two-dimensional Walsh-Hadamard transformation are presented.

Investigating Patterns for Self-Induced Emotion Recognition from EEG Signals.

PubMed

Zhuang, Ning; Zeng, Ying; Yang, Kai; Zhang, Chi; Tong, Li; Yan, Bin

2018-03-12

Most current approaches to emotion recognition are based on neural signals elicited by affective materials such as images, sounds and videos. However, the application of neural patterns in the recognition of self-induced emotions remains uninvestigated. In this study we inferred the patterns and neural signatures of self-induced emotions from electroencephalogram (EEG) signals. The EEG signals of 30 participants were recorded while they watched 18 Chinese movie clips which were intended to elicit six discrete emotions, including joy, neutrality, sadness, disgust, anger and fear. After watching each movie clip the participants were asked to self-induce emotions by recalling a specific scene from each movie. We analyzed the important features, electrode distribution and average neural patterns of different self-induced emotions. Results demonstrated that features related to high-frequency rhythm of EEG signals from electrodes distributed in the bilateral temporal, prefrontal and occipital lobes have outstanding performance in the discrimination of emotions. Moreover, the six discrete categories of self-induced emotion exhibit specific neural patterns and brain topography distributions. We achieved an average accuracy of 87.36% in the discrimination of positive from negative self-induced emotions and 54.52% in the classification of emotions into six discrete categories. Our research will help promote the development of comprehensive endogenous emotion recognition methods.

Investigating Patterns for Self-Induced Emotion Recognition from EEG Signals

PubMed Central

Zeng, Ying; Yang, Kai; Tong, Li; Yan, Bin

2018-01-01

Most current approaches to emotion recognition are based on neural signals elicited by affective materials such as images, sounds and videos. However, the application of neural patterns in the recognition of self-induced emotions remains uninvestigated. In this study we inferred the patterns and neural signatures of self-induced emotions from electroencephalogram (EEG) signals. The EEG signals of 30 participants were recorded while they watched 18 Chinese movie clips which were intended to elicit six discrete emotions, including joy, neutrality, sadness, disgust, anger and fear. After watching each movie clip the participants were asked to self-induce emotions by recalling a specific scene from each movie. We analyzed the important features, electrode distribution and average neural patterns of different self-induced emotions. Results demonstrated that features related to high-frequency rhythm of EEG signals from electrodes distributed in the bilateral temporal, prefrontal and occipital lobes have outstanding performance in the discrimination of emotions. Moreover, the six discrete categories of self-induced emotion exhibit specific neural patterns and brain topography distributions. We achieved an average accuracy of 87.36% in the discrimination of positive from negative self-induced emotions and 54.52% in the classification of emotions into six discrete categories. Our research will help promote the development of comprehensive endogenous emotion recognition methods. PMID:29534515

Requirements of transcription factor Smad-dependent and -independent TGF-β signaling to control discrete T-cell functions.

PubMed

Gu, Ai-Di; Wang, Yunqi; Lin, Lin; Zhang, Song S; Wan, Yisong Y

2012-01-17

TGF-β modulates immune response by suppressing non-regulatory T (Treg) function and promoting Treg function. The question of whether TGF-β achieves distinct effects on non-Treg and Treg cells through discrete signaling pathways remains outstanding. In this study, we investigated the requirements of Smad-dependent and -independent TGF-β signaling for T-cell function. Smad2 and Smad3 double deficiency in T cells led to lethal inflammatory disorder in mice. Non-Treg cells were spontaneously activated and produced effector cytokines in vivo on deletion of both Smad2 and Smad3. In addition, TGF-β failed to suppress T helper differentiation efficiently and to promote induced Treg generation of non-Treg cells lacking both Smad2 and Smad3, suggesting that Smad-dependent signaling is obligatory to mediate TGF-β function in non-Treg cells. Unexpectedly, however, the development, homeostasis, and function of Treg cells remained intact in the absence of Smad2 and Smad3, suggesting that the Smad-independent pathway is important for Treg function. Indeed, Treg-specific deletion of TGF-β-activated kinase 1 led to failed Treg homeostasis and lethal immune disorder in mice. Therefore, Smad-dependent and -independent TGF-β signaling discretely controls non-Treg and Treg function to modulate immune tolerance and immune homeostasis.

A Discrete Dynamical System Approach to Pathway Activation Profiles of Signaling Cascades.

PubMed

Catozzi, S; Sepulchre, J-A

2017-08-01

In living organisms, cascades of covalent modification cycles are one of the major intracellular signaling mechanisms, allowing to transduce physical or chemical stimuli of the external world into variations of activated biochemical species within the cell. In this paper, we develop a novel method to study the stimulus-response of signaling cascades and overall the concept of pathway activation profile which is, for a given stimulus, the sequence of activated proteins at each tier of the cascade. Our approach is based on a correspondence that we establish between the stationary states of a cascade and pieces of orbits of a 2D discrete dynamical system. The study of its possible phase portraits in function of the biochemical parameters, and in particular of the contraction/expansion properties around the fixed points of this discrete map, as well as their bifurcations, yields a classification of the cascade tiers into three main types, whose biological impact within a signaling network is examined. In particular, our approach enables to discuss quantitatively the notion of cascade amplification/attenuation from this new perspective. The method allows also to study the interplay between forward and "retroactive" signaling, i.e., the upstream influence of an inhibiting drug bound to the last tier of the cascade.

Joint sparsity based heterogeneous data-level fusion for target detection and estimation

NASA Astrophysics Data System (ADS)

Niu, Ruixin; Zulch, Peter; Distasio, Marcello; Blasch, Erik; Shen, Dan; Chen, Genshe

2017-05-01

Typical surveillance systems employ decision- or feature-level fusion approaches to integrate heterogeneous sensor data, which are sub-optimal and incur information loss. In this paper, we investigate data-level heterogeneous sensor fusion. Since the sensors monitor the common targets of interest, whose states can be determined by only a few parameters, it is reasonable to assume that the measurement domain has a low intrinsic dimensionality. For heterogeneous sensor data, we develop a joint-sparse data-level fusion (JSDLF) approach based on the emerging joint sparse signal recovery techniques by discretizing the target state space. This approach is applied to fuse signals from multiple distributed radio frequency (RF) signal sensors and a video camera for joint target detection and state estimation. The JSDLF approach is data-driven and requires minimum prior information, since there is no need to know the time-varying RF signal amplitudes, or the image intensity of the targets. It can handle non-linearity in the sensor data due to state space discretization and the use of frequency/pixel selection matrices. Furthermore, for a multi-target case with J targets, the JSDLF approach only requires discretization in a single-target state space, instead of discretization in a J-target state space, as in the case of the generalized likelihood ratio test (GLRT) or the maximum likelihood estimator (MLE). Numerical examples are provided to demonstrate that the proposed JSDLF approach achieves excellent performance with near real-time accurate target position and velocity estimates.

Switched periodic systems in discrete time: stability and input-output norms

NASA Astrophysics Data System (ADS)

Bolzern, Paolo; Colaneri, Patrizio

2013-07-01

This paper deals with the analysis of stability and the characterisation of input-output norms for discrete-time periodic switched linear systems. Such systems consist of a network of time-periodic linear subsystems sharing the same state vector and an exogenous switching signal that triggers the jumps between the subsystems. The overall system exhibits a complex dynamic behaviour due to the interplay between the time periodicity of the subsystem parameters and the switching signal. Both arbitrary switching signals and signals satisfying a dwell-time constraint are considered. Linear matrix inequality conditions for stability and guaranteed H2 and H∞ performances are provided. The results heavily rely on the merge of the theory of linear periodic systems and recent developments on switched linear time-invariant systems.

Digital transmitter for data bus communications system

NASA Technical Reports Server (NTRS)

Proch, G. E. (Inventor)

1975-01-01

An improved digital transmitter for transmitting serial pulse code modulation (pcm) data at high bit rates over a transmission line is disclosed. When not transmitting, the transmitter features a high output impedance which prevents the transmitter from loading the transmission line. The pcm input is supplied to a logic control circuit which produces two discrete logic level signals which are supplied to an amplifier. The amplifier, which is transformer coupled to the output isolation circuitry, converts the discrete logic level signals to two high current level, ground isolated signals in the secondary windings of the coupling transformer. The latter signals are employed as inputs to the isolation circuitry which includes two series transistor pairs operating into a hybrid transformer functioning to isolate the transmitter circuitry from the transmission line.

Input reconstruction for networked control systems subject to deception attacks and data losses on control signals

NASA Astrophysics Data System (ADS)

Keller, J. Y.; Chabir, K.; Sauter, D.

2016-03-01

State estimation of stochastic discrete-time linear systems subject to unknown inputs or constant biases has been widely studied but no work has been dedicated to the case where a disturbance switches between unknown input and constant bias. We show that such disturbance can affect a networked control system subject to deception attacks and data losses on the control signals transmitted by the controller to the plant. This paper proposes to estimate the switching disturbance from an augmented state version of the intermittent unknown input Kalman filter recently developed by the authors. Sufficient stochastic stability conditions are established when the arrival binary sequence of data losses follows a Bernoulli random process.

Notch signalling coordinates tissue growth and wing fate specification in Drosophila.

PubMed

Rafel, Neus; Milán, Marco

2008-12-01

During the development of a given organ, tissue growth and fate specification are simultaneously controlled by the activity of a discrete number of signalling molecules. Here, we report that these two processes are extraordinarily coordinated in the Drosophila wing primordium, which extensively proliferates during larval development to give rise to the dorsal thoracic body wall and the adult wing. The developmental decision between wing and body wall is defined by the opposing activities of two secreted signalling molecules, Wingless and the EGF receptor ligand Vein. Notch signalling is involved in the determination of a variety of cell fates, including growth and cell survival. We present evidence that growth of the wing primordium mediated by the activity of Notch is required for wing fate specification. Our data indicate that tissue size modulates the activity range of the signalling molecules Wingless and Vein. These results highlight a crucial role of Notch in linking proliferation and fate specification in the developing wing primordium.

GPS Signal Corruption by the Discrete Aurora: Precise Measurements From the Mahali Experiment

NASA Astrophysics Data System (ADS)

Semeter, Joshua; Mrak, Sebastijan; Hirsch, Michael; Swoboda, John; Akbari, Hassan; Starr, Gregory; Hampton, Don; Erickson, Philip; Lind, Frank; Coster, Anthea; Pankratius, Victor

2017-10-01

Measurements from a dense network of GPS receivers have been used to clarify the relationship between substorm auroras and GPS signal corruption as manifested by loss of lock on the received signal. A network of nine receivers was deployed along roadways near the Poker Flat Research Range in central Alaska, with receiver spacing between 15 and 30 km. Instances of large-amplitude phase fluctuations and signal loss of lock were registered in space and time with auroral forms associated with a sequence of westward traveling surges associated with a substorm onset over central Canada. The following conclusions were obtained: (1) The signal corruption originated in the ionospheric E region, between 100 and 150 km altitude, and (2) the GPS links suffering loss of lock were confined to a narrow band (<20 km wide) along the trailing edge of the moving auroral forms. The results are discussed in the context of mechanisms typically cited to account for GPS phase scintillation by auroral processes.

Performance improvement by orthogonal pulse amplitude modulation and discrete multitone modulation signals in hybrid fiber-visible laser light communication system

NASA Astrophysics Data System (ADS)

Zhang, Fangliu; He, Jing; Deng, Rui; Chen, Qinghui; Chen, Lin

2016-10-01

A modulation format, orthogonal pulse amplitude modulation and discrete multitone modulation (O-PAM-DMT), is experimentally demonstrated in a hybrid fiber-visible laser light communication (fiber-VLLC) system using a cost-effective directly modulated laser and blue laser diode. In addition, low overhead is achieved by utilizing only one training sequence to implement synchronization and channel estimation. Through adjusting the ratio of PAM and DMT signal, three types of O-PAM-DMT signals are investigated. After transmission over a 20-km standard single-mode fiber and 5-m free-space VLLC, the receiver sensitivity for 4.36-Gbit/s O-PAM-DMT signals can be improved by 0.4, 1.4, and 2.7 dB, respectively, at a bit error rate of 1×10-3, compared with a conventional DMT signal.

Latent degradation indicators estimation and prediction: A Monte Carlo approach

NASA Astrophysics Data System (ADS)

Zhou, Yifan; Sun, Yong; Mathew, Joseph; Wolff, Rodney; Ma, Lin

2011-01-01

Asset health inspections can produce two types of indicators: (1) direct indicators (e.g. the thickness of a brake pad, and the crack depth on a gear) which directly relate to a failure mechanism; and (2) indirect indicators (e.g. the indicators extracted from vibration signals and oil analysis data) which can only partially reveal a failure mechanism. While direct indicators enable more precise references to asset health condition, they are often more difficult to obtain than indirect indicators. The state space model provides an efficient approach to estimating direct indicators by using indirect indicators. However, existing state space models to estimate direct indicators largely depend on assumptions such as, discrete time, discrete state, linearity, and Gaussianity. The discrete time assumption requires fixed inspection intervals. The discrete state assumption entails discretising continuous degradation indicators, which often introduces additional errors. The linear and Gaussian assumptions are not consistent with nonlinear and irreversible degradation processes in most engineering assets. This paper proposes a state space model without these assumptions. Monte Carlo-based algorithms are developed to estimate the model parameters and the remaining useful life. These algorithms are evaluated for performance using numerical simulations through MATLAB. The result shows that both the parameters and the remaining useful life are estimated accurately. Finally, the new state space model is used to process vibration and crack depth data from an accelerated test of a gearbox. During this application, the new state space model shows a better fitness result than the state space model with linear and Gaussian assumption.

High-resolution correlation

NASA Astrophysics Data System (ADS)

Nelson, D. J.

2007-09-01

In the basic correlation process a sequence of time-lag-indexed correlation coefficients are computed as the inner or dot product of segments of two signals. The time-lag(s) for which the magnitude of the correlation coefficient sequence is maximized is the estimated relative time delay of the two signals. For discrete sampled signals, the delay estimated in this manner is quantized with the same relative accuracy as the clock used in sampling the signals. In addition, the correlation coefficients are real if the input signals are real. There have been many methods proposed to estimate signal delay to more accuracy than the sample interval of the digitizer clock, with some success. These methods include interpolation of the correlation coefficients, estimation of the signal delay from the group delay function, and beam forming techniques, such as the MUSIC algorithm. For spectral estimation, techniques based on phase differentiation have been popular, but these techniques have apparently not been applied to the correlation problem . We propose a phase based delay estimation method (PBDEM) based on the phase of the correlation function that provides a significant improvement of the accuracy of time delay estimation. In the process, the standard correlation function is first calculated. A time lag error function is then calculated from the correlation phase and is used to interpolate the correlation function. The signal delay is shown to be accurately estimated as the zero crossing of the correlation phase near the index of the peak correlation magnitude. This process is nearly as fast as the conventional correlation function on which it is based. For real valued signals, a simple modification is provided, which results in the same correlation accuracy as is obtained for complex valued signals.

Error minimizing algorithms for nearest eighbor classifiers

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

Porter, Reid B; Hush, Don; Zimmer, G. Beate

2011-01-03

Stack Filters define a large class of discrete nonlinear filter first introd uced in image and signal processing for noise removal. In recent years we have suggested their application to classification problems, and investigated their relationship to other types of discrete classifiers such as Decision Trees. In this paper we focus on a continuous domain version of Stack Filter Classifiers which we call Ordered Hypothesis Machines (OHM), and investigate their relationship to Nearest Neighbor classifiers. We show that OHM classifiers provide a novel framework in which to train Nearest Neighbor type classifiers by minimizing empirical error based loss functions. Wemore » use the framework to investigate a new cost sensitive loss function that allows us to train a Nearest Neighbor type classifier for low false alarm rate applications. We report results on both synthetic data and real-world image data.« less

Kalman filters for fractional discrete-time stochastic systems along with time-delay in the observation signal

NASA Astrophysics Data System (ADS)

Torabi, H.; Pariz, N.; Karimpour, A.

2016-02-01

This paper investigates fractional Kalman filters when time-delay is entered in the observation signal in the discrete-time stochastic fractional order state-space representation. After investigating the common fractional Kalman filter, we try to derive a fractional Kalman filter for time-delay fractional systems. A detailed derivation is given. Fractional Kalman filters will be used to estimate recursively the states of fractional order state-space systems based on minimizing the cost function when there is a constant time delay (d) in the observation signal. The problem will be solved by converting the filtering problem to a usual d-step prediction problem for delay-free fractional systems.

Optimization of training sequence for DFT-spread DMT signal in optical access network with direct detection utilizing DML.

PubMed

Li, Fan; Li, Xinying; Yu, Jianjun; Chen, Lin

2014-09-22

We experimentally demonstrated the transmission of 79.86-Gb/s discrete-Fourier-transform spread 32 QAM discrete multi-tone (DFT-spread 32 QAM-DMT) signal over 20-km standard single-mode fiber (SSMF) utilizing directly modulated laser (DML). The experimental results show DFT-spread effectively reduces Peak-to-Average Power Ratio (PAPR) of DMT signal, and also well overcomes narrowband interference and high frequencies power attenuation. We compared different types of training sequence (TS) symbols and found that the optimized TS for channel estimation is the symbol with digital BPSK/QPSK modulation format due to its best performance against optical link noise during channel estimation.

Energy thresholds of discrete breathers in thermal equilibrium and relaxation processes.

PubMed

Ming, Yi; Ling, Dong-Bo; Li, Hui-Min; Ding, Ze-Jun

2017-06-01

So far, only the energy thresholds of single discrete breathers in nonlinear Hamiltonian systems have been analytically obtained. In this work, the energy thresholds of discrete breathers in thermal equilibrium and the energy thresholds of long-lived discrete breathers which can remain after a long time relaxation are analytically estimated for nonlinear chains. These energy thresholds are size dependent. The energy thresholds of discrete breathers in thermal equilibrium are the same as the previous analytical results for single discrete breathers. The energy thresholds of long-lived discrete breathers in relaxation processes are different from the previous results for single discrete breathers but agree well with the published numerical results known to us. Because real systems are either in thermal equilibrium or in relaxation processes, the obtained results could be important for experimental detection of discrete breathers.

EEG source analysis of data from paralysed subjects

NASA Astrophysics Data System (ADS)

Carabali, Carmen A.; Willoughby, John O.; Fitzgibbon, Sean P.; Grummett, Tyler; Lewis, Trent; DeLosAngeles, Dylan; Pope, Kenneth J.

2015-12-01

One of the limitations of Encephalography (EEG) data is its quality, as it is usually contaminated with electric signal from muscle. This research intends to study results of two EEG source analysis methods applied to scalp recordings taken in paralysis and in normal conditions during the performance of a cognitive task. The aim is to determinate which types of analysis are appropriate for dealing with EEG data containing myogenic components. The data used are the scalp recordings of six subjects in normal conditions and during paralysis while performing different cognitive tasks including the oddball task which is the object of this research. The data were pre-processed by filtering it and correcting artefact, then, epochs of one second long for targets and distractors were extracted. Distributed source analysis was performed in BESA Research 6.0, using its results and information from the literature, 9 ideal locations for source dipoles were identified. The nine dipoles were used to perform discrete source analysis, fitting them to the averaged epochs for obtaining source waveforms. The results were statistically analysed comparing the outcomes before and after the subjects were paralysed. Finally, frequency analysis was performed for better explain the results. The findings were that distributed source analysis could produce confounded results for EEG contaminated with myogenic signals, conversely, statistical analysis of the results from discrete source analysis showed that this method could help for dealing with EEG data contaminated with muscle electrical signal.

Measurand transient signal suppressor

NASA Technical Reports Server (NTRS)

Bozeman, Richard J., Jr. (Inventor)

1994-01-01

A transient signal suppressor for use in a controls system which is adapted to respond to a change in a physical parameter whenever it crosses a predetermined threshold value in a selected direction of increasing or decreasing values with respect to the threshold value and is sustained for a selected discrete time interval is presented. The suppressor includes a sensor transducer for sensing the physical parameter and generating an electrical input signal whenever the sensed physical parameter crosses the threshold level in the selected direction. A manually operated switch is provided for adapting the suppressor to produce an output drive signal whenever the physical parameter crosses the threshold value in the selected direction of increasing or decreasing values. A time delay circuit is selectively adjustable for suppressing the transducer input signal for a preselected one of a plurality of available discrete suppression time and producing an output signal only if the input signal is sustained for a time greater than the selected suppression time. An electronic gate is coupled to receive the transducer input signal and the timer output signal and produce an output drive signal for energizing a control relay whenever the transducer input is a non-transient signal which is sustained beyond the selected time interval.

Gradient-based multiresolution image fusion.

PubMed

Petrović, Valdimir S; Xydeas, Costas S

2004-02-01

A novel approach to multiresolution signal-level image fusion is presented for accurately transferring visual information from any number of input image signals, into a single fused image without loss of information or the introduction of distortion. The proposed system uses a "fuse-then-decompose" technique realized through a novel, fusion/decomposition system architecture. In particular, information fusion is performed on a multiresolution gradient map representation domain of image signal information. At each resolution, input images are represented as gradient maps and combined to produce new, fused gradient maps. Fused gradient map signals are processed, using gradient filters derived from high-pass quadrature mirror filters to yield a fused multiresolution pyramid representation. The fused output image is obtained by applying, on the fused pyramid, a reconstruction process that is analogous to that of conventional discrete wavelet transform. This new gradient fusion significantly reduces the amount of distortion artefacts and the loss of contrast information usually observed in fused images obtained from conventional multiresolution fusion schemes. This is because fusion in the gradient map domain significantly improves the reliability of the feature selection and information fusion processes. Fusion performance is evaluated through informal visual inspection and subjective psychometric preference tests, as well as objective fusion performance measurements. Results clearly demonstrate the superiority of this new approach when compared to conventional fusion systems.

Implementation of Adaptive Digital Controllers on Programmable Logic Devices

NASA Technical Reports Server (NTRS)

Gwaltney, David A.; King, Kenneth D.; Smith, Keary J.; Monenegro, Justino (Technical Monitor)

2002-01-01

Much has been made of the capabilities of FPGA's (Field Programmable Gate Arrays) in the hardware implementation of fast digital signal processing. Such capability also makes an FPGA a suitable platform for the digital implementation of closed loop controllers. Other researchers have implemented a variety of closed-loop digital controllers on FPGA's. Some of these controllers include the widely used proportional-integral-derivative (PID) controller, state space controllers, neural network and fuzzy logic based controllers. There are myriad advantages to utilizing an FPGA for discrete-time control functions which include the capability for reconfiguration when SRAM-based FPGA's are employed, fast parallel implementation of multiple control loops and implementations that can meet space level radiation tolerance requirements in a compact form-factor. Generally, a software implementation on a DSP (Digital Signal Processor) or microcontroller is used to implement digital controllers. At Marshall Space Flight Center, the Control Electronics Group has been studying adaptive discrete-time control of motor driven actuator systems using digital signal processor (DSP) devices. While small form factor, commercial DSP devices are now available with event capture, data conversion, pulse width modulated (PWM) outputs and communication peripherals, these devices are not currently available in designs and packages which meet space level radiation requirements. In general, very few DSP devices are produced that are designed to meet any level of radiation tolerance or hardness. The goal of this effort is to create a fully digital, flight ready controller design that utilizes an FPGA for implementation of signal conditioning for control feedback signals, generation of commands to the controlled system, and hardware insertion of adaptive control algorithm approaches. An alternative is required for compact implementation of such functionality to withstand the harsh environment encountered on spacecraft. Radiation tolerant FPGA's are a feasible option for reaching this goal.

Application of wavelet filtering and Barker-coded pulse compression hybrid method to air-coupled ultrasonic testing

NASA Astrophysics Data System (ADS)

Zhou, Zhenggan; Ma, Baoquan; Jiang, Jingtao; Yu, Guang; Liu, Kui; Zhang, Dongmei; Liu, Weiping

2014-10-01

Air-coupled ultrasonic testing (ACUT) technique has been viewed as a viable solution in defect detection of advanced composites used in aerospace and aviation industries. However, the giant mismatch of acoustic impedance in air-solid interface makes the transmission efficiency of ultrasound low, and leads to poor signal-to-noise (SNR) ratio of received signal. The utilisation of signal-processing techniques in non-destructive testing is highly appreciated. This paper presents a wavelet filtering and phase-coded pulse compression hybrid method to improve the SNR and output power of received signal. The wavelet transform is utilised to filter insignificant components from noisy ultrasonic signal, and pulse compression process is used to improve the power of correlated signal based on cross-correction algorithm. For the purpose of reasonable parameter selection, different families of wavelets (Daubechies, Symlet and Coiflet) and decomposition level in discrete wavelet transform are analysed, different Barker codes (5-13 bits) are also analysed to acquire higher main-to-side lobe ratio. The performance of the hybrid method was verified in a honeycomb composite sample. Experimental results demonstrated that the proposed method is very efficient in improving the SNR and signal strength. The applicability of the proposed method seems to be a very promising tool to evaluate the integrity of high ultrasound attenuation composite materials using the ACUT.

Nonlinear Signal Processing and Team Differential Games.

DTIC Science & Technology

1986-03-01

w can be viewed as a control variable belonging to a mythical mini- mizing third party, such that (33) is a Nash strategy. It can be shown that the...Morgenstern [2] the discrete game analysis embodied most of the prin- ciples of the game theory yet recognized as important. But it is not until the...more common variety. Nor can it be treated as a second phase of a bargaining game with coalitions already formed, such as studied by Von Netman and

Smart Phase Tuning in Microwave Photonic Integrated Circuits Toward Automated Frequency Multiplication by Design

NASA Astrophysics Data System (ADS)

Nabavi, N.

2018-07-01

The author investigates the monitoring methods for fine adjustment of the previously proposed on-chip architecture for frequency multiplication and translation of harmonics by design. Digital signal processing (DSP) algorithms are utilized to create an optimized microwave photonic integrated circuit functionality toward automated frequency multiplication. The implemented DSP algorithms are formed on discrete Fourier transform and optimization-based algorithms (Greedy and gradient-based algorithms), which are analytically derived and numerically compared based on the accuracy and speed of convergence criteria.

Mathematical Methods of Communication Signal Design

DTIC Science & Technology

1990-09-30

Labelling of Annals of Discrete Math ., 1989-90. iv. T. Etzion, S.W. Golomb, and H. Taylor, "Polygonal Path Constructions for Tuscan-k Squares...the Special Issue on Graph Labellings of A,.nals of Discrete Math ., 1989-1990. vi. T. Etzion, "An Algorithm for Realization of Permutations in a

Application of wavelet and Fuorier transforms as powerful alternatives for derivative spectrophotometry in analysis of binary mixtures: A comparative study

NASA Astrophysics Data System (ADS)

Hassan, Said A.; Abdel-Gawad, Sherif A.

2018-02-01

Two signal processing methods, namely, Continuous Wavelet Transform (CWT) and the second was Discrete Fourier Transform (DFT) were introduced as alternatives to the classical Derivative Spectrophotometry (DS) in analysis of binary mixtures. To show the advantages of these methods, a comparative study was performed on a binary mixture of Naltrexone (NTX) and Bupropion (BUP). The methods were compared by analyzing laboratory prepared mixtures of the two drugs. By comparing performance of the three methods, it was proved that CWT and DFT methods are more efficient and advantageous in analysis of mixtures with overlapped spectra than DS. The three signal processing methods were adopted for the quantification of NTX and BUP in pure and tablet forms. The adopted methods were validated according to the ICH guideline where accuracy, precision and specificity were found to be within appropriate limits.

How input fluctuations reshape the dynamics of a biological switching system

NASA Astrophysics Data System (ADS)

Hu, Bo; Kessler, David A.; Rappel, Wouter-Jan; Levine, Herbert

2012-12-01

An important task in quantitative biology is to understand the role of stochasticity in biochemical regulation. Here, as an extension of our recent work [Phys. Rev. Lett.PRLTAO0031-900710.1103/PhysRevLett.107.148101 107, 148101 (2011)], we study how input fluctuations affect the stochastic dynamics of a simple biological switch. In our model, the on transition rate of the switch is directly regulated by a noisy input signal, which is described as a non-negative mean-reverting diffusion process. This continuous process can be a good approximation of the discrete birth-death process and is much more analytically tractable. Within this setup, we apply the Feynman-Kac theorem to investigate the statistical features of the output switching dynamics. Consistent with our previous findings, the input noise is found to effectively suppress the input-dependent transitions. We show analytically that this effect becomes significant when the input signal fluctuates greatly in amplitude and reverts slowly to its mean.

Discretization of Continuous Time Discrete Scale Invariant Processes: Estimation and Spectra

NASA Astrophysics Data System (ADS)

Rezakhah, Saeid; Maleki, Yasaman

2016-07-01

Imposing some flexible sampling scheme we provide some discretization of continuous time discrete scale invariant (DSI) processes which is a subsidiary discrete time DSI process. Then by introducing some simple random measure we provide a second continuous time DSI process which provides a proper approximation of the first one. This enables us to provide a bilateral relation between covariance functions of the subsidiary process and the new continuous time processes. The time varying spectral representation of such continuous time DSI process is characterized, and its spectrum is estimated. Also, a new method for estimation time dependent Hurst parameter of such processes is provided which gives a more accurate estimation. The performance of this estimation method is studied via simulation. Finally this method is applied to the real data of S & P500 and Dow Jones indices for some special periods.

Redox signaling: Potential arbitrator of autophagy and apoptosis in therapeutic response.

PubMed

Zhang, Lu; Wang, Kui; Lei, Yunlong; Li, Qifu; Nice, Edouard Collins; Huang, Canhua

2015-12-01

Redox signaling plays important roles in the regulation of cell death and survival in response to cancer therapy. Autophagy and apoptosis are discrete cellular processes mediated by distinct groups of regulatory and executioner molecules, and both are thought to be cellular responses to various stress conditions including oxidative stress, therefore controlling cell fate. Basic levels of reactive oxygen species (ROS) may function as signals to promote cell proliferation and survival, whereas increase of ROS can induce autophagy and apoptosis by damaging cellular components. Growing evidence in recent years argues for ROS that below detrimental levels acting as intracellular signal transducers that regulate autophagy and apoptosis. ROS-regulated autophagy and apoptosis can cross-talk with each other. However, how redox signaling determines different cell fates by regulating autophagy and apoptosis remains unclear. In this review, we will focus on understanding the delicate molecular mechanism by which autophagy and apoptosis are finely orchestrated by redox signaling and discuss how this understanding can be used to develop strategies for the treatment of cancer. Copyright © 2015 Elsevier Inc. All rights reserved.

Radial artery pulse waveform analysis based on curve fitting using discrete Fourier series.

PubMed

Jiang, Zhixing; Zhang, David; Lu, Guangming

2018-04-19

Radial artery pulse diagnosis has been playing an important role in traditional Chinese medicine (TCM). For its non-invasion and convenience, the pulse diagnosis has great significance in diseases analysis of modern medicine. The practitioners sense the pulse waveforms in patients' wrist to make diagnoses based on their non-objective personal experience. With the researches of pulse acquisition platforms and computerized analysis methods, the objective study on pulse diagnosis can help the TCM to keep up with the development of modern medicine. In this paper, we propose a new method to extract feature from pulse waveform based on discrete Fourier series (DFS). It regards the waveform as one kind of signal that consists of a series of sub-components represented by sine and cosine (SC) signals with different frequencies and amplitudes. After the pulse signals are collected and preprocessed, we fit the average waveform for each sample using discrete Fourier series by least squares. The feature vector is comprised by the coefficients of discrete Fourier series function. Compared with the fitting method using Gaussian mixture function, the fitting errors of proposed method are smaller, which indicate that our method can represent the original signal better. The classification performance of proposed feature is superior to the other features extracted from waveform, liking auto-regression model and Gaussian mixture model. The coefficients of optimized DFS function, who is used to fit the arterial pressure waveforms, can obtain better performance in modeling the waveforms and holds more potential information for distinguishing different psychological states. Copyright © 2018 Elsevier B.V. All rights reserved.

Time-frequency energy density precipitation method for time-of-flight extraction of narrowband Lamb wave detection signals

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

Zhang, Y., E-mail: thuzhangyu@foxmail.com; Huang, S. L., E-mail: huangsling@tsinghua.edu.cn; Wang, S.

The time-of-flight of the Lamb wave provides an important basis for defect evaluation in metal plates and is the input signal for Lamb wave tomographic imaging. However, the time-of-flight can be difficult to acquire because of the Lamb wave dispersion characteristics. This work proposes a time-frequency energy density precipitation method to accurately extract the time-of-flight of narrowband Lamb wave detection signals in metal plates. In the proposed method, a discrete short-time Fourier transform is performed on the narrowband Lamb wave detection signals to obtain the corresponding discrete time-frequency energy density distribution. The energy density values at the center frequency formore » all discrete time points are then calculated by linear interpolation. Next, the time-domain energy density curve focused on that center frequency is precipitated by least squares fitting of the calculated energy density values. Finally, the peak times of the energy density curve obtained relative to the initial pulse signal are extracted as the time-of-flight for the narrowband Lamb wave detection signals. An experimental platform is established for time-of-flight extraction of narrowband Lamb wave detection signals, and sensitivity analysis of the proposed time-frequency energy density precipitation method is performed in terms of propagation distance, dispersion characteristics, center frequency, and plate thickness. For comparison, the widely used Hilbert–Huang transform method is also implemented for time-of-flight extraction. The results show that the time-frequency energy density precipitation method can accurately extract the time-of-flight with relative error of <1% and thus can act as a universal time-of-flight extraction method for narrowband Lamb wave detection signals.« less

Time-frequency energy density precipitation method for time-of-flight extraction of narrowband Lamb wave detection signals.

PubMed

Zhang, Y; Huang, S L; Wang, S; Zhao, W

2016-05-01

The time-of-flight of the Lamb wave provides an important basis for defect evaluation in metal plates and is the input signal for Lamb wave tomographic imaging. However, the time-of-flight can be difficult to acquire because of the Lamb wave dispersion characteristics. This work proposes a time-frequency energy density precipitation method to accurately extract the time-of-flight of narrowband Lamb wave detection signals in metal plates. In the proposed method, a discrete short-time Fourier transform is performed on the narrowband Lamb wave detection signals to obtain the corresponding discrete time-frequency energy density distribution. The energy density values at the center frequency for all discrete time points are then calculated by linear interpolation. Next, the time-domain energy density curve focused on that center frequency is precipitated by least squares fitting of the calculated energy density values. Finally, the peak times of the energy density curve obtained relative to the initial pulse signal are extracted as the time-of-flight for the narrowband Lamb wave detection signals. An experimental platform is established for time-of-flight extraction of narrowband Lamb wave detection signals, and sensitivity analysis of the proposed time-frequency energy density precipitation method is performed in terms of propagation distance, dispersion characteristics, center frequency, and plate thickness. For comparison, the widely used Hilbert-Huang transform method is also implemented for time-of-flight extraction. The results show that the time-frequency energy density precipitation method can accurately extract the time-of-flight with relative error of <1% and thus can act as a universal time-of-flight extraction method for narrowband Lamb wave detection signals.

Laboratory for Engineering Man/Machine Systems (LEMS): System identification, model reduction and deconvolution filtering using Fourier based modulating signals and high order statistics

NASA Technical Reports Server (NTRS)

Pan, Jianqiang

1992-01-01

Several important problems in the fields of signal processing and model identification, such as system structure identification, frequency response determination, high order model reduction, high resolution frequency analysis, deconvolution filtering, and etc. Each of these topics involves a wide range of applications and has received considerable attention. Using the Fourier based sinusoidal modulating signals, it is shown that a discrete autoregressive model can be constructed for the least squares identification of continuous systems. Some identification algorithms are presented for both SISO and MIMO systems frequency response determination using only transient data. Also, several new schemes for model reduction were developed. Based upon the complex sinusoidal modulating signals, a parametric least squares algorithm for high resolution frequency estimation is proposed. Numerical examples show that the proposed algorithm gives better performance than the usual. Also, the problem was studied of deconvolution and parameter identification of a general noncausal nonminimum phase ARMA system driven by non-Gaussian stationary random processes. Algorithms are introduced for inverse cumulant estimation, both in the frequency domain via the FFT algorithms and in the domain via the least squares algorithm.

A Novel DFT-Based DOA Estimation by a Virtual Array Extension Using Simple Multiplications for FMCW Radar

PubMed Central

Kim, Bongseok; Kim, Sangdong; Lee, Jonghun

2018-01-01

We propose a novel discrete Fourier transform (DFT)-based direction of arrival (DOA) estimation by a virtual array extension using simple multiplications for frequency modulated continuous wave (FMCW) radar. DFT-based DOA estimation is usually employed in radar systems because it provides the advantage of low complexity for real-time signal processing. In order to enhance the resolution of DOA estimation or to decrease the missing detection probability, it is essential to have a considerable number of channel signals. However, due to constraints of space and cost, it is not easy to increase the number of channel signals. In order to address this issue, we increase the number of effective channel signals by generating virtual channel signals using simple multiplications of the given channel signals. The increase in channel signals allows the proposed scheme to detect DOA more accurately than the conventional scheme while using the same number of channel signals. Simulation results show that the proposed scheme achieves improved DOA estimation compared to the conventional DFT-based method. Furthermore, the effectiveness of the proposed scheme in a practical environment is verified through the experiment. PMID:29758016

Sparse dictionary for synthetic transmit aperture medical ultrasound imaging.

PubMed

Wang, Ping; Jiang, Jin-Yang; Li, Na; Luo, Han-Wu; Li, Fang; Cui, Shi-Gang

2017-07-01

It is possible to recover a signal below the Nyquist sampling limit using a compressive sensing technique in ultrasound imaging. However, the reconstruction enabled by common sparse transform approaches does not achieve satisfactory results. Considering the ultrasound echo signal's features of attenuation, repetition, and superposition, a sparse dictionary with the emission pulse signal is proposed. Sparse coefficients in the proposed dictionary have high sparsity. Images reconstructed with this dictionary were compared with those obtained with the three other common transforms, namely, discrete Fourier transform, discrete cosine transform, and discrete wavelet transform. The performance of the proposed dictionary was analyzed via a simulation and experimental data. The mean absolute error (MAE) was used to quantify the quality of the reconstructions. Experimental results indicate that the MAE associated with the proposed dictionary was always the smallest, the reconstruction time required was the shortest, and the lateral resolution and contrast of the reconstructed images were also the closest to the original images. The proposed sparse dictionary performed better than the other three sparse transforms. With the same sampling rate, the proposed dictionary achieved excellent reconstruction quality.

Approximation-Based Discrete-Time Adaptive Position Tracking Control for Interior Permanent Magnet Synchronous Motors.

PubMed

Yu, Jinpeng; Shi, Peng; Yu, Haisheng; Chen, Bing; Lin, Chong

2015-07-01

This paper considers the problem of discrete-time adaptive position tracking control for a interior permanent magnet synchronous motor (IPMSM) based on fuzzy-approximation. Fuzzy logic systems are used to approximate the nonlinearities of the discrete-time IPMSM drive system which is derived by direct discretization using Euler method, and a discrete-time fuzzy position tracking controller is designed via backstepping approach. In contrast to existing results, the advantage of the scheme is that the number of the adjustable parameters is reduced to two only and the problem of coupling nonlinearity can be overcome. It is shown that the proposed discrete-time fuzzy controller can guarantee the tracking error converges to a small neighborhood of the origin and all the signals are bounded. Simulation results illustrate the effectiveness and the potentials of the theoretic results obtained.

Analog 65/130 nm CMOS 5 GHz Sub-Arrays with ROACH-2 FPGA Beamformers for Hybrid Aperture-Array Receivers

DTIC Science & Technology

2017-03-20

sub-array, which is based on all-pass filters (APFs) is realized using 130 nm CMOS technology. Approximate- discrete Fourier transform (a-DFT...fixed beams are directed at known directions [9]. The proposed approximate- discrete Fourier transform (a-DFT) based multi-beamformer [9] yields L...to digital conversion daughter board. occurs in the discrete time domain (in ROACH-2 FPGA platform) following signal digitization (see Figs. 1(d) and

A hybrid continuous-discrete method for stochastic reaction–diffusion processes

PubMed Central

Zheng, Likun; Nie, Qing

2016-01-01

Stochastic fluctuations in reaction–diffusion processes often have substantial effect on spatial and temporal dynamics of signal transductions in complex biological systems. One popular approach for simulating these processes is to divide the system into small spatial compartments assuming that molecules react only within the same compartment and jump between adjacent compartments driven by the diffusion. While the approach is convenient in terms of its implementation, its computational cost may become prohibitive when diffusive jumps occur significantly more frequently than reactions, as in the case of rapid diffusion. Here, we present a hybrid continuous-discrete method in which diffusion is simulated using continuous approximation while reactions are based on the Gillespie algorithm. Specifically, the diffusive jumps are approximated as continuous Gaussian random vectors with time-dependent means and covariances, allowing use of a large time step, even for rapid diffusion. By considering the correlation among diffusive jumps, the approximation is accurate for the second moment of the diffusion process. In addition, a criterion is obtained for identifying the region in which such diffusion approximation is required to enable adaptive calculations for better accuracy. Applications to a linear diffusion system and two nonlinear systems of morphogens demonstrate the effectiveness and benefits of the new hybrid method. PMID:27703710

Chrestenson transform FPGA embedded factorizations.

PubMed

Corinthios, Michael J

2016-01-01

Chrestenson generalized Walsh transform factorizations for parallel processing imbedded implementations on field programmable gate arrays are presented. This general base transform, sometimes referred to as the Discrete Chrestenson transform, has received special attention in recent years. In fact, the Discrete Fourier transform and Walsh-Hadamard transform are but special cases of the Chrestenson generalized Walsh transform. Rotations of a base-p hypercube, where p is an arbitrary integer, are shown to produce dynamic contention-free memory allocation, in processor architecture. The approach is illustrated by factorizations involving the processing of matrices of the transform which are function of four variables. Parallel operations are implemented matrix multiplications. Each matrix, of dimension N × N, where N = p (n) , n integer, has a structure that depends on a variable parameter k that denotes the iteration number in the factorization process. The level of parallelism, in the form of M = p (m) processors can be chosen arbitrarily by varying m between zero to its maximum value of n - 1. The result is an equation describing the generalised parallelism factorization as a function of the four variables n, p, k and m. Applications of the approach are shown in relation to configuring field programmable gate arrays for digital signal processing applications.

Hybrid modeling in biochemical systems theory by means of functional petri nets.

PubMed

Wu, Jialiang; Voit, Eberhard

2009-02-01

Many biological systems are genuinely hybrids consisting of interacting discrete and continuous components and processes that often operate at different time scales. It is therefore desirable to create modeling frameworks capable of combining differently structured processes and permitting their analysis over multiple time horizons. During the past 40 years, Biochemical Systems Theory (BST) has been a very successful approach to elucidating metabolic, gene regulatory, and signaling systems. However, its foundation in ordinary differential equations has precluded BST from directly addressing problems containing switches, delays, and stochastic effects. In this study, we extend BST to hybrid modeling within the framework of Hybrid Functional Petri Nets (HFPN). First, we show how the canonical GMA and S-system models in BST can be directly implemented in a standard Petri Net framework. In a second step we demonstrate how to account for different types of time delays as well as for discrete, stochastic, and switching effects. Using representative test cases, we validate the hybrid modeling approach through comparative analyses and simulations with other approaches and highlight the feasibility, quality, and efficiency of the hybrid method.

The discrete Fourier transform algorithm for determining decay constants—Implementation using a field programmable gate array

NASA Astrophysics Data System (ADS)

Bostrom, G.; Atkinson, D.; Rice, A.

2015-04-01

Cavity ringdown spectroscopy (CRDS) uses the exponential decay constant of light exiting a high-finesse resonance cavity to determine analyte concentration, typically via absorption. We present a high-throughput data acquisition system that determines the decay constant in near real time using the discrete Fourier transform algorithm on a field programmable gate array (FPGA). A commercially available, high-speed, high-resolution, analog-to-digital converter evaluation board system is used as the platform for the system, after minor hardware and software modifications. The system outputs decay constants at maximum rate of 4.4 kHz using an 8192-point fast Fourier transform by processing the intensity decay signal between ringdown events. We present the details of the system, including the modifications required to adapt the evaluation board to accurately process the exponential waveform. We also demonstrate the performance of the system, both stand-alone and incorporated into our existing CRDS system. Details of FPGA, microcontroller, and circuitry modifications are provided in the Appendix and computer code is available upon request from the authors.

Multiqubit Clifford groups are unitary 3-designs

NASA Astrophysics Data System (ADS)

Zhu, Huangjun

2017-12-01

Unitary t -designs are a ubiquitous tool in many research areas, including randomized benchmarking, quantum process tomography, and scrambling. Despite the intensive efforts of many researchers, little is known about unitary t -designs with t ≥3 in the literature. We show that the multiqubit Clifford group in any even prime-power dimension is not only a unitary 2-design, but also a 3-design. Moreover, it is a minimal 3-design except for dimension 4. As an immediate consequence, any orbit of pure states of the multiqubit Clifford group forms a complex projective 3-design; in particular, the set of stabilizer states forms a 3-design. In addition, our study is helpful in studying higher moments of the Clifford group, which are useful in many research areas ranging from quantum information science to signal processing. Furthermore, we reveal a surprising connection between unitary 3-designs and the physics of discrete phase spaces and thereby offer a simple explanation of why no discrete Wigner function is covariant with respect to the multiqubit Clifford group, which is of intrinsic interest in studying quantum computation.

DISCRETE COMPOUND POISSON PROCESSES AND TABLES OF THE GEOMETRIC POISSON DISTRIBUTION.

DTIC Science & Technology

A concise summary of the salient properties of discrete Poisson processes , with emphasis on comparing the geometric and logarithmic Poisson processes . The...the geometric Poisson process are given for 176 sets of parameter values. New discrete compound Poisson processes are also introduced. These...processes have properties that are particularly relevant when the summation of several different Poisson processes is to be analyzed. This study provides the

Unconditional security proof of long-distance continuous-variable quantum key distribution with discrete modulation.

PubMed

Leverrier, Anthony; Grangier, Philippe

2009-05-08

We present a continuous-variable quantum key distribution protocol combining a discrete modulation and reverse reconciliation. This protocol is proven unconditionally secure and allows the distribution of secret keys over long distances, thanks to a reverse reconciliation scheme efficient at very low signal-to-noise ratio.

Coding for Single-Line Transmission

NASA Technical Reports Server (NTRS)

Madison, L. G.

1983-01-01

Digital transmission code combines data and clock signals into single waveform. MADCODE needs four standard integrated circuits in generator and converter plus five small discrete components. MADCODE allows simple coding and decoding for transmission of digital signals over single line.

A Robust Zero-Watermarking Algorithm for Audio

NASA Astrophysics Data System (ADS)

Chen, Ning; Zhu, Jie

2007-12-01

In traditional watermarking algorithms, the insertion of watermark into the host signal inevitably introduces some perceptible quality degradation. Another problem is the inherent conflict between imperceptibility and robustness. Zero-watermarking technique can solve these problems successfully. Instead of embedding watermark, the zero-watermarking technique extracts some essential characteristics from the host signal and uses them for watermark detection. However, most of the available zero-watermarking schemes are designed for still image and their robustness is not satisfactory. In this paper, an efficient and robust zero-watermarking technique for audio signal is presented. The multiresolution characteristic of discrete wavelet transform (DWT), the energy compression characteristic of discrete cosine transform (DCT), and the Gaussian noise suppression property of higher-order cumulant are combined to extract essential features from the host audio signal and they are then used for watermark recovery. Simulation results demonstrate the effectiveness of our scheme in terms of inaudibility, detection reliability, and robustness.

Detecting dynamical changes in time series by using the Jensen Shannon divergence

NASA Astrophysics Data System (ADS)

Mateos, D. M.; Riveaud, L. E.; Lamberti, P. W.

2017-08-01

Most of the time series in nature are a mixture of signals with deterministic and random dynamics. Thus the distinction between these two characteristics becomes important. Distinguishing between chaotic and aleatory signals is difficult because they have a common wide band power spectrum, a delta like autocorrelation function, and share other features as well. In general, signals are presented as continuous records and require to be discretized for being analyzed. In this work, we introduce different schemes for discretizing and for detecting dynamical changes in time series. One of the main motivations is to detect transitions between the chaotic and random regime. The tools here used here originate from the Information Theory. The schemes proposed are applied to simulated and real life signals, showing in all cases a high proficiency for detecting changes in the dynamics of the associated time series.

Enhancing Three-dimensional Movement Control System for Assemblies of Machine-Building Facilities

NASA Astrophysics Data System (ADS)

Kuzyakov, O. N.; Andreeva, M. A.

2018-01-01

Aspects of enhancing three-dimensional movement control system are given in the paper. Such system is to be used while controlling assemblies of machine-building facilities, which is a relevant issue. The base of the system known is three-dimensional movement control device with optical principle of action. The device consists of multi point light emitter and light receiver matrix. The processing of signals is enhanced to increase accuracy of measurements by switching from discrete to analog signals. Light receiver matrix is divided into four areas, and the output value of each light emitter in each matrix area is proportional to its luminance level. Thus, determing output electric signal value of each light emitter in corresponding area leads to determing position of multipoint light emitter and position of object tracked. This is done by using Case-based reasoning method, the precedent in which is described as integral signal value of each matrix area, coordinates of light receivers, which luminance level is high, and decision to be made in this situation.

Normative evidence accumulation in unpredictable environments

PubMed Central

Glaze, Christopher M; Kable, Joseph W; Gold, Joshua I

2015-01-01

In our dynamic world, decisions about noisy stimuli can require temporal accumulation of evidence to identify steady signals, differentiation to detect unpredictable changes in those signals, or both. Normative models can account for learning in these environments but have not yet been applied to faster decision processes. We present a novel, normative formulation of adaptive learning models that forms decisions by acting as a leaky accumulator with non-absorbing bounds. These dynamics, derived for both discrete and continuous cases, depend on the expected rate of change of the statistics of the evidence and balance signal identification and change detection. We found that, for two different tasks, human subjects learned these expectations, albeit imperfectly, then used them to make decisions in accordance with the normative model. The results represent a unified, empirically supported account of decision-making in unpredictable environments that provides new insights into the expectation-driven dynamics of the underlying neural signals. DOI: http://dx.doi.org/10.7554/eLife.08825.001 PMID:26322383

Modeling the Atmospheric Phase Effects of a Digital Antenna Array Communications System

NASA Technical Reports Server (NTRS)

Tkacenko, A.

2006-01-01

In an antenna array system such as that used in the Deep Space Network (DSN) for satellite communication, it is often necessary to account for the effects due to the atmosphere. Typically, the atmosphere induces amplitude and phase fluctuations on the transmitted downlink signal that invalidate the assumed stationarity of the signal model. The degree to which these perturbations affect the stationarity of the model depends both on parameters of the atmosphere, including wind speed and turbulence strength, and on parameters of the communication system, such as the sampling rate used. In this article, we focus on modeling the atmospheric phase fluctuations in a digital antenna array communications system. Based on a continuous-time statistical model for the atmospheric phase effects, we show how to obtain a related discrete-time model based on sampling the continuous-time process. The effects of the nonstationarity of the resulting signal model are investigated using the sample matrix inversion (SMI) algorithm for minimum mean-squared error (MMSE) equalization of the received signal

Active elimination of radio frequency interference for improved signal-to-noise ratio for in-situ NMR experiments in strong magnetic field gradients

NASA Astrophysics Data System (ADS)

Ibrahim, M.; Pardi, C. I.; Brown, T. W. C.; McDonald, P. J.

2018-02-01

Improvement in the signal-to-noise ratio of Nuclear Magnetic Resonance (NMR) systems may be achieved either by increasing the signal amplitude or by decreasing the noise. The noise has multiple origins - not all of which are strictly "noise": incoherent thermal noise originating in the probe and pre-amplifiers, probe ring down or acoustic noise and coherent externally broadcast radio frequency transmissions. The last cannot always be shielded in open access experiments. In this paper, we show that pulsed, low radio-frequency data communications are a significant source of broadcast interference. We explore two signal processing methods of de-noising short T2∗ NMR experiments corrupted by these communications: Linear Predictive Coding (LPC) and the Discrete Wavelet Transform (DWT). Results are shown for numerical simulations and experiments conducted under controlled conditions with pseudo radio frequency interference. We show that both the LPC and DWT methods have merit.

Effect of TE Mode Power on the PEP II LER BPM System

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

Ng, Cho-K

2011-08-26

The beam chamber of the PEP-II B-Factory Low Energy Ring (LER) arc sections is connected to an antechamber for the absorption of synchrotron radiation on discrete photon stops. The presence of the antechamber substantially reduces the cutoff frequency of the vacuum chamber and, in particular, allows the propagation of higher-order-mode (HOM) TE power generated by beamline components at the BPM signal processing frequency. Calculations of the transmission properties of the TE mode in different sections of the vacuum chamber show that the power is trapped between widely separated bellows in the arc sections. Because of the narrow signal bandwidth andmore » weak coupling of the TE mode to the BPM buttons, the noise contributed by the HOM TE power will not produce a noticeable effect on the BPM position signal voltage. The LER arc vacuum chamber employs an antechamber with a discrete photon stop for absorption of synchrotron radiation and with pumps for maintaining pressure below 10 nTorr [1]. The horizontal dimensions of the antechambers at the pumping chamber section and the magnet chamber section are larger or comparable to that of the beam chamber. Because of the increase in the horizontal dimension, the cutoff frequency of the TE10-like mode (in rectangular coordinates) of the vacuum chamber is considerably reduced and, in particular, is less than the BPM signal processing frequency at 952 MHz. TE power propagating in the vacuum chamber will penetrate through the BPM buttons and will affect the pickup signal if its magnitude is not properly controlled. It is the purpose of this note to clarify various issues pertaining to this problem. TE power is generated when the beam passes a noncylindrically symmetric beamline component such as the RF cavity, the injection region, the IR crotch and the IP region. The beampipes connected to these components have TE cutoff frequencies greater than 952 MHz (for example, the TE cutoff frequency of the RF cavity beampipe is 1.8 GHz), and hence no TE power at this frequency propagates from the component. TE power can also be generated by the scattering of TM power through these beamline components. Since the cutoff frequency of the TM mode is in general higher than that of the TE mode, this mechanism is not pertinent to the problem related to the BPM signal. Consequently, the TE power that needs to be considered is mainly generated by components of the LER arc vacuum chamber, where the TE cutoff frequency is less than the BPM processing frequency.« less

Discretization in time gives rise to noise-induced improvement of the signal-to-noise ratio in static nonlinearities.

PubMed

Davidović, A; Huntington, E H; Frater, M R

2009-07-01

For some nonlinear systems the performance can improve with an increasing noise level. Such noise-induced improvement in static nonlinearities is of great interest for practical applications since many systems can be modeled in that way (e.g., sensors, quantizers, limiters, etc.). We present experimental evidence that noise-induced performance improvement occurs in those systems as a consequence of discretization in time with the achievable signal-to-noise ratio (SNR) gain increasing with decreasing ratio of input noise bandwidth and total measurement bandwidth. By modifying the input noise bandwidth, noise-induced improvement with SNR gain larger than unity is demonstrated in a system where it was not previously thought possible. Our experimental results bring closer two different theoretical models for the same class of nonlinearities and shed light on the behavior of static nonlinear discrete-time systems.

Fuzzy Adaptive Control Design and Discretization for a Class of Nonlinear Uncertain Systems.

PubMed

Zhao, Xudong; Shi, Peng; Zheng, Xiaolong

2016-06-01

In this paper, tracking control problems are investigated for a class of uncertain nonlinear systems in lower triangular form. First, a state-feedback controller is designed by using adaptive backstepping technique and the universal approximation ability of fuzzy logic systems. During the design procedure, a developed method with less computation is proposed by constructing one maximum adaptive parameter. Furthermore, adaptive controllers with nonsymmetric dead-zone are also designed for the systems. Then, a sampled-data control scheme is presented to discretize the obtained continuous-time controller by using the forward Euler method. It is shown that both proposed continuous and discrete controllers can ensure that the system output tracks the target signal with a small bounded error and the other closed-loop signals remain bounded. Two simulation examples are presented to verify the effectiveness and applicability of the proposed new design techniques.

Multi-channel temperature measurement amplification system. [solar heating systems

NASA Technical Reports Server (NTRS)

Currie, J. R. (Inventor)

1981-01-01

A number of differential outputs of thermocouples are sequentially amplified by a common amplifier. The amplified outputs are compared with a reference temperature signal in an offset correction amplifier, and a particularly poled output signal is provided when a differential output is of a discrete level compared with a reference temperature signal.

Multi-Velocity Component LDV

NASA Technical Reports Server (NTRS)

Johnson, Dennis A. (Inventor)

1996-01-01

A laser doppler velocimeter uses frequency shifting of a laser beam to provide signal information for each velocity component. A composite electrical signal generated by a light detector is digitized and a processor produces a discrete Fourier transform based on the digitized electrical signal. The transform includes two peak frequencies corresponding to the two velocity components.

Full-wave modeling of the time domain reflectometry signal in wetted sandy soils using a random microstructure discretization: Comparison with experiments

NASA Astrophysics Data System (ADS)

Rejiba, F.; Sagnard, F.; Schamper, C.

2011-07-01

Time domain reflectometry (TDR) is a proven, nondestructive method for the measurement of the permittivity and electrical conductivity of soils, using electromagnetic (EM) waves. Standard interpretation of TDR data leads to the estimation of the soil's equivalent electromagnetic properties since the wavelengths associated with the source signal are considerably greater than the microstructure of the soil. The aforementioned approximation tends to hide an important issue: the influence of the microstructure and phase configuration in the generation of a polarized electric field, which is complicated because of the presence of numerous length scales. In this paper, the influence of the microstructural distribution of each phase on the TDR signal has been studied. We propose a two-step EM modeling technique at a microscale range (?): first, we define an equivalent grain including a thin shell of free water, and second, we solve Maxwell's equations over the discretized, statistically distributed triphasic porous medium. Modeling of the TDR probe with the soil sample was performed using a three-dimensional finite difference time domain scheme. The effectiveness of this hybrid homogenization approach is tested on unsaturated Nemours sand with narrow granulometric fractions. The comparisons made between numerical and experimental results are promising, despite significant assumptions concerning (1) the TDR probe head and the coaxial cable and (2) the assumed effective medium theory homogenization associated with the electromagnetic processes arising locally between the liquid and solid phases at the grain scale.

Simultaneous storage of medical images in the spatial and frequency domain: a comparative study.

PubMed

Nayak, Jagadish; Bhat, P Subbanna; Acharya U, Rajendra; Uc, Niranjan

2004-06-05

Digital watermarking is a technique of hiding specific identification data for copyright authentication. This technique is adapted here for interleaving patient information with medical images, to reduce storage and transmission overheads. The patient information is encrypted before interleaving with images to ensure greater security. The bio-signals are compressed and subsequently interleaved with the image. This interleaving is carried out in the spatial domain and Frequency domain. The performance of interleaving in the spatial, Discrete Fourier Transform (DFT), Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) coefficients is studied. Differential pulse code modulation (DPCM) is employed for data compression as well as encryption and results are tabulated for a specific example. It can be seen from results, the process does not affect the picture quality. This is attributed to the fact that the change in LSB of a pixel changes its brightness by 1 part in 256. Spatial and DFT domain interleaving gave very less %NRMSE as compared to DCT and DWT domain. The Results show that spatial domain the interleaving, the %NRMSE was less than 0.25% for 8-bit encoded pixel intensity. Among the frequency domain interleaving methods, DFT was found to be very efficient.

Features of control systems analysis with discrete control devices using mathematical packages

NASA Astrophysics Data System (ADS)

Yakovleva, E. M.; Faerman, V. A.

2017-02-01

The article contains presentation of basic provisions of the theory of automatic pulse control systems as well as methods of analysis of such systems using the mathematical software widespread in the academic environment. The pulse systems under research are considered as analogues systems interacting among themselves, including sensors, amplifiers, controlled objects, and discrete parts. To describe such systems, one uses a mathematical apparatus of difference equations as well as discrete transfer functions. To obtain a transfer function of the open-loop system, being important from the point of view of the analysis of control systems, one uses mathematical packages Mathcad and Matlab. Despite identity of the obtained result, the way of its achievement from the point of view of user’s action is various for the specified means. In particular, Matlab uses a structural model of the control system while Mathcad allows only execution of a chain of operator transforms. It is worth noting that distinctions taking place allow considering transformation of signals during interaction of the linear and continuous parts of the control system from different sides. The latter can be used in an educational process for the best assimilation of the course of the control system theory by students.

Advanced Engine Health Management Applications of the SSME Real-Time Vibration Monitoring System

NASA Technical Reports Server (NTRS)

Fiorucci, Tony R.; Lakin, David R., II; Reynolds, Tracy D.; Turner, James E. (Technical Monitor)

2000-01-01

The Real Time Vibration Monitoring System (RTVMS) is a 32-channel high speed vibration data acquisition and processing system developed at Marshall Space Flight Center (MSFC). It Delivers sample rates as high as 51,200 samples/second per channel and performs Fast Fourier Transform (FFT) processing via on-board digital signal processing (DSP) chips in a real-time format. Advanced engine health assessment is achieved by utilizing the vibration spectra to provide accurate sensor validation and enhanced engine vibration redlines. Discrete spectral signatures (such as synchronous) that are indicators of imminent failure can be assessed and utilized to mitigate catastrophic engine failures- a first in rocket engine health assessment. This paper is presented in viewgraph form.

Multi-exponential analysis of magnitude MR images using a quantitative multispectral edge-preserving filter.

PubMed

Bonny, Jean Marie; Boespflug-Tanguly, Odile; Zanca, Michel; Renou, Jean Pierre

2003-03-01

A solution for discrete multi-exponential analysis of T(2) relaxation decay curves obtained in current multi-echo imaging protocol conditions is described. We propose a preprocessing step to improve the signal-to-noise ratio and thus lower the signal-to-noise ratio threshold from which a high percentage of true multi-exponential detection is detected. It consists of a multispectral nonlinear edge-preserving filter that takes into account the signal-dependent Rician distribution of noise affecting magnitude MR images. Discrete multi-exponential decomposition, which requires no a priori knowledge, is performed by a non-linear least-squares procedure initialized with estimates obtained from a total least-squares linear prediction algorithm. This approach was validated and optimized experimentally on simulated data sets of normal human brains.

Orbital-angular-momentum mode-group multiplexed transmission over a graded-index ring-core fiber based on receive diversity and maximal ratio combining

NASA Astrophysics Data System (ADS)

Zhang, Junwei; Zhu, Guoxuan; Liu, Jie; Wu, Xiong; Zhu, Jiangbo; Du, Cheng; Luo, Wenyong; Chen, Yujie; Yu, Siyuan

2018-02-01

An orbital-angular-momentum (OAM) mode-group multiplexing (MGM) scheme based on a graded-index ring-core fiber (GIRCF) is proposed, in which a single-input two-output (or receive diversity) architecture is designed for each MG channel and simple digital signal processing (DSP) is utilized to adaptively resist the mode partition noise resulting from random intra-group mode crosstalk. There is no need of complex multiple-input multiple-output (MIMO) equalization in this scheme. Furthermore, the signal-to-noise ratio (SNR) of the received signals can be improved if a simple maximal ratio combining (MRC) technique is employed on the receiver side to efficiently take advantage of the diversity gain of receiver. Intensity-modulated direct-detection (IM-DD) systems transmitting three OAM mode groups with total 100-Gb/s discrete multi-tone (DMT) signals over a 1-km GIRCF and two OAM mode groups with total 40-Gb/s DMT signals over an 18-km GIRCF are experimentally demonstrated, respectively, to confirm the feasibility of our proposed OAM-MGM scheme.

Initial Evaluation of Signal-Based Bayesian Monitoring

NASA Astrophysics Data System (ADS)

Moore, D.; Russell, S.

2016-12-01

We present SIGVISA (Signal-based Vertically Integrated Seismic Analysis), a next-generation system for global seismic monitoring through Bayesian inference on seismic signals. Traditional seismic monitoring systems rely on discrete detections produced by station processing software, discarding significant information present in the original recorded signal. By modeling signals directly, our forward model is able to incorporate a rich representation of the physics underlying the signal generation process, including source mechanisms, wave propagation, and station response. This allows inference in the model to recover the qualitative behavior of geophysical methods including waveform matching and double-differencing, all as part of a unified Bayesian monitoring system that simultaneously detects and locates events from a network of stations. We report results from an evaluation of SIGVISA monitoring the western United States for a two-week period following the magnitude 6.0 event in Wells, NV in February 2008. During this period, SIGVISA detects more than twice as many events as NETVISA, and three times as many as SEL3, while operating at the same precision; at lower precisions it detects up to five times as many events as SEL3. At the same time, signal-based monitoring reduces mean location errors by a factor of four relative to detection-based systems. We provide evidence that, given only IMS data, SIGVISA detects events that are missed by regional monitoring networks, indicating that our evaluations may even underestimate its performance. Finally, SIGVISA matches or exceeds the detection rates of existing systems for de novo events - events with no nearby historical seismicity - and detects through automated processing a number of such events missed even by the human analysts generating the LEB.

Implementation of Adaptive Digital Controllers on Programmable Logic Devices

NASA Technical Reports Server (NTRS)

Gwaltney, David A.; King, Kenneth D.; Smith, Keary J.; Montenegro, Justino (Technical Monitor)

2002-01-01

Much has been made of the capabilities of Field Programmable Gate Arrays (FPGA's) in the hardware implementation of fast digital signal processing functions. Such capability also makes an FPGA a suitable platform for the digital implementation of closed loop controllers. Other researchers have implemented a variety of closed-loop digital controllers on FPGA's. Some of these controllers include the widely used Proportional-Integral-Derivative (PID) controller, state space controllers, neural network and fuzzy logic based controllers. There are myriad advantages to utilizing an FPGA for discrete-time control functions which include the capability for reconfiguration when SRAM- based FPGA's are employed, fast parallel implementation of multiple control loops and implementations that can meet space level radiation tolerance requirements in a compact form-factor. Generally, a software implementation on a Digital Signal Processor (DSP) device or microcontroller is used to implement digital controllers. At Marshall Space Flight Center, the Control Electronics Group has been studying adaptive discrete-time control of motor driven actuator systems using DSP devices. While small form factor, commercial DSP devices are now available with event capture, data conversion, Pulse Width Modulated (PWM) outputs and communication peripherals, these devices are not currently available in designs and packages which meet space level radiation requirements. In general, very few DSP devices are produced that are designed to meet any level of radiation tolerance or hardness. An alternative is required for compact implementation of such functionality to withstand the harsh environment encountered on spacemap. The goal of this effort is to create a fully digital, flight ready controller design that utilizes an FPGA for implementation of signal conditioning for control feedback signals, generation of commands to the controlled system, and hardware insertion of adaptive-control algorithm approaches. Radiation tolerant FPGA's are a feasible option for reaching this goal.

Improving surface EMG burst detection in infrahyoid muscles during swallowing using digital filters and discrete wavelet analysis.

PubMed

Restrepo-Agudelo, Sebastian; Roldan-Vasco, Sebastian; Ramirez-Arbelaez, Lina; Cadavid-Arboleda, Santiago; Perez-Giraldo, Estefania; Orozco-Duque, Andres

2017-08-01

The visual inspection is a widely used method for evaluating the surface electromyographic signal (sEMG) during deglutition, a process highly dependent of the examiners expertise. It is desirable to have a less subjective and automated technique to improve the onset detection in swallowing related muscles, which have a low signal-to-noise ratio. In this work, we acquired sEMG measured in infrahyoid muscles with high baseline noise of ten healthy adults during water swallowing tasks. Two methods were applied to find the combination of cutoff frequencies that achieve the most accurate onset detection: discrete wavelet decomposition based method and fixed steps variations of low and high cutoff frequencies of a digital bandpass filter. Teager-Kaiser Energy operator, root mean square and simple threshold method were applied for both techniques. Results show a narrowing of the effective bandwidth vs. the literature recommended parameters for sEMG acquisition. Both level 3 decomposition with mother wavelet db4 and bandpass filter with cutoff frequencies between 130 and 180Hz were optimal for onset detection in infrahyoid muscles. The proposed methodologies recognized the onset time with predictive power above 0.95, that is similar to previous findings but in larger and more superficial muscles in limbs. Copyright © 2017 Elsevier Ltd. All rights reserved.

Random Telegraph Signal Amplitudes in Sub 100 nm (Decanano) MOSFETs: A 3D 'Atomistic' Simulation Study

NASA Technical Reports Server (NTRS)

Asenov, Asen; Balasubramaniam, R.; Brown, A. R.; Davies, J. H.; Saini, Subhash

2000-01-01

In this paper we use 3D simulations to study the amplitudes of random telegraph signals (RTS) associated with the trapping of a single carrier in interface states in the channel of sub 100 nm (decanano) MOSFETs. Both simulations using continuous doping charge and random discrete dopants in the active region of the MOSFETs are presented. We have studied the dependence of the RTS amplitudes on the position of the trapped charge in the channel and on the device design parameters. We have observed a significant increase in the maximum RTS amplitude when discrete random dopants are employed in the simulations.

Advanced technology for a satellite multichannel demultiplexer/demodulator

NASA Technical Reports Server (NTRS)

Abramovitz, Irwin J.; Flechsig, Drew E.; Matteis, Richard M., Jr.

1994-01-01

Satellite on-board processing is needed to efficiently service multiple users while at the same time minimizing earth station complexity. The processing satellite receives a wideband uplink at 30 GHz and down-converts it to a suitable intermediate frequency. A multichannel demultiplexer then separates the composite signal into discrete channels. Each channel is then demodulated by bulk demodulators, with the baseband signals routed to the downlink processor for retransmission to the receiving earth stations. This type of processing circumvents many of the difficulties associated with traditional bent-pipe repeater satellites. Uplink signal distortion and interference are not retransmitted on the downlink. Downlink power can be allocated in accordance with user needs, independent of uplink transmissions. This allows the uplink users to employ different data rates as well as different modulation and coding schemes. In addition, all downlink users have a common frequency standard and symbol clock on the satellite, which is useful for network synchronization in time division multiple access schemes. The purpose of this program is to demonstrate the concept of an optically implemented multichannel demultiplexer (MCD). A proof-of-concept (POC) model has been developed which has the ability to receive a 40 MHz wide composite signal consisting of up to 1000 40 kHz QPSK modulated channels and perform the demultiplexing process. In addition a set of special test equipment (STE) has been configured to evaluate the performance of the POC model. The optical MCD is realized as an acousto-optic spectrum analyzer utilizing the capability of Bragg cells to perform the required channelization. These Bragg cells receive an optical input from a laser source and an RF input (the signal). The Bragg interaction causes optical output diffractions at angles proportional to the RF input frequency. These discrete diffractions are optically detected and output to individual demodulators for baseband conversion. Optimization of the MCD design was conducted in order to achieve a compromise between two opposing sources of signal degradation: adjacent channel interference and intersymbol interference. The system was also optimized to allow simple, inexpensive ground stations communications with the MCD. These design goals led to the realization of a POC MCD which demonstrates the demultiplexing function with minimal signal degradation. Performance evaluation results using the STE equipment indicate that the dynamic range of the demultiplexer in the presence of adjacent and multiple channel loading is 40 - 50 dB. Measured bit error rate (BER) probabilities varied from the predicted theoretical results by one dB or less. The performance of the proof-of-concept model indicate that the development of a space qualified optically implemented MCD are feasible. The advantages to such an implementation include reduced size, weight and power and increased reliability when compared with electronic approaches. All of these factors are critical to on-board satellite processors. Further optimization can be conducted which trade ground station complexity and MCD performance to achieve desired system results.

A comparison of orthogonal transformations for digital speech processing.

NASA Technical Reports Server (NTRS)

Campanella, S. J.; Robinson, G. S.

1971-01-01

Discrete forms of the Fourier, Hadamard, and Karhunen-Loeve transforms are examined for their capacity to reduce the bit rate necessary to transmit speech signals. To rate their effectiveness in accomplishing this goal the quantizing error (or noise) resulting for each transformation method at various bit rates is computed and compared with that for conventional companded PCM processing. Based on this comparison, it is found that Karhunen-Loeve provides a reduction in bit rate of 13.5 kbits/s, Fourier 10 kbits/s, and Hadamard 7.5 kbits/s as compared with the bit rate required for companded PCM. These bit-rate reductions are shown to be somewhat independent of the transmission bit rate.

Slush hydrogen liquid level system

NASA Technical Reports Server (NTRS)

Hamlet, J. F.; Adams, R. G.

1972-01-01

A discrete capacitance liquid level system developed is specifically for slush hydrogen, but applicable to LOX, LN2, LH2, and RP1 without modification is described. The signal processing portion of the system is compatible with conventional liquid level sensors. Compatibility with slush hydrogen was achieved by designing the sensor with adequate spacing, while retaining the electrical characteristics of conventional sensors. Tests indicate excellent stability of the system over a temperature range of -20 C to 70 C for the circuit and to cryogenic temperatures of the sensor. The sensor was tested up to 40 g's rms random vibration with no damage to the sensor. Operation with 305 m of cable between the sensor and signal processor was demonstrated. It is concluded that this design is more than adequate for most flight and ground applications.

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

Bakhtiari, S.; Liao, S.; Elmer, T.

This paper analyzes heart rate (HR) information from physiological tracings collected with a remote millimeter wave (mmW) I-Q sensor for biometric monitoring applications. A parameter optimization method based on the nonlinear Levenberg-Marquardt algorithm is used. The mmW sensor works at 94 GHz and can detect the vital signs of a human subject from a few to tens of meters away. The reflected mmW signal is typically affected by respiration, body movement, background noise, and electronic system noise. Processing of the mmW radar signal is, thus, necessary to obtain the true HR. The down-converted received signal in this case consists ofmore » both the real part (I-branch) and the imaginary part (Q-branch), which can be considered as the cosine and sine of the received phase of the HR signal. Instead of fitting the converted phase angle signal, the method directly fits the real and imaginary parts of the HR signal, which circumvents the need for phase unwrapping. This is particularly useful when the SNR is low. Also, the method identifies both beat-to-beat HR and individual heartbeat magnitude, which is valuable for some medical diagnosis applications. The mean HR here is compared to that obtained using the discrete Fourier transform.« less

Wavelet-Based Signal and Image Processing for Target Recognition

NASA Astrophysics Data System (ADS)

Sherlock, Barry G.

2002-11-01

The PI visited NSWC Dahlgren, VA, for six weeks in May-June 2002 and collaborated with scientists in the G33 TEAMS facility, and with Marilyn Rudzinsky of T44 Technology and Photonic Systems Branch. During this visit the PI also presented six educational seminars to NSWC scientists on various aspects of signal processing. Several items from the grant proposal were completed, including (1) wavelet-based algorithms for interpolation of 1-d signals and 2-d images; (2) Discrete Wavelet Transform domain based algorithms for filtering of image data; (3) wavelet-based smoothing of image sequence data originally obtained for the CRITTIR (Clutter Rejection Involving Temporal Techniques in the Infra-Red) project. The PI visited the University of Stellenbosch, South Africa to collaborate with colleagues Prof. B.M. Herbst and Prof. J. du Preez on the use of wavelet image processing in conjunction with pattern recognition techniques. The University of Stellenbosch has offered the PI partial funding to support a sabbatical visit in Fall 2003, the primary purpose of which is to enable the PI to develop and enhance his expertise in Pattern Recognition. During the first year, the grant supported publication of 3 referred papers, presentation of 9 seminars and an intensive two-day course on wavelet theory. The grant supported the work of two students who functioned as research assistants.

Rapid prototyping of update algorithm of discrete Fourier transform for real-time signal processing

NASA Astrophysics Data System (ADS)

Kakad, Yogendra P.; Sherlock, Barry G.; Chatapuram, Krishnan V.; Bishop, Stephen

2001-10-01

An algorithm is developed in the companion paper, to update the existing DFT to represent the new data series that results when a new signal point is received. Updating the DFT in this way uses less computation than directly evaluating the DFT using the FFT algorithm, This reduces the computational order by a factor of log2 N. The algorithm is able to work in the presence of data window function, for use with rectangular window, the split triangular, Hanning, Hamming, and Blackman windows. In this paper, a hardware implementation of this algorithm, using FPGA technology, is outlined. Unlike traditional fully customized VLSI circuits, FPGAs represent a technical break through in the corresponding industry. The FPGA implements thousands of gates of logic in a single IC chip and it can be programmed by users at their site in a few seconds or less depending on the type of device used. The risk is low and the development time is short. The advantages have made FPGAs very popular for rapid prototyping of algorithms in the area of digital communication, digital signal processing, and image processing. Our paper addresses the related issues of implementation using hardware descriptive language in the development of the design and the subsequent downloading on the programmable hardware chip.

Discretized Streams: A Fault-Tolerant Model for Scalable Stream Processing

DTIC Science & Technology

2012-12-14

Discretized Streams: A Fault-Tolerant Model for Scalable Stream Processing Matei Zaharia Tathagata Das Haoyuan Li Timothy Hunter Scott Shenker Ion...SUBTITLE Discretized Streams: A Fault-Tolerant Model for Scalable Stream Processing 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER...time. However, current programming models for distributed stream processing are relatively low-level often leaving the user to worry about consistency of

FPGA-based smart sensor for drought stress detection in tomato plants using novel physiological variables and discrete wavelet transform.

PubMed

Duarte-Galvan, Carlos; Romero-Troncoso, Rene de J; Torres-Pacheco, Irineo; Guevara-Gonzalez, Ramon G; Fernandez-Jaramillo, Arturo A; Contreras-Medina, Luis M; Carrillo-Serrano, Roberto V; Millan-Almaraz, Jesus R

2014-10-09

Soil drought represents one of the most dangerous stresses for plants. It impacts the yield and quality of crops, and if it remains undetected for a long time, the entire crop could be lost. However, for some plants a certain amount of drought stress improves specific characteristics. In such cases, a device capable of detecting and quantifying the impact of drought stress in plants is desirable. This article focuses on testing if the monitoring of physiological process through a gas exchange methodology provides enough information to detect drought stress conditions in plants. The experiment consists of using a set of smart sensors based on Field Programmable Gate Arrays (FPGAs) to monitor a group of plants under controlled drought conditions. The main objective was to use different digital signal processing techniques such as the Discrete Wavelet Transform (DWT) to explore the response of plant physiological processes to drought. Also, an index-based methodology was utilized to compensate the spatial variation inside the greenhouse. As a result, differences between treatments were determined to be independent of climate variations inside the greenhouse. Finally, after using the DWT as digital filter, results demonstrated that the proposed system is capable to reject high frequency noise and to detect drought conditions.

A High-Performance Neural Prosthesis Incorporating Discrete State Selection With Hidden Markov Models.

PubMed

Kao, Jonathan C; Nuyujukian, Paul; Ryu, Stephen I; Shenoy, Krishna V

2017-04-01

Communication neural prostheses aim to restore efficient communication to people with motor neurological injury or disease by decoding neural activity into control signals. These control signals are both analog (e.g., the velocity of a computer mouse) and discrete (e.g., clicking an icon with a computer mouse) in nature. Effective, high-performing, and intuitive-to-use communication prostheses should be capable of decoding both analog and discrete state variables seamlessly. However, to date, the highest-performing autonomous communication prostheses rely on precise analog decoding and typically do not incorporate high-performance discrete decoding. In this report, we incorporated a hidden Markov model (HMM) into an intracortical communication prosthesis to enable accurate and fast discrete state decoding in parallel with analog decoding. In closed-loop experiments with nonhuman primates implanted with multielectrode arrays, we demonstrate that incorporating an HMM into a neural prosthesis can increase state-of-the-art achieved bitrate by 13.9% and 4.2% in two monkeys ( ). We found that the transition model of the HMM is critical to achieving this performance increase. Further, we found that using an HMM resulted in the highest achieved peak performance we have ever observed for these monkeys, achieving peak bitrates of 6.5, 5.7, and 4.7 bps in Monkeys J, R, and L, respectively. Finally, we found that this neural prosthesis was robustly controllable for the duration of entire experimental sessions. These results demonstrate that high-performance discrete decoding can be beneficially combined with analog decoding to achieve new state-of-the-art levels of performance.

General simulation algorithm for autocorrelated binary processes.

PubMed

Serinaldi, Francesco; Lombardo, Federico

2017-02-01

The apparent ubiquity of binary random processes in physics and many other fields has attracted considerable attention from the modeling community. However, generation of binary sequences with prescribed autocorrelation is a challenging task owing to the discrete nature of the marginal distributions, which makes the application of classical spectral techniques problematic. We show that such methods can effectively be used if we focus on the parent continuous process of beta distributed transition probabilities rather than on the target binary process. This change of paradigm results in a simulation procedure effectively embedding a spectrum-based iterative amplitude-adjusted Fourier transform method devised for continuous processes. The proposed algorithm is fully general, requires minimal assumptions, and can easily simulate binary signals with power-law and exponentially decaying autocorrelation functions corresponding, for instance, to Hurst-Kolmogorov and Markov processes. An application to rainfall intermittency shows that the proposed algorithm can also simulate surrogate data preserving the empirical autocorrelation.

Terahertz imaging devices and systems, and related methods, for detection of materials

DOEpatents

Kotter, Dale K.

2016-11-15

Terahertz imaging devices may comprise a focal plane array including a substrate and a plurality of resonance elements. The plurality of resonance elements may comprise a conductive material coupled to the substrate. Each resonance element of the plurality of resonance elements may be configured to resonate and produce an output signal responsive to incident radiation having a frequency between about a 0.1 THz and 4 THz range. A method of detecting a hazardous material may comprise receiving incident radiation by a focal plane array having a plurality of discrete pixels including a resonance element configured to absorb the incident radiation at a resonant frequency in the THz, generating an output signal from each of the discrete pixels, and determining a presence of a hazardous material by interpreting spectral information from the output signal.

Multi-star processing and gyro filtering for the video inertial pointing system

NASA Technical Reports Server (NTRS)

Murphy, J. P.

1976-01-01

The video inertial pointing (VIP) system is being developed to satisfy the acquisition and pointing requirements of astronomical telescopes. The VIP system uses a single video sensor to provide star position information that can be used to generate three-axis pointing error signals (multi-star processing) and for input to a cathode ray tube (CRT) display of the star field. The pointing error signals are used to update the telescope's gyro stabilization system (gyro filtering). The CRT display facilitates target acquisition and positioning of the telescope by a remote operator. Linearized small angle equations are used for the multistar processing and a consideration of error performance and singularities lead to star pair location restrictions and equation selection criteria. A discrete steady-state Kalman filter which uses the integration of the gyros is developed and analyzed. The filter includes unit time delays representing asynchronous operations of the VIP microprocessor and video sensor. A digital simulation of a typical gyro stabilized gimbal is developed and used to validate the approach to the gyro filtering.

Linear prediction data extrapolation superresolution radar imaging

NASA Astrophysics Data System (ADS)

Zhu, Zhaoda; Ye, Zhenru; Wu, Xiaoqing

1993-05-01

Range resolution and cross-range resolution of range-doppler imaging radars are related to the effective bandwidth of transmitted signal and the angle through which the object rotates relatively to the radar line of sight (RLOS) during the coherent processing time, respectively. In this paper, linear prediction data extrapolation discrete Fourier transform (LPDEDFT) superresolution imaging method is investigated for the purpose of surpassing the limitation imposed by the conventional FFT range-doppler processing and improving the resolution capability of range-doppler imaging radar. The LPDEDFT superresolution imaging method, which is conceptually simple, consists of extrapolating observed data beyond the observation windows by means of linear prediction, and then performing the conventional IDFT of the extrapolated data. The live data of a metalized scale model B-52 aircraft mounted on a rotating platform in a microwave anechoic chamber and a flying Boeing-727 aircraft were processed. It is concluded that, compared to the conventional Fourier method, either higher resolution for the same effective bandwidth of transmitted signals and total rotation angle of the object or equal-quality images from smaller bandwidth and total angle may be obtained by LPDEDFT.

Autogenic geomorphic processes determine the resolution and fidelity of terrestrial paleoclimate records.

PubMed

Foreman, Brady Z; Straub, Kyle M

2017-09-01

Terrestrial paleoclimate records rely on proxies hosted in alluvial strata whose beds are deposited by unsteady and nonlinear geomorphic processes. It is broadly assumed that this renders the resultant time series of terrestrial paleoclimatic variability noisy and incomplete. We evaluate this assumption using a model of oscillating climate and the precise topographic evolution of an experimental alluvial system. We find that geomorphic stochasticity can create aliasing in the time series and spurious climate signals, but these issues are eliminated when the period of climate oscillation is longer than a key time scale of internal dynamics in the geomorphic system. This emergent autogenic geomorphic behavior imparts regularity to deposition and represents a natural discretization interval of the continuous climate signal. We propose that this time scale in nature could be in excess of 10 4 years but would still allow assessments of the rates of climate change at resolutions finer than the existing age model techniques in isolation.

Recurrent mutation of IGF signalling genes and distinct patterns of genomic rearrangement in osteosarcoma

DOE PAGES

Behjati, Sam; Tarpey, Patrick S.; Haase, Kerstin; ...

2017-06-23

Osteosarcoma is a primary malignancy of bone that affects children and adults. Here, we present the largest sequencing study of osteosarcoma to date, comprising 112 childhood and adult tumours encompassing all major histological subtypes. A key finding of our study is the identification of mutations in insulin-like growth factor (IGF) signalling genes in 8/112 (7%) of cases. We validate this observation using fluorescence in situ hybridization (FISH) in an additional 87 osteosarcomas, with IGF1 receptor (IGF1R) amplification observed in 14% of tumours. These findings may inform patient selection in future trials of IGF1R inhibitors in osteosarcoma. Analysing patterns of mutation,more » we identify distinct rearrangement profiles including a process characterized by chromothripsis and amplification. This process operates recurrently at discrete genomic regions and generates driver mutations. Lastly, it may represent an age-independent mutational mechanism that contributes to the development of osteosarcoma in children and adults alike.« less

Applications of rigged Hilbert spaces in quantum mechanics and signal processing

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

Celeghini, E., E-mail: celeghini@fi.infn.it; Departamento de Física Teórica, Atómica y Óptica and IMUVA, Universidad de Valladolid, Paseo Belén 7, 47011 Valladolid; Gadella, M., E-mail: manuelgadella1@gmail.com

Simultaneous use of discrete and continuous bases in quantum systems is not possible in the context of Hilbert spaces, but only in the more general structure of rigged Hilbert spaces (RHS). In addition, the relevant operators in RHS (but not in Hilbert space) are a realization of elements of a Lie enveloping algebra and support representations of semigroups. We explicitly construct here basis dependent RHS of the line and half-line and relate them to the universal enveloping algebras of the Weyl-Heisenberg algebra and su(1, 1), respectively. The complete sub-structure of both RHS and of the operators acting on them ismore » obtained from their algebraic structures or from the related fractional Fourier transforms. This allows us to describe both quantum and signal processing states and their dynamics. Two relevant improvements are introduced: (i) new kinds of filters related to restrictions to subspaces and/or the elimination of high frequency fluctuations and (ii) an operatorial structure that, starting from fix objects, describes their time evolution.« less

Recurrent mutation of IGF signalling genes and distinct patterns of genomic rearrangement in osteosarcoma

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

Behjati, Sam; Tarpey, Patrick S.; Haase, Kerstin

Osteosarcoma is a primary malignancy of bone that affects children and adults. Here, we present the largest sequencing study of osteosarcoma to date, comprising 112 childhood and adult tumours encompassing all major histological subtypes. A key finding of our study is the identification of mutations in insulin-like growth factor (IGF) signalling genes in 8/112 (7%) of cases. We validate this observation using fluorescence in situ hybridization (FISH) in an additional 87 osteosarcomas, with IGF1 receptor (IGF1R) amplification observed in 14% of tumours. These findings may inform patient selection in future trials of IGF1R inhibitors in osteosarcoma. Analysing patterns of mutation,more » we identify distinct rearrangement profiles including a process characterized by chromothripsis and amplification. This process operates recurrently at discrete genomic regions and generates driver mutations. Lastly, it may represent an age-independent mutational mechanism that contributes to the development of osteosarcoma in children and adults alike.« less

Autogenic geomorphic processes determine the resolution and fidelity of terrestrial paleoclimate records

PubMed Central

Foreman, Brady Z.; Straub, Kyle M.

2017-01-01

Terrestrial paleoclimate records rely on proxies hosted in alluvial strata whose beds are deposited by unsteady and nonlinear geomorphic processes. It is broadly assumed that this renders the resultant time series of terrestrial paleoclimatic variability noisy and incomplete. We evaluate this assumption using a model of oscillating climate and the precise topographic evolution of an experimental alluvial system. We find that geomorphic stochasticity can create aliasing in the time series and spurious climate signals, but these issues are eliminated when the period of climate oscillation is longer than a key time scale of internal dynamics in the geomorphic system. This emergent autogenic geomorphic behavior imparts regularity to deposition and represents a natural discretization interval of the continuous climate signal. We propose that this time scale in nature could be in excess of 104 years but would still allow assessments of the rates of climate change at resolutions finer than the existing age model techniques in isolation. PMID:28924607

Design of Discrete Time Radio Receiver for the Demodulation of Power-Separated Co-Channel Satellite Communication Signals

DTIC Science & Technology

2013-09-01

35 2. Signal Rotator .....................................................................................37 1...37 Figure 18. The implementation of a clockwise rotator for phase error correction. ...........39 Figure... rotation by carrier phase/frequency synchronization circuit. .........................................................41 Figure 21. Output of the phase

Multiresolution analysis (discrete wavelet transform) through Daubechies family for emotion recognition in speech.

NASA Astrophysics Data System (ADS)

Campo, D.; Quintero, O. L.; Bastidas, M.

2016-04-01

We propose a study of the mathematical properties of voice as an audio signal. This work includes signals in which the channel conditions are not ideal for emotion recognition. Multiresolution analysis- discrete wavelet transform - was performed through the use of Daubechies Wavelet Family (Db1-Haar, Db6, Db8, Db10) allowing the decomposition of the initial audio signal into sets of coefficients on which a set of features was extracted and analyzed statistically in order to differentiate emotional states. ANNs proved to be a system that allows an appropriate classification of such states. This study shows that the extracted features using wavelet decomposition are enough to analyze and extract emotional content in audio signals presenting a high accuracy rate in classification of emotional states without the need to use other kinds of classical frequency-time features. Accordingly, this paper seeks to characterize mathematically the six basic emotions in humans: boredom, disgust, happiness, anxiety, anger and sadness, also included the neutrality, for a total of seven states to identify.

Efficient algorithm for baseline wander and powerline noise removal from ECG signals based on discrete Fourier series.

PubMed

Bahaz, Mohamed; Benzid, Redha

2018-03-01

Electrocardiogram (ECG) signals are often contaminated with artefacts and noises which can lead to incorrect diagnosis when they are visually inspected by cardiologists. In this paper, the well-known discrete Fourier series (DFS) is re-explored and an efficient DFS-based method is proposed to reduce contribution of both baseline wander (BW) and powerline interference (PLI) noises in ECG records. In the first step, the determination of the exact number of low frequency harmonics contributing in BW is achieved. Next, the baseline drift is estimated by the sum of all associated Fourier sinusoids components. Then, the baseline shift is discarded efficiently by a subtraction of its approximated version from the original biased ECG signal. Concerning the PLI, the subtraction of the contributing harmonics calculated in the same manner reduces efficiently such type of noise. In addition of visual quality results, the proposed algorithm shows superior performance in terms of higher signal-to-noise ratio and smaller mean square error when faced to the DCT-based algorithm.

Passive Seismic Monitoring for Rockfall at Yucca Mountain: Concept Tests

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

Cheng, J; Twilley, K; Murvosh, H

2003-03-03

For the purpose of proof-testing a system intended to remotely monitor rockfall inside a potential radioactive waste repository at Yucca Mountain, a system of seismic sub-arrays will be deployed and tested on the surface of the mountain. The goal is to identify and locate rockfall events remotely using automated data collecting and processing techniques. We install seismometers on the ground surface, generate seismic energy to simulate rockfall in underground space beneath the array, and interpret the surface response to discriminate and locate the event. Data will be analyzed using matched-field processing, a generalized beam forming method for localizing discrete signals.more » Software is being developed to facilitate the processing. To date, a three-component sub-array has been installed and successfully tested.« less

Multiple Facets of cAMP Signalling and Physiological Impact: cAMP Compartmentalization in the Lung

PubMed Central

Oldenburger, Anouk; Maarsingh, Harm; Schmidt, Martina

2012-01-01

Therapies involving elevation of the endogenous suppressor cyclic AMP (cAMP) are currently used in the treatment of several chronic inflammatory disorders, including chronic obstructive pulmonary disease (COPD). Characteristics of COPD are airway obstruction, airway inflammation and airway remodelling, processes encompassed by increased airway smooth muscle mass, epithelial changes, goblet cell and submucosal gland hyperplasia. In addition to inflammatory cells, airway smooth muscle cells and (myo)fibroblasts, epithelial cells underpin a variety of key responses in the airways such as inflammatory cytokine release, airway remodelling, mucus hypersecretion and airway barrier function. Cigarette smoke, being next to environmental pollution the main cause of COPD, is believed to cause epithelial hyperpermeability by disrupting the barrier function. Here we will focus on the most recent progress on compartmentalized signalling by cAMP. In addition to G protein-coupled receptors, adenylyl cyclases, cAMP-specific phospho-diesterases (PDEs) maintain compartmentalized cAMP signalling. Intriguingly, spatially discrete cAMP-sensing signalling complexes seem also to involve distinct members of the A-kinase anchoring (AKAP) superfamily and IQ motif containing GTPase activating protein (IQGAPs). In this review, we will highlight the interaction between cAMP and the epithelial barrier to retain proper lung function and to alleviate COPD symptoms and focus on the possible molecular mechanisms involved in this process. Future studies should include the development of cAMP-sensing multiprotein complex specific disruptors and/or stabilizers to orchestrate cellular functions. Compartmentalized cAMP signalling regulates important cellular processes in the lung and may serve as a therapeutic target. PMID:24281338

Observation of Discrete-Time-Crystal Signatures in an Ordered Dipolar Many-Body System

NASA Astrophysics Data System (ADS)

Rovny, Jared; Blum, Robert L.; Barrett, Sean E.

2018-05-01

A discrete time crystal (DTC) is a robust phase of driven systems that breaks the discrete time translation symmetry of the driving Hamiltonian. Recent experiments have observed DTC signatures in two distinct systems. Here we show nuclear magnetic resonance observations of DTC signatures in a third, strikingly different system: an ordered spatial crystal. We use a novel DTC echo experiment to probe the coherence of the driven system. Finally, we show that interactions during the pulse of the DTC sequence contribute to the decay of the signal, complicating attempts to measure the intrinsic lifetime of the DTC.

Observation of Discrete-Time-Crystal Signatures in an Ordered Dipolar Many-Body System.

PubMed

Rovny, Jared; Blum, Robert L; Barrett, Sean E

2018-05-04

A discrete time crystal (DTC) is a robust phase of driven systems that breaks the discrete time translation symmetry of the driving Hamiltonian. Recent experiments have observed DTC signatures in two distinct systems. Here we show nuclear magnetic resonance observations of DTC signatures in a third, strikingly different system: an ordered spatial crystal. We use a novel DTC echo experiment to probe the coherence of the driven system. Finally, we show that interactions during the pulse of the DTC sequence contribute to the decay of the signal, complicating attempts to measure the intrinsic lifetime of the DTC.

Development and Application of a Low Frequency Near-Field Interferometric-TOA 3D Lightning Mapping Array

NASA Astrophysics Data System (ADS)

Lyu, F.; Cummer, S. A.; Weinert, J. L.; McTague, L. E.; Solanki, R.; Barrett, J.

2014-12-01

Lightning processes radiated extremely wideband electromagnetic signals. Lightning images mapped by VHF interferometry and VHF time of arrival lightning mapping arrays enable us to understand the lightning in-cloud detail development during the extent of flash that can not always be captured by cameras because of the shield of cloud. Lightning processes radiate electromagnetically over an extremely wide bandwidth, offering the possibility of multispectral lightning radio imaging. Low frequency signals are often used for lightning detection, but usually only for ground point location or thunderstorm tracking. Some recent results have demonstrated lightning LF 3D mapping of discrete lightning pulses, but imaging of continuous LF emissions have not been shown. In this work, we report a GPS-synchronized LF near field interferometric-TOA 3D lightning mapping array applied to image the development of lightning flashes on second time scale. Cross-correlation, as used in broadband interferometry, is applied in our system to find windowed arrival time differences with sub-microsecond time resolution. However, because the sources are in the near field of the array, time of arrival processing is used to find the source locations with a typical precision of 100 meters. We show that this system images the complete lightning flash structure with thousands of LF sources for extensive flashes. Importantly, this system is able to map both continuous emissions like dart leaders, and bursty or discrete emissions. Lightning stepped leader and dart leader propagation speeds are estimated to 0.56-2.5x105 m/s and 0.8-2.0x106 m/s respectively, which are consistent with previous reports. In many aspects our LF images are remarkably similar to VHF lightning mapping array images, despite the 1000 times difference in frequency, which may suggest some special links between the LF and VHF emission during lightning processes.

Processing of mammalian preprogastrin-releasing peptide.

PubMed

Reeve, J R; Cuttitta, F; Vigna, S R; Shively, J E; Walsh, J H

1988-01-01

The processing of preprogastrin-releasing peptide in mammalian tissues and in cultured cells takes place at discrete sites (Figure 6). Signal peptidase cleaves away the signal peptide from the amino terminus of gastrin-releasing peptide. An exopeptidase activity may remove dipeptides from the amino terminus. The amidation site (not shown in Fig. 6; see Fig. 2) has the same general sequence (Gly-Lys-Lys) seen for other amidated peptides. Cleavage after single basic residues yields gene-related products from Form I or II preproGRP. A unique non-basic cleavage yields a gene-related product from Form III preproGRP. The processing that occurs to form GRP, GRP, and GRP gene-related peptides is shown in Figure 7. ProGRP is cleaved by a series of enzymes to form GRP with an amidated carboxyl-terminal methionine (indicated by an asterisk in Fig. 7). GRP is cleaved to form the decapeptide GRP. The carboxyl-terminal flanking peptides of all three mRNA translation products are cleaved to form several gastrin-releasing peptide gene-related products. Knowledge of the processing of gastrin-releasing peptide and its gene-related products will allow synthesis of duplicates of the stored forms of these peptides, which can then be used for biological testing.

Eigenforms, Discrete Processes and Quantum Processes

NASA Astrophysics Data System (ADS)

Kauffman, Louis H.

2012-05-01

This essay is a discussion of the concept of eigenform, due to Heinz von Foerster, and its relationship with discrete physics and quantum mechanics. We interpret the square root of minus one as a simple oscillatory process - a clock, and as an eigenform. By taking a generalization of this identification of i as a clock and eigenform, we show how quantum mechanics emerges from discrete physics.

Fault Detection and Diagnosis In Hall-Héroult Cells Based on Individual Anode Current Measurements Using Dynamic Kernel PCA

NASA Astrophysics Data System (ADS)

Yao, Yuchen; Bao, Jie; Skyllas-Kazacos, Maria; Welch, Barry J.; Akhmetov, Sergey

2018-04-01

Individual anode current signals in aluminum reduction cells provide localized cell conditions in the vicinity of each anode, which contain more information than the conventionally measured cell voltage and line current. One common use of this measurement is to identify process faults that can cause significant changes in the anode current signals. While this method is simple and direct, it ignores the interactions between anode currents and other important process variables. This paper presents an approach that applies multivariate statistical analysis techniques to individual anode currents and other process operating data, for the detection and diagnosis of local process abnormalities in aluminum reduction cells. Specifically, since the Hall-Héroult process is time-varying with its process variables dynamically and nonlinearly correlated, dynamic kernel principal component analysis with moving windows is used. The cell is discretized into a number of subsystems, with each subsystem representing one anode and cell conditions in its vicinity. The fault associated with each subsystem is identified based on multivariate statistical control charts. The results show that the proposed approach is able to not only effectively pinpoint the problematic areas in the cell, but also assess the effect of the fault on different parts of the cell.

Optimization and quantization in gradient symbol systems: a framework for integrating the continuous and the discrete in cognition.

PubMed

Smolensky, Paul; Goldrick, Matthew; Mathis, Donald

2014-08-01

Mental representations have continuous as well as discrete, combinatorial properties. For example, while predominantly discrete, phonological representations also vary continuously; this is reflected by gradient effects in instrumental studies of speech production. Can an integrated theoretical framework address both aspects of structure? The framework we introduce here, Gradient Symbol Processing, characterizes the emergence of grammatical macrostructure from the Parallel Distributed Processing microstructure (McClelland, Rumelhart, & The PDP Research Group, 1986) of language processing. The mental representations that emerge, Distributed Symbol Systems, have both combinatorial and gradient structure. They are processed through Subsymbolic Optimization-Quantization, in which an optimization process favoring representations that satisfy well-formedness constraints operates in parallel with a distributed quantization process favoring discrete symbolic structures. We apply a particular instantiation of this framework, λ-Diffusion Theory, to phonological production. Simulations of the resulting model suggest that Gradient Symbol Processing offers a way to unify accounts of grammatical competence with both discrete and continuous patterns in language performance. Copyright © 2013 Cognitive Science Society, Inc.

Clustering social cues to determine social signals: developing learning algorithms using the "n-most likely states" approach

NASA Astrophysics Data System (ADS)

Best, Andrew; Kapalo, Katelynn A.; Warta, Samantha F.; Fiore, Stephen M.

2016-05-01

Human-robot teaming largely relies on the ability of machines to respond and relate to human social signals. Prior work in Social Signal Processing has drawn a distinction between social cues (discrete, observable features) and social signals (underlying meaning). For machines to attribute meaning to behavior, they must first understand some probabilistic relationship between the cues presented and the signal conveyed. Using data derived from a study in which participants identified a set of salient social signals in a simulated scenario and indicated the cues related to the perceived signals, we detail a learning algorithm, which clusters social cue observations and defines an "N-Most Likely States" set for each cluster. Since multiple signals may be co-present in a given simulation and a set of social cues often maps to multiple social signals, the "N-Most Likely States" approach provides a dramatic improvement over typical linear classifiers. We find that the target social signal appears in a "3 most-likely signals" set with up to 85% probability. This results in increased speed and accuracy on large amounts of data, which is critical for modeling social cognition mechanisms in robots to facilitate more natural human-robot interaction. These results also demonstrate the utility of such an approach in deployed scenarios where robots need to communicate with human teammates quickly and efficiently. In this paper, we detail our algorithm, comparative results, and offer potential applications for robot social signal detection and machine-aided human social signal detection.

Relative Wave Energy based Adaptive Neuro-Fuzzy Inference System model for the Estimation of Depth of Anaesthesia.

PubMed

Benzy, V K; Jasmin, E A; Koshy, Rachel Cherian; Amal, Frank; Indiradevi, K P

2018-01-01

The advancement in medical research and intelligent modeling techniques has lead to the developments in anaesthesia management. The present study is targeted to estimate the depth of anaesthesia using cognitive signal processing and intelligent modeling techniques. The neurophysiological signal that reflects cognitive state of anaesthetic drugs is the electroencephalogram signal. The information available on electroencephalogram signals during anaesthesia are drawn by extracting relative wave energy features from the anaesthetic electroencephalogram signals. Discrete wavelet transform is used to decomposes the electroencephalogram signals into four levels and then relative wave energy is computed from approximate and detail coefficients of sub-band signals. Relative wave energy is extracted to find out the degree of importance of different electroencephalogram frequency bands associated with different anaesthetic phases awake, induction, maintenance and recovery. The Kruskal-Wallis statistical test is applied on the relative wave energy features to check the discriminating capability of relative wave energy features as awake, light anaesthesia, moderate anaesthesia and deep anaesthesia. A novel depth of anaesthesia index is generated by implementing a Adaptive neuro-fuzzy inference system based fuzzy c-means clustering algorithm which uses relative wave energy features as inputs. Finally, the generated depth of anaesthesia index is compared with a commercially available depth of anaesthesia monitor Bispectral index.

Two-level image authentication by two-step phase-shifting interferometry and compressive sensing

NASA Astrophysics Data System (ADS)

Zhang, Xue; Meng, Xiangfeng; Yin, Yongkai; Yang, Xiulun; Wang, Yurong; Li, Xianye; Peng, Xiang; He, Wenqi; Dong, Guoyan; Chen, Hongyi

2018-01-01

A two-level image authentication method is proposed; the method is based on two-step phase-shifting interferometry, double random phase encoding, and compressive sensing (CS) theory, by which the certification image can be encoded into two interferograms. Through discrete wavelet transform (DWT), sparseness processing, Arnold transform, and data compression, two compressed signals can be generated and delivered to two different participants of the authentication system. Only the participant who possesses the first compressed signal attempts to pass the low-level authentication. The application of Orthogonal Match Pursuit CS algorithm reconstruction, inverse Arnold transform, inverse DWT, two-step phase-shifting wavefront reconstruction, and inverse Fresnel transform can result in the output of a remarkable peak in the central location of the nonlinear correlation coefficient distributions of the recovered image and the standard certification image. Then, the other participant, who possesses the second compressed signal, is authorized to carry out the high-level authentication. Therefore, both compressed signals are collected to reconstruct the original meaningful certification image with a high correlation coefficient. Theoretical analysis and numerical simulations verify the feasibility of the proposed method.

A new discrete dynamic model of ABA-induced stomatal closure predicts key feedback loops

PubMed Central

Acharya, Biswa R.; Jeon, Byeong Wook; Zañudo, Jorge G. T.; Zhu, Mengmeng; Osman, Karim; Assmann, Sarah M.

2017-01-01

Stomata, microscopic pores in leaf surfaces through which water loss and carbon dioxide uptake occur, are closed in response to drought by the phytohormone abscisic acid (ABA). This process is vital for drought tolerance and has been the topic of extensive experimental investigation in the last decades. Although a core signaling chain has been elucidated consisting of ABA binding to receptors, which alleviates negative regulation by protein phosphatases 2C (PP2Cs) of the protein kinase OPEN STOMATA 1 (OST1) and ultimately results in activation of anion channels, osmotic water loss, and stomatal closure, over 70 additional components have been identified, yet their relationships with each other and the core components are poorly elucidated. We integrated and processed hundreds of disparate observations regarding ABA signal transduction responses underlying stomatal closure into a network of 84 nodes and 156 edges and, as a result, established those relationships, including identification of a 36-node, strongly connected (feedback-rich) component as well as its in- and out-components. The network’s domination by a feedback-rich component may reflect a general feature of rapid signaling events. We developed a discrete dynamic model of this network and elucidated the effects of ABA plus knockout or constitutive activity of 79 nodes on both the outcome of the system (closure) and the status of all internal nodes. The model, with more than 1024 system states, is far from fully determined by the available data, yet model results agree with existing experiments in 82 cases and disagree in only 17 cases, a validation rate of 75%. Our results reveal nodes that could be engineered to impact stomatal closure in a controlled fashion and also provide over 140 novel predictions for which experimental data are currently lacking. Noting the paucity of wet-bench data regarding combinatorial effects of ABA and internal node activation, we experimentally confirmed several predictions of the model with regard to reactive oxygen species, cytosolic Ca2+ (Ca2+c), and heterotrimeric G-protein signaling. We analyzed dynamics-determining positive and negative feedback loops, thereby elucidating the attractor (dynamic behavior) repertoire of the system and the groups of nodes that determine each attractor. Based on this analysis, we predict the likely presence of a previously unrecognized feedback mechanism dependent on Ca2+c. This mechanism would provide model agreement with 10 additional experimental observations, for a validation rate of 85%. Our research underscores the importance of feedback regulation in generating robust and adaptable biological responses. The high validation rate of our model illustrates the advantages of discrete dynamic modeling for complex, nonlinear systems common in biology. PMID:28937978

Imaging quality evaluation method of pixel coupled electro-optical imaging system

NASA Astrophysics Data System (ADS)

He, Xu; Yuan, Li; Jin, Chunqi; Zhang, Xiaohui

2017-09-01

With advancements in high-resolution imaging optical fiber bundle fabrication technology, traditional photoelectric imaging system have become ;flexible; with greatly reduced volume and weight. However, traditional image quality evaluation models are limited by the coupling discrete sampling effect of fiber-optic image bundles and charge-coupled device (CCD) pixels. This limitation substantially complicates the design, optimization, assembly, and evaluation image quality of the coupled discrete sampling imaging system. Based on the transfer process of grayscale cosine distribution optical signal in the fiber-optic image bundle and CCD, a mathematical model of coupled modulation transfer function (coupled-MTF) is established. This model can be used as a basis for following studies on the convergence and periodically oscillating characteristics of the function. We also propose the concept of the average coupled-MTF, which is consistent with the definition of traditional MTF. Based on this concept, the relationships among core distance, core layer radius, and average coupled-MTF are investigated.

A H-infinity Fault Detection and Diagnosis Scheme for Discrete Nonlinear System Using Output Probability Density Estimation

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

Zhang Yumin; Lum, Kai-Yew; Wang Qingguo

In this paper, a H-infinity fault detection and diagnosis (FDD) scheme for a class of discrete nonlinear system fault using output probability density estimation is presented. Unlike classical FDD problems, the measured output of the system is viewed as a stochastic process and its square root probability density function (PDF) is modeled with B-spline functions, which leads to a deterministic space-time dynamic model including nonlinearities, uncertainties. A weighting mean value is given as an integral function of the square root PDF along space direction, which leads a function only about time and can be used to construct residual signal. Thus,more » the classical nonlinear filter approach can be used to detect and diagnose the fault in system. A feasible detection criterion is obtained at first, and a new H-infinity adaptive fault diagnosis algorithm is further investigated to estimate the fault. Simulation example is given to demonstrate the effectiveness of the proposed approaches.« less

A H-infinity Fault Detection and Diagnosis Scheme for Discrete Nonlinear System Using Output Probability Density Estimation

NASA Astrophysics Data System (ADS)

Zhang, Yumin; Wang, Qing-Guo; Lum, Kai-Yew

2009-03-01

In this paper, a H-infinity fault detection and diagnosis (FDD) scheme for a class of discrete nonlinear system fault using output probability density estimation is presented. Unlike classical FDD problems, the measured output of the system is viewed as a stochastic process and its square root probability density function (PDF) is modeled with B-spline functions, which leads to a deterministic space-time dynamic model including nonlinearities, uncertainties. A weighting mean value is given as an integral function of the square root PDF along space direction, which leads a function only about time and can be used to construct residual signal. Thus, the classical nonlinear filter approach can be used to detect and diagnose the fault in system. A feasible detection criterion is obtained at first, and a new H-infinity adaptive fault diagnosis algorithm is further investigated to estimate the fault. Simulation example is given to demonstrate the effectiveness of the proposed approaches.

Discrete-time modelling of musical instruments

NASA Astrophysics Data System (ADS)

Välimäki, Vesa; Pakarinen, Jyri; Erkut, Cumhur; Karjalainen, Matti

2006-01-01

This article describes physical modelling techniques that can be used for simulating musical instruments. The methods are closely related to digital signal processing. They discretize the system with respect to time, because the aim is to run the simulation using a computer. The physics-based modelling methods can be classified as mass-spring, modal, wave digital, finite difference, digital waveguide and source-filter models. We present the basic theory and a discussion on possible extensions for each modelling technique. For some methods, a simple model example is chosen from the existing literature demonstrating a typical use of the method. For instance, in the case of the digital waveguide modelling technique a vibrating string model is discussed, and in the case of the wave digital filter technique we present a classical piano hammer model. We tackle some nonlinear and time-varying models and include new results on the digital waveguide modelling of a nonlinear string. Current trends and future directions in physical modelling of musical instruments are discussed.

Using leap motion to investigate the emergence of structure in speech and language.

PubMed

Eryilmaz, Kerem; Little, Hannah

2017-10-01

 In evolutionary linguistics, experiments using artificial signal spaces are being used to investigate the emergenceof speech structure. These signal spaces need to be continuous, non-discretized spaces from which discrete unitsand patterns can emerge. They need to be dissimilar from-but comparable with-the vocal tract, in order tominimize interference from pre-existing linguistic knowledge, while informing us about language. This is a hardbalance to strike. This article outlines a new approach that uses the Leap Motion, an infrared controller that canconvert manual movement in 3d space into sound. The signal space using this approach is more flexible than signalspaces in previous attempts. Further, output data using this approach is simpler to arrange and analyze. Theexperimental interface was built using free, and mostly open- source libraries in Python. We provide our sourcecode for other researchers as open source.

Delay-feedback control strategy for reducing CO2 emission of traffic flow system

NASA Astrophysics Data System (ADS)

Zhang, Li-Dong; Zhu, Wen-Xing

2015-06-01

To study the signal control strategy for reducing traffic emission theoretically, we first presented a kind of discrete traffic flow model with relative speed term based on traditional coupled map car-following model. In the model, the relative speed difference between two successive running cars is incorporated into following vehicle's acceleration running equation. Then we analyzed its stability condition with discrete control system stability theory. Third, we designed a delay-feedback controller to suppress traffic jam and decrease traffic emission based on modern controller theory. Last, numerical simulations are made to support our theoretical results, including the comparison of models' stability analysis, the influence of model type and signal control on CO2 emissions. The results show that the temporal behavior of our model is superior to other models, and the traffic signal controller has good effect on traffic jam suppression and traffic CO2 emission, which fully supports the theoretical conclusions.

The behavior of quantization spectra as a function of signal-to-noise ratio

NASA Technical Reports Server (NTRS)

Flanagan, M. J.

1991-01-01

An expression for the spectrum of quantization error in a discrete-time system whose input is a sinusoid plus white Gaussian noise is derived. This quantization spectrum consists of two components: a white-noise floor and spurious harmonics. The dithering effect of the input Gaussian noise in both components of the spectrum is considered. Quantitative results in a discrete Fourier transform (DFT) example show the behavior of spurious harmonics as a function of the signal-to-noise ratio (SNR). These results have strong implications for digital reception and signal analysis systems. At low SNRs, spurious harmonics decay exponentially on a log-log scale, and the resulting spectrum is white. As the SNR increases, the spurious harmonics figure prominently in the output spectrum. A useful expression is given that roughly bounds the magnitude of a spurious harmonic as a function of the SNR.

Iterative Potts and Blake–Zisserman minimization for the recovery of functions with discontinuities from indirect measurements

PubMed Central

Weinmann, Andreas; Storath, Martin

2015-01-01

Signals with discontinuities appear in many problems in the applied sciences ranging from mechanics, electrical engineering to biology and medicine. The concrete data acquired are typically discrete, indirect and noisy measurements of some quantities describing the signal under consideration. The task is to restore the signal and, in particular, the discontinuities. In this respect, classical methods perform rather poor, whereas non-convex non-smooth variational methods seem to be the correct choice. Examples are methods based on Mumford–Shah and piecewise constant Mumford–Shah functionals and discretized versions which are known as Blake–Zisserman and Potts functionals. Owing to their non-convexity, minimization of such functionals is challenging. In this paper, we propose a new iterative minimization strategy for Blake–Zisserman as well as Potts functionals and a related jump-sparsity problem dealing with indirect, noisy measurements. We provide a convergence analysis and underpin our findings with numerical experiments. PMID:27547074

Synergistic control of protein kinase Cgamma activity by ionotropic and metabotropic glutamate receptor inputs in hippocampal neurons.

PubMed

Codazzi, Franca; Di Cesare, Alessandra; Chiulli, Nino; Albanese, Alberto; Meyer, Tobias; Zacchetti, Daniele; Grohovaz, Fabio

2006-03-29

Conventional protein kinase C (PKC) isoforms are abundant neuronal signaling proteins with important roles in regulating synaptic plasticity and other neuronal processes. Here, we investigate the role of ionotropic and metabotropic glutamate receptor (iGluR and mGluR, respectively) activation on the generation of Ca2+ and diacylglycerol (DAG) signals and the subsequent activation of the neuron-specific PKCgamma isoform in hippocampal neurons. By combining Ca2+ imaging with total internal reflection microscopy analysis of specific biosensors, we show that elevation of both Ca2+ and DAG is necessary for sustained translocation and activation of EGFP (enhanced green fluorescent protein)-PKCgamma. Both DAG production and PKCgamma translocation were localized processes, typically observed within discrete microdomains along the dendritic branches. Markedly, intermediate-strength NMDA receptor (NMDAR) activation or moderate electrical stimulation generated Ca2+ but no DAG signals, whereas mGluR activation generated DAG but no Ca2+ signals. Both receptors were needed for PKCgamma activation. This suggests that a coincidence detection process exists between iGluRs and mGluRs that relies on a molecular coincidence detection process based on the corequirement of Ca2+ and DAG for PKCgamma activation. Nevertheless, the requirement for costimulation with mGluRs could be overcome for maximal NMDAR stimulation through a direct production of DAG via activation of the Ca2+-sensitive PLCdelta (phospholipase Cdelta) isoform. In a second important exception, mGluRs were sufficient for PKCgamma activation in neurons in which Ca2+ stores were loaded by previous electrical activity. Together, the dual activation requirement for PKCgamma provides a plausible molecular interpretation for different synergistic contributions of mGluRs to long-term potentiation and other synaptic plasticity processes.

Simultaneous storage of medical images in the spatial and frequency domain: A comparative study

PubMed Central

Nayak, Jagadish; Bhat, P Subbanna; Acharya U, Rajendra; UC, Niranjan

2004-01-01

Background Digital watermarking is a technique of hiding specific identification data for copyright authentication. This technique is adapted here for interleaving patient information with medical images, to reduce storage and transmission overheads. Methods The patient information is encrypted before interleaving with images to ensure greater security. The bio-signals are compressed and subsequently interleaved with the image. This interleaving is carried out in the spatial domain and Frequency domain. The performance of interleaving in the spatial, Discrete Fourier Transform (DFT), Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) coefficients is studied. Differential pulse code modulation (DPCM) is employed for data compression as well as encryption and results are tabulated for a specific example. Results It can be seen from results, the process does not affect the picture quality. This is attributed to the fact that the change in LSB of a pixel changes its brightness by 1 part in 256. Spatial and DFT domain interleaving gave very less %NRMSE as compared to DCT and DWT domain. Conclusion The Results show that spatial domain the interleaving, the %NRMSE was less than 0.25% for 8-bit encoded pixel intensity. Among the frequency domain interleaving methods, DFT was found to be very efficient. PMID:15180899

Drosophila Neuropeptide F Signaling Independently Regulates Feeding and Sleep-Wake Behavior.

PubMed

Chung, Brian Y; Ro, Jennifer; Hutter, Sabine A; Miller, Kylie M; Guduguntla, Lakshmi S; Kondo, Shu; Pletcher, Scott D

2017-06-20

Proper regulation of sleep-wake behavior and feeding is essential for organismal health and survival. While previous studies have isolated discrete neural loci and substrates important for either sleep or feeding, how the brain is organized to coordinate both processes with respect to one another remains poorly understood. Here, we provide evidence that the Drosophila Neuropeptide F (NPF) network forms a critical component of both adult sleep and feeding regulation. Activation of NPF signaling in the brain promotes wakefulness and adult feeding, likely through its cognate receptor NPFR. Flies carrying a loss-of-function NPF allele do not suppress sleep following prolonged starvation conditions, suggesting that NPF acts as a hunger signal to keep the animal awake. NPF-expressing cells, specifically those expressing the circadian photoreceptor cryptochrome, are largely responsible for changes to sleep behavior caused by NPF neuron activation, but not feeding, demonstrating that different NPF neurons separately drive wakefulness and hunger. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

A Full Dynamic Compound Inverse Method for output-only element-level system identification and input estimation from earthquake response signals

NASA Astrophysics Data System (ADS)

Pioldi, Fabio; Rizzi, Egidio

2016-08-01

This paper proposes a new output-only element-level system identification and input estimation technique, towards the simultaneous identification of modal parameters, input excitation time history and structural features at the element-level by adopting earthquake-induced structural response signals. The method, named Full Dynamic Compound Inverse Method (FDCIM), releases strong assumptions of earlier element-level techniques, by working with a two-stage iterative algorithm. Jointly, a Statistical Average technique, a modification process and a parameter projection strategy are adopted at each stage to achieve stronger convergence for the identified estimates. The proposed method works in a deterministic way and is completely developed in State-Space form. Further, it does not require continuous- to discrete-time transformations and does not depend on initialization conditions. Synthetic earthquake-induced response signals from different shear-type buildings are generated to validate the implemented procedure, also with noise-corrupted cases. The achieved results provide a necessary condition to demonstrate the effectiveness of the proposed identification method.

Signal acquisition and analysis for cortical control of neuroprosthetics.

PubMed

Tillery, Stephen I Helms; Taylor, Dawn M

2004-12-01

Work in cortically controlled neuroprosthetic systems has concentrated on decoding natural behaviors from neural activity, with the idea that if the behavior could be fully decoded it could be duplicated using an artificial system. Initial estimates from this approach suggested that a high-fidelity signal comprised of many hundreds of neurons would be required to control a neuroprosthetic system successfully. However, recent studies are showing hints that these systems can be controlled effectively using only a few tens of neurons. Attempting to decode the pre-existing relationship between neural activity and natural behavior is not nearly as important as choosing a decoding scheme that can be more readily deployed and trained to generate the desired actions of the artificial system. These artificial systems need not resemble or behave similarly to any natural biological system. Effective matching of discrete and continuous neural command signals to appropriately configured device functions will enable effective control of both natural and abstract artificial systems using compatible thought processes.

Two Analyte Calibration From The Transient Response Of Potentiometric Sensors Employed With The SIA Technique

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

Cartas, Raul; Mimendia, Aitor; Valle, Manel del

2009-05-23

Calibration models for multi-analyte electronic tongues have been commonly built using a set of sensors, at least one per analyte under study. Complex signals recorded with these systems are formed by the sensors' responses to the analytes of interest plus interferents, from which a multivariate response model is then developed. This work describes a data treatment method for the simultaneous quantification of two species in solution employing the signal from a single sensor. The approach used here takes advantage of the complex information recorded with one electrode's transient after insertion of sample for building the calibration models for both analytes.more » The departure information from the electrode was firstly processed by discrete wavelet for transforming the signals to extract useful information and reduce its length, and then by artificial neural networks for fitting a model. Two different potentiometric sensors were used as study case for simultaneously corroborating the effectiveness of the approach.« less

Wavelet methodology to improve single unit isolation in primary motor cortex cells

PubMed Central

Ortiz-Rosario, Alexis; Adeli, Hojjat; Buford, John A.

2016-01-01

The proper isolation of action potentials recorded extracellularly from neural tissue is an active area of research in the fields of neuroscience and biomedical signal processing. This paper presents an isolation methodology for neural recordings using the wavelet transform (WT), a statistical thresholding scheme, and the principal component analysis (PCA) algorithm. The effectiveness of five different mother wavelets was investigated: biorthogonal, Daubachies, discrete Meyer, symmetric, and Coifman; along with three different wavelet coefficient thresholding schemes: fixed form threshold, Stein’s unbiased estimate of risk, and minimax; and two different thresholding rules: soft and hard thresholding. The signal quality was evaluated using three different statistical measures: mean-squared error, root-mean squared, and signal to noise ratio. The clustering quality was evaluated using two different statistical measures: isolation distance, and L-ratio. This research shows that the selection of the mother wavelet has a strong influence on the clustering and isolation of single unit neural activity, with the Daubachies 4 wavelet and minimax thresholding scheme performing the best. PMID:25794461

Influence of Waveform Characteristics on LiDAR Ranging Accuracy and Precision

PubMed Central

Yang, Bingwei; Xie, Xinhao; Li, Duan

2018-01-01

Time of flight (TOF) based light detection and ranging (LiDAR) is a technology for calculating distance between start/stop signals of time of flight. In lab-built LiDAR, two ranging systems for measuring flying time between start/stop signals include time-to-digital converter (TDC) that counts time between trigger signals and analog-to-digital converter (ADC) that processes the sampled start/stop pulses waveform for time estimation. We study the influence of waveform characteristics on range accuracy and precision of two kinds of ranging system. Comparing waveform based ranging (WR) with analog discrete return system based ranging (AR), a peak detection method (WR-PK) shows the best ranging performance because of less execution time, high ranging accuracy, and stable precision. Based on a novel statistic mathematical method maximal information coefficient (MIC), WR-PK precision has a high linear relationship with the received pulse width standard deviation. Thus keeping the received pulse width of measuring a constant distance as stable as possible can improve ranging precision. PMID:29642639

Discrete-State Stochastic Models of Calcium-Regulated Calcium Influx and Subspace Dynamics Are Not Well-Approximated by ODEs That Neglect Concentration Fluctuations

PubMed Central

Weinberg, Seth H.; Smith, Gregory D.

2012-01-01

Cardiac myocyte calcium signaling is often modeled using deterministic ordinary differential equations (ODEs) and mass-action kinetics. However, spatially restricted “domains” associated with calcium influx are small enough (e.g., 10−17 liters) that local signaling may involve 1–100 calcium ions. Is it appropriate to model the dynamics of subspace calcium using deterministic ODEs or, alternatively, do we require stochastic descriptions that account for the fundamentally discrete nature of these local calcium signals? To address this question, we constructed a minimal Markov model of a calcium-regulated calcium channel and associated subspace. We compared the expected value of fluctuating subspace calcium concentration (a result that accounts for the small subspace volume) with the corresponding deterministic model (an approximation that assumes large system size). When subspace calcium did not regulate calcium influx, the deterministic and stochastic descriptions agreed. However, when calcium binding altered channel activity in the model, the continuous deterministic description often deviated significantly from the discrete stochastic model, unless the subspace volume is unrealistically large and/or the kinetics of the calcium binding are sufficiently fast. This principle was also demonstrated using a physiologically realistic model of calmodulin regulation of L-type calcium channels introduced by Yue and coworkers. PMID:23509597

Continuous Active Sonar for Undersea Vehicles Final Report: Input of Factor Graphs into the Detection, Classification, and Localization Chain and Continuous Active SONAR in Undersea Vehicles

DTIC Science & Technology

2015-12-31

image from NURP annual report. in X The ray -cone code simulates the CAS signal received after being reflected form two different targets, and...Cm where m, m, ... , 1fn are X ’s parents, and nodes C1, C1, ... , C,, are X ’s children. Image based on (Duda, Hart, & Stork, 2001). The first...Sorenson, 1970). Using the reference (Welch & Bishop, 2006), the procedure for estimating the real state x , of a discrete-time controlled process , will

Implementing the sine transform of fermionic modes as a tensor network

NASA Astrophysics Data System (ADS)

Epple, Hannes; Fries, Pascal; Hinrichsen, Haye

2017-09-01

Based on the algebraic theory of signal processing, we recursively decompose the discrete sine transform of the first kind (DST-I) into small orthogonal block operations. Using a diagrammatic language, we then second-quantize this decomposition to construct a tensor network implementing the DST-I for fermionic modes on a lattice. The complexity of the resulting network is shown to scale as 5/4 n logn (not considering swap gates), where n is the number of lattice sites. Our method provides a systematic approach of generalizing Ferris' spectral tensor network for nontrivial boundary conditions.

Circuitry, systems and methods for detecting magnetic fields

DOEpatents

Kotter, Dale K [Shelley, ID; Spencer, David F [Idaho Falls, ID; Roybal, Lyle G [Idaho Falls, ID; Rohrbaugh, David T [Idaho Falls, ID

2010-09-14

Circuitry for detecting magnetic fields includes a first magnetoresistive sensor and a second magnetoresistive sensor configured to form a gradiometer. The circuitry includes a digital signal processor and a first feedback loop coupled between the first magnetoresistive sensor and the digital signal processor. A second feedback loop which is discrete from the first feedback loop is coupled between the second magnetoresistive sensor and the digital signal processor.

Human Supervision of Time Critical Control Systems. Addendum

DTIC Science & Technology

2010-02-26

signals such as electroencephalogram (EEG) and electrooculography ( EOG ). Current research has demonstrated these signals ’ ability to respond to changing...relationships often present in EEG/ EOG data; they routinely achieve classification accuracy greater than 80%. However, the discrete output of these...present data there were seven EEG and EOG signals recorded, thus, ICA assumes each were a mixture of seven independent components (Stone, 2002). Some

Fast heap transform-based QR-decomposition of real and complex matrices: algorithms and codes

NASA Astrophysics Data System (ADS)

Grigoryan, Artyom M.

2015-03-01

In this paper, we describe a new look on the application of Givens rotations to the QR-decomposition problem, which is similar to the method of Householder transformations. We apply the concept of the discrete heap transform, or signal-induced unitary transforms which had been introduced by Grigoryan (2006) and used in signal and image processing. Both cases of real and complex nonsingular matrices are considered and examples of performing QR-decomposition of square matrices are given. The proposed method of QR-decomposition for the complex matrix is novel and differs from the known method of complex Givens rotation and is based on analytical equations for the heap transforms. Many examples illustrated the proposed heap transform method of QR-decomposition are given, algorithms are described in detail, and MATLAB-based codes are included.

Molecular parameters of head and neck cancer metastasis

PubMed Central

Bhave, Sanjay L.; Teknos, Theodoros N.; Pan, Quintin; James, Arthur G.; Solove, Richard J.

2011-01-01

Metastasis remains a major cause of mortality in patients with head and neck squamous cell carcinoma (HNSCC). HNSCC patients with metastatic disease have extremely poor prognosis with survival rate of less than a year. Metastasis is an intricate sequential process which requires a discrete population of tumor cells to possess the capacity to intravasate from the primary tumor into systemic circulation, survive in circulation, extravasate at a distant site, and proliferate in a foreign hostile environment. Literature has accumulated to provide mechanistic insight into several signal transduction pathways, receptor tyrosine kinases (RTKs), signal transducer and activator of transcription 3 (Stat3), Rho GTPases, protein kinase Cε (PKCε), and nuclear factor-κB (NF-κB), that are involved in mediating a metastatic tumor cell phenotype in HNSCC. Here we highlight accrued information regarding the key molecular parameters of HNSCC metastasis. PMID:22077153

Acoustic sand detector for fluid flowstreams

DOEpatents

Beattie, Alan G.; Bohon, W. Mark

1993-01-01

The particle volume and particle mass production rate of particulate solids entrained in fluid flowstreams such as formation sand or fracture proppant entrained in oil and gas production flowstreams is determined by a system having a metal probe interposed in a flow conduit for transmitting acoustic emissions created by particles impacting the probe to a sensor and signal processing circuit which produces discrete signals related to the impact of each of the particles striking the probe. The volume or mass flow rate of particulates is determined from making an initial particle size distribution and particle energy distribution and comparing the initial energy distribution and/or the initial size distribution with values related to the impact energies of a predetermined number of recorded impacts. The comparison is also used to recalibrate the system to compensate for changes in flow velocity.

SPHARA--a generalized spatial Fourier analysis for multi-sensor systems with non-uniformly arranged sensors: application to EEG.

PubMed

Graichen, Uwe; Eichardt, Roland; Fiedler, Patrique; Strohmeier, Daniel; Zanow, Frank; Haueisen, Jens

2015-01-01

Important requirements for the analysis of multichannel EEG data are efficient techniques for signal enhancement, signal decomposition, feature extraction, and dimensionality reduction. We propose a new approach for spatial harmonic analysis (SPHARA) that extends the classical spatial Fourier analysis to EEG sensors positioned non-uniformly on the surface of the head. The proposed method is based on the eigenanalysis of the discrete Laplace-Beltrami operator defined on a triangular mesh. We present several ways to discretize the continuous Laplace-Beltrami operator and compare the properties of the resulting basis functions computed using these discretization methods. We apply SPHARA to somatosensory evoked potential data from eleven volunteers and demonstrate the ability of the method for spatial data decomposition, dimensionality reduction and noise suppression. When employing SPHARA for dimensionality reduction, a significantly more compact representation can be achieved using the FEM approach, compared to the other discretization methods. Using FEM, to recover 95% and 99% of the total energy of the EEG data, on average only 35% and 58% of the coefficients are necessary. The capability of SPHARA for noise suppression is shown using artificial data. We conclude that SPHARA can be used for spatial harmonic analysis of multi-sensor data at arbitrary positions and can be utilized in a variety of other applications.

Parallel Stochastic discrete event simulation of calcium dynamics in neuron.

PubMed

Ishlam Patoary, Mohammad Nazrul; Tropper, Carl; McDougal, Robert A; Zhongwei, Lin; Lytton, William W

2017-09-26

The intra-cellular calcium signaling pathways of a neuron depends on both biochemical reactions and diffusions. Some quasi-isolated compartments (e.g. spines) are so small and calcium concentrations are so low that one extra molecule diffusing in by chance can make a nontrivial difference in its concentration (percentage-wise). These rare events can affect dynamics discretely in such way that they cannot be evaluated by a deterministic simulation. Stochastic models of such a system provide a more detailed understanding of these systems than existing deterministic models because they capture their behavior at a molecular level. Our research focuses on the development of a high performance parallel discrete event simulation environment, Neuron Time Warp (NTW), which is intended for use in the parallel simulation of stochastic reaction-diffusion systems such as intra-calcium signaling. NTW is integrated with NEURON, a simulator which is widely used within the neuroscience community. We simulate two models, a calcium buffer and a calcium wave model. The calcium buffer model is employed in order to verify the correctness and performance of NTW by comparing it to a serial deterministic simulation in NEURON. We also derived a discrete event calcium wave model from a deterministic model using the stochastic IP3R structure.

A new time-adaptive discrete bionic wavelet transform for enhancing speech from adverse noise environment

NASA Astrophysics Data System (ADS)

Palaniswamy, Sumithra; Duraisamy, Prakash; Alam, Mohammad Showkat; Yuan, Xiaohui

2012-04-01

Automatic speech processing systems are widely used in everyday life such as mobile communication, speech and speaker recognition, and for assisting the hearing impaired. In speech communication systems, the quality and intelligibility of speech is of utmost importance for ease and accuracy of information exchange. To obtain an intelligible speech signal and one that is more pleasant to listen, noise reduction is essential. In this paper a new Time Adaptive Discrete Bionic Wavelet Thresholding (TADBWT) scheme is proposed. The proposed technique uses Daubechies mother wavelet to achieve better enhancement of speech from additive non- stationary noises which occur in real life such as street noise and factory noise. Due to the integration of human auditory system model into the wavelet transform, bionic wavelet transform (BWT) has great potential for speech enhancement which may lead to a new path in speech processing. In the proposed technique, at first, discrete BWT is applied to noisy speech to derive TADBWT coefficients. Then the adaptive nature of the BWT is captured by introducing a time varying linear factor which updates the coefficients at each scale over time. This approach has shown better performance than the existing algorithms at lower input SNR due to modified soft level dependent thresholding on time adaptive coefficients. The objective and subjective test results confirmed the competency of the TADBWT technique. The effectiveness of the proposed technique is also evaluated for speaker recognition task under noisy environment. The recognition results show that the TADWT technique yields better performance when compared to alternate methods specifically at lower input SNR.

Method for distributed agent-based non-expert simulation of manufacturing process behavior

DOEpatents

Ivezic, Nenad; Potok, Thomas E.

2004-11-30

A method for distributed agent based non-expert simulation of manufacturing process behavior on a single-processor computer comprises the steps of: object modeling a manufacturing technique having a plurality of processes; associating a distributed agent with each the process; and, programming each the agent to respond to discrete events corresponding to the manufacturing technique, wherein each discrete event triggers a programmed response. The method can further comprise the step of transmitting the discrete events to each agent in a message loop. In addition, the programming step comprises the step of conditioning each agent to respond to a discrete event selected from the group consisting of a clock tick message, a resources received message, and a request for output production message.

Processing of the Liquid Xenon calorimeter's signals for timing measurements

NASA Astrophysics Data System (ADS)

Epshteyn, L. B.; Yudin, Yu V.

2014-09-01

One of the goals of the Cryogenic Magnetic Detector at Budker Institute of Nuclear Physics SB RAS (Novosibirsk, Russia) is a study of nucleons production in electron-positron collisions near threshold. The neutron-antineutron pair production events can be detected only by the calorimeters. In the barrel calorimeter the antineutron annihilation typically occurs by 5 ns or later after beams crossing. For identification of such events it is necessary to measure the time of flight of particles to the LXe-calorimeter with accuracy of about 3 ns. The LXe-calorimeter consists of 14 layers of ionization chambers with anode and cathode readout. The duration of charge collection to the anodes is about 4.5 mks, while the required accuracy of measuring of the signal arrival time is less than 1/1000 of that. Besides, the signals' shapes differ substantially from event to event, so the signal arrival time is measured in two stages. At the first stage, the signal arrival time is determined with an accuracy of 1-2 discretization periods, and initial values of parameters for subsequent fitting procedure are calculated. At the second stage, the signal arrival time is determined with the required accuracy by means of fitting of the signal waveform with a template waveform. To implement that, a special electronics has been developed which performs waveform digitization and On-Line measurement of signals' arrival times and amplitudes.

Time delay estimation using new spectral and adaptive filtering methods with applications to underwater target detection

NASA Astrophysics Data System (ADS)

Hasan, Mohammed A.

1997-11-01

In this dissertation, we present several novel approaches for detection and identification of targets of arbitrary shapes from the acoustic backscattered data and using the incident waveform. This problem is formulated as time- delay estimation and sinusoidal frequency estimation problems which both have applications in many other important areas in signal processing. Solving time-delay estimation problem allows the identification of the specular components in the backscattered signal from elastic and non-elastic targets. Thus, accurate estimation of these time delays would help in determining the existence of certain clues for detecting targets. Several new methods for solving these two problems in the time, frequency and wavelet domains are developed. In the time domain, a new block fast transversal filter (BFTF) is proposed for a fast implementation of the least squares (LS) method. This BFTF algorithm is derived by using data-related constrained block-LS cost function to guarantee global optimality. The new soft-constrained algorithm provides an efficient way of transferring weight information between blocks of data and thus it is computationally very efficient compared with other LS- based schemes. Additionally, the tracking ability of the algorithm can be controlled by varying the block length and/or a soft constrained parameter. The effectiveness of this algorithm is tested on several underwater acoustic backscattered data for elastic targets and non-elastic (cement chunk) objects. In the frequency domain, the time-delay estimation problem is converted to a sinusoidal frequency estimation problem by using the discrete Fourier transform. Then, the lagged sample covariance matrices of the resulting signal are computed and studied in terms of their eigen- structure. These matrices are shown to be robust and effective in extracting bases for the signal and noise subspaces. New MUSIC and matrix pencil-based methods are derived these subspaces. The effectiveness of the method is demonstrated on the problem of detection of multiple specular components in the acoustic backscattered data. Finally, a method for the estimation of time delays using wavelet decomposition is derived. The sub-band adaptive filtering uses discrete wavelet transform for multi- resolution or sub-band decomposition. Joint time delay estimation for identifying multi-specular components and subsequent adaptive filtering processes are performed on the signal in each sub-band. This would provide multiple 'look' of the signal at different resolution scale which results in more accurate estimates for delays associated with the specular components. Simulation results on the simulated and real shallow water data are provided which show the promise of this new scheme for target detection in a heavy cluttered environment.

Low-power hardware implementation of movement decoding for brain computer interface with reduced-resolution discrete cosine transform.

PubMed

Minho Won; Albalawi, Hassan; Xin Li; Thomas, Donald E

2014-01-01

This paper describes a low-power hardware implementation for movement decoding of brain computer interface. Our proposed hardware design is facilitated by two novel ideas: (i) an efficient feature extraction method based on reduced-resolution discrete cosine transform (DCT), and (ii) a new hardware architecture of dual look-up table to perform discrete cosine transform without explicit multiplication. The proposed hardware implementation has been validated for movement decoding of electrocorticography (ECoG) signal by using a Xilinx FPGA Zynq-7000 board. It achieves more than 56× energy reduction over a reference design using band-pass filters for feature extraction.

Bearing faults identification and resonant band demodulation based on wavelet de-noising methods and envelope analysis

NASA Astrophysics Data System (ADS)

Abdelrhman, Ahmed M.; Sei Kien, Yong; Salman Leong, M.; Meng Hee, Lim; Al-Obaidi, Salah M. Ali

2017-07-01

The vibration signals produced by rotating machinery contain useful information for condition monitoring and fault diagnosis. Fault severities assessment is a challenging task. Wavelet Transform (WT) as a multivariate analysis tool is able to compromise between the time and frequency information in the signals and served as a de-noising method. The CWT scaling function gives different resolutions to the discretely signals such as very fine resolution at lower scale but coarser resolution at a higher scale. However, the computational cost increased as it needs to produce different signal resolutions. DWT has better low computation cost as the dilation function allowed the signals to be decomposed through a tree of low and high pass filters and no further analysing the high-frequency components. In this paper, a method for bearing faults identification is presented by combing Continuous Wavelet Transform (CWT) and Discrete Wavelet Transform (DWT) with envelope analysis for bearing fault diagnosis. The experimental data was sampled by Case Western Reserve University. The analysis result showed that the proposed method is effective in bearing faults detection, identify the exact fault’s location and severity assessment especially for the inner race and outer race faults.

Differential pulse amplitude modulation for multiple-input single-output OWVLC

NASA Astrophysics Data System (ADS)

Yang, S. H.; Kwon, D. H.; Kim, S. J.; Son, Y. H.; Han, S. K.

2015-01-01

White light-emitting diodes (LEDs) are widely used for lighting due to their energy efficiency, eco-friendly, and small size than previously light sources such as incandescent, fluorescent bulbs and so on. Optical wireless visible light communication (OWVLC) based on LED merges lighting and communications in applications such as indoor lighting, traffic signals, vehicles, and underwater communications because LED can be easily modulated. However, physical bandwidth of LED is limited about several MHz by slow time constant of the phosphor and characteristics of device. Therefore, using the simplest modulation format which is non-return-zero on-off-keying (NRZ-OOK), the data rate reaches only to dozens Mbit/s. Thus, to improve the transmission capacity, optical filtering and pre-, post-equalizer are adapted. Also, high-speed wireless connectivity is implemented using spectrally efficient modulation methods: orthogonal frequency division multiplexing (OFDM) or discrete multi-tone (DMT). However, these modulation methods need additional digital signal processing such as FFT and IFFT, thus complexity of transmitter and receiver is increasing. To reduce the complexity of transmitter and receiver, we proposed a novel modulation scheme which is named differential pulse amplitude modulation. The proposed modulation scheme transmits different NRZ-OOK signals with same amplitude and unit time delay using each LED chip, respectively. The `N' parallel signals from LEDs are overlapped and directly detected at optical receiver. Received signal is demodulated by power difference between unit time slots. The proposed scheme can overcome the bandwidth limitation of LEDs and data rate can be improved according to number of LEDs without complex digital signal processing.

Discrete post-processing of total cloud cover ensemble forecasts

NASA Astrophysics Data System (ADS)

Hemri, Stephan; Haiden, Thomas; Pappenberger, Florian

2017-04-01

This contribution presents an approach to post-process ensemble forecasts for the discrete and bounded weather variable of total cloud cover. Two methods for discrete statistical post-processing of ensemble predictions are tested. The first approach is based on multinomial logistic regression, the second involves a proportional odds logistic regression model. Applying them to total cloud cover raw ensemble forecasts from the European Centre for Medium-Range Weather Forecasts improves forecast skill significantly. Based on station-wise post-processing of raw ensemble total cloud cover forecasts for a global set of 3330 stations over the period from 2007 to early 2014, the more parsimonious proportional odds logistic regression model proved to slightly outperform the multinomial logistic regression model. Reference Hemri, S., Haiden, T., & Pappenberger, F. (2016). Discrete post-processing of total cloud cover ensemble forecasts. Monthly Weather Review 144, 2565-2577.

Digitally controlled distributed phase shifter

DOEpatents

Hietala, V.M.; Kravitz, S.H.; Vawter, G.A.

1993-08-17

A digitally controlled distributed phase shifter is comprised of N phase shifters. Digital control is achieved by using N binary length-weighted electrodes located on the top surface of a waveguide. A control terminal is attached to each electrode thereby allowing the application of a control signal. The control signal is either one or two discrete bias voltages. The application of the discrete bias voltages changes the modal index of a portion of the waveguide that corresponds to a length of the electrode to which the bias voltage is applied, thereby causing the phase to change through the underlying portion of the waveguide. The digitally controlled distributed phase shift network has a total phase shift comprised of the sum of the individual phase shifters.

Digitally controlled distributed phase shifter

DOEpatents

Hietala, Vincent M.; Kravitz, Stanley H.; Vawter, Gregory A.

1993-01-01

A digitally controlled distributed phase shifter is comprised of N phase shifters. Digital control is achieved by using N binary length-weighted electrodes located on the top surface of a waveguide. A control terminal is attached to each electrode thereby allowing the application of a control signal. The control signal is either one or two discrete bias voltages. The application of the discrete bias voltages changes the modal index of a portion of the waveguide that corresponds to a length of the electrode to which the bias voltage is applied, thereby causing the phase to change through the underlying portion of the waveguide. The digitally controlled distributed phase shift network has a total phase shift comprised of the sum of the individual phase shifters.

Penetrating transmission zeros in the design of robust servomechanism systems

NASA Technical Reports Server (NTRS)

Wang, S. H.; Davison, E. J.

1981-01-01

In the design of a robust servomechanism system, it is well known that the system cannot track a reference signal whose frequency coincides with the transmission zeros of the system. This paper proposes a new design method for overcoming this difficulty. The controller to be used employs a sampler and holding device with exponential decay. It is shown that the transmission zeros of the discretized system can be shifted by changing the rate of the exponential decay of the holding device. Thus, it is possible to design a robust controller for the discretized system to track any reference signal of given frequency, even if the given frequency coincides with the transmission zeros of the original continuous-time system.

Image compression-encryption algorithms by combining hyper-chaotic system with discrete fractional random transform

NASA Astrophysics Data System (ADS)

Gong, Lihua; Deng, Chengzhi; Pan, Shumin; Zhou, Nanrun

2018-07-01

Based on hyper-chaotic system and discrete fractional random transform, an image compression-encryption algorithm is designed. The original image is first transformed into a spectrum by the discrete cosine transform and the resulting spectrum is compressed according to the method of spectrum cutting. The random matrix of the discrete fractional random transform is controlled by a chaotic sequence originated from the high dimensional hyper-chaotic system. Then the compressed spectrum is encrypted by the discrete fractional random transform. The order of DFrRT and the parameters of the hyper-chaotic system are the main keys of this image compression and encryption algorithm. The proposed algorithm can compress and encrypt image signal, especially can encrypt multiple images once. To achieve the compression of multiple images, the images are transformed into spectra by the discrete cosine transform, and then the spectra are incised and spliced into a composite spectrum by Zigzag scanning. Simulation results demonstrate that the proposed image compression and encryption algorithm is of high security and good compression performance.

Cortical Neural Computation by Discrete Results Hypothesis

PubMed Central

Castejon, Carlos; Nuñez, Angel

2016-01-01

One of the most challenging problems we face in neuroscience is to understand how the cortex performs computations. There is increasing evidence that the power of the cortical processing is produced by populations of neurons forming dynamic neuronal ensembles. Theoretical proposals and multineuronal experimental studies have revealed that ensembles of neurons can form emergent functional units. However, how these ensembles are implicated in cortical computations is still a mystery. Although cell ensembles have been associated with brain rhythms, the functional interaction remains largely unclear. It is still unknown how spatially distributed neuronal activity can be temporally integrated to contribute to cortical computations. A theoretical explanation integrating spatial and temporal aspects of cortical processing is still lacking. In this Hypothesis and Theory article, we propose a new functional theoretical framework to explain the computational roles of these ensembles in cortical processing. We suggest that complex neural computations underlying cortical processing could be temporally discrete and that sensory information would need to be quantized to be computed by the cerebral cortex. Accordingly, we propose that cortical processing is produced by the computation of discrete spatio-temporal functional units that we have called “Discrete Results” (Discrete Results Hypothesis). This hypothesis represents a novel functional mechanism by which information processing is computed in the cortex. Furthermore, we propose that precise dynamic sequences of “Discrete Results” is the mechanism used by the cortex to extract, code, memorize and transmit neural information. The novel “Discrete Results” concept has the ability to match the spatial and temporal aspects of cortical processing. We discuss the possible neural underpinnings of these functional computational units and describe the empirical evidence supporting our hypothesis. We propose that fast-spiking (FS) interneuron may be a key element in our hypothesis providing the basis for this computation. PMID:27807408

Cortical Neural Computation by Discrete Results Hypothesis.

PubMed

Castejon, Carlos; Nuñez, Angel

2016-01-01

One of the most challenging problems we face in neuroscience is to understand how the cortex performs computations. There is increasing evidence that the power of the cortical processing is produced by populations of neurons forming dynamic neuronal ensembles. Theoretical proposals and multineuronal experimental studies have revealed that ensembles of neurons can form emergent functional units. However, how these ensembles are implicated in cortical computations is still a mystery. Although cell ensembles have been associated with brain rhythms, the functional interaction remains largely unclear. It is still unknown how spatially distributed neuronal activity can be temporally integrated to contribute to cortical computations. A theoretical explanation integrating spatial and temporal aspects of cortical processing is still lacking. In this Hypothesis and Theory article, we propose a new functional theoretical framework to explain the computational roles of these ensembles in cortical processing. We suggest that complex neural computations underlying cortical processing could be temporally discrete and that sensory information would need to be quantized to be computed by the cerebral cortex. Accordingly, we propose that cortical processing is produced by the computation of discrete spatio-temporal functional units that we have called "Discrete Results" (Discrete Results Hypothesis). This hypothesis represents a novel functional mechanism by which information processing is computed in the cortex. Furthermore, we propose that precise dynamic sequences of "Discrete Results" is the mechanism used by the cortex to extract, code, memorize and transmit neural information. The novel "Discrete Results" concept has the ability to match the spatial and temporal aspects of cortical processing. We discuss the possible neural underpinnings of these functional computational units and describe the empirical evidence supporting our hypothesis. We propose that fast-spiking (FS) interneuron may be a key element in our hypothesis providing the basis for this computation.

Electromyography (EMG) signal recognition using combined discrete wavelet transform based adaptive neuro-fuzzy inference systems (ANFIS)

NASA Astrophysics Data System (ADS)

Arozi, Moh; Putri, Farika T.; Ariyanto, Mochammad; Khusnul Ari, M.; Munadi, Setiawan, Joga D.

2017-01-01

People with disabilities are increasing from year to year either due to congenital factors, sickness, accident factors and war. One form of disability is the case of interruptions of hand function. The condition requires and encourages the search for solutions in the form of creating an artificial hand with the ability as a human hand. The development of science in the field of neuroscience currently allows the use of electromyography (EMG) to control the motion of artificial prosthetic hand into the necessary use of EMG as an input signal to control artificial prosthetic hand. This study is the beginning of a significant research planned in the development of artificial prosthetic hand with EMG signal input. This initial research focused on the study of EMG signal recognition. Preliminary results show that the EMG signal recognition using combined discrete wavelet transform and Adaptive Neuro-Fuzzy Inference System (ANFIS) produces accuracy 98.3 % for training and 98.51% for testing. Thus the results can be used as an input signal for Simulink block diagram of a prosthetic hand that will be developed on next study. The research will proceed with the construction of artificial prosthetic hand along with Simulink program controlling and integrating everything into one system.

Induction motors airgap-eccentricity detection through the discrete wavelet transform of the apparent power signal under non-stationary operating conditions.

PubMed

Yahia, K; Cardoso, A J M; Ghoggal, A; Zouzou, S E

2014-03-01

Fast Fourier transform (FFT) analysis has been successfully used for fault diagnosis in induction machines. However, this method does not always provide good results for the cases of load torque, speed and voltages variation, leading to a variation of the motor-slip and the consequent FFT problems that appear due to the non-stationary nature of the involved signals. In this paper, the discrete wavelet transform (DWT) of the apparent-power signal for the airgap-eccentricity fault detection in three-phase induction motors is presented in order to overcome the above FFT problems. The proposed method is based on the decomposition of the apparent-power signal from which wavelet approximation and detail coefficients are extracted. The energy evaluation of a known bandwidth permits to define a fault severity factor (FSF). Simulation as well as experimental results are provided to illustrate the effectiveness and accuracy of the proposed method presented even for the case of load torque variations. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

Ensemble-type numerical uncertainty information from single model integrations

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

Rauser, Florian, E-mail: florian.rauser@mpimet.mpg.de; Marotzke, Jochem; Korn, Peter

2015-07-01

We suggest an algorithm that quantifies the discretization error of time-dependent physical quantities of interest (goals) for numerical models of geophysical fluid dynamics. The goal discretization error is estimated using a sum of weighted local discretization errors. The key feature of our algorithm is that these local discretization errors are interpreted as realizations of a random process. The random process is determined by the model and the flow state. From a class of local error random processes we select a suitable specific random process by integrating the model over a short time interval at different resolutions. The weights of themore » influences of the local discretization errors on the goal are modeled as goal sensitivities, which are calculated via automatic differentiation. The integration of the weighted realizations of local error random processes yields a posterior ensemble of goal approximations from a single run of the numerical model. From the posterior ensemble we derive the uncertainty information of the goal discretization error. This algorithm bypasses the requirement of detailed knowledge about the models discretization to generate numerical error estimates. The algorithm is evaluated for the spherical shallow-water equations. For two standard test cases we successfully estimate the error of regional potential energy, track its evolution, and compare it to standard ensemble techniques. The posterior ensemble shares linear-error-growth properties with ensembles of multiple model integrations when comparably perturbed. The posterior ensemble numerical error estimates are of comparable size as those of a stochastic physics ensemble.« less

Discrete fourier transform (DFT) analysis for applications using iterative transform methods

NASA Technical Reports Server (NTRS)

Dean, Bruce H. (Inventor)

2012-01-01

According to various embodiments, a method is provided for determining aberration data for an optical system. The method comprises collecting a data signal, and generating a pre-transformation algorithm. The data is pre-transformed by multiplying the data with the pre-transformation algorithm. A discrete Fourier transform of the pre-transformed data is performed in an iterative loop. The method further comprises back-transforming the data to generate aberration data.

Modeling borehole microseismic and strain signals measured by a distributed fiber optic sensor

NASA Astrophysics Data System (ADS)

Mellors, R. J.; Sherman, C. S.; Ryerson, F. J.; Morris, J.; Allen, G. S.; Messerly, M. J.; Carr, T.; Kavousi, P.

2017-12-01

The advent of distributed fiber optic sensors installed in boreholes provides a new and data-rich perspective on the subsurface environment. This includes the long-term capability for vertical seismic profiles, monitoring of active borehole processes such as well stimulation, and measuring of microseismic signals. The distributed fiber sensor, which measures strain (or strain-rate), is an active sensor with highest sensitivity parallel to the fiber and subject to varying types of noise, both external and internal. We take a systems approach and include the response of the electronics, fiber/cable, and subsurface to improve interpretation of the signals. This aids in understanding noise sources, assessing error bounds on amplitudes, and developing appropriate algorithms for improving the image. Ultimately, a robust understanding will allow identification of areas for future improvement and possible optimization in fiber and cable design. The subsurface signals are simulated in two ways: 1) a massively parallel multi-physics code that is capable of modeling hydraulic stimulation of heterogeneous reservoir with a pre-existing discrete fracture network, and 2) a parallelized 3D finite difference code for high-frequency seismic signals. Geometry and parameters for the simulations are derived from fiber deployments, including the Marcellus Shale Energy and Environment Laboratory (MSEEL) project in West Virginia. The combination mimics both the low-frequency strain signals generated during the fracture process and high-frequency signals from microseismic and perforation shots. Results are compared with available fiber data and demonstrate that quantitative interpretation of the fiber data provides valuable constraints on the fracture geometry and microseismic activity. These constraints appear difficult, if not impossible, to obtain otherwise.

Development of signal processing system of avalanche photo diode for space observations by Astro-H

NASA Astrophysics Data System (ADS)

Ohno, M.; Goto, K.; Hanabata, Y.; Takahashi, H.; Fukazawa, Y.; Yoshino, M.; Saito, T.; Nakamori, T.; Kataoka, J.; Sasano, M.; Torii, S.; Uchiyama, H.; Nakazawa, K.; Watanabe, S.; Kokubun, M.; Ohta, M.; Sato, T.; Takahashi, T.; Tajima, H.

2013-01-01

Astro-H is the sixth Japanese X-ray space observatory which will be launched in 2014. Two of onboard instruments of Astro-H, Hard X-ray Imager and Soft Gamma-ray Detector are surrounded by many number of large Bismuth Germanate (Bi4Ge3O12; BGO) scintillators. Optimum readout system of scintillation lights from these BGOs are essential to reduce the background signals and achieve high performance for main detectors because most of gamma-rays from out of field-of-view of main detectors or radio-isotopes produced inside them due to activation can be eliminated by anti-coincidence technique using BGO signals. We apply Avalanche Photo Diode (APD) for light sensor of these BGO detectors since their compactness and high quantum efficiency make it easy to design such large number of BGO detector system. For signal processing from APDs, digital filter and other trigger logics on the Field-Programmable Gate Array (FPGA) is used instead of discrete analog circuits due to limitation of circuit implementation area on spacecraft. For efficient observations, we have to achieve as low threshold of anti-coincidence signal as possible by utilizing the digital filtering. In addition, such anti-coincident signals should be sent to the main detector within 5 μs to make it in time to veto the A-D conversion. Considering this requirement and constraint from logic size of FPGA, we adopt two types of filter, 8 delay taps filter with only 2 bit precision coefficient and 16 delay taps filter with 8 bit precision coefficient. The data after former simple filter provides anti-coincidence signal quickly in orbit, and the latter filter is used for detail analysis after the data is down-linked.

Erythropoietin Receptor Signaling Is Membrane Raft Dependent

PubMed Central

McGraw, Kathy L.; Fuhler, Gwenny M.; Johnson, Joseph O.; Clark, Justine A.; Caceres, Gisela C.; Sokol, Lubomir; List, Alan F.

2012-01-01

Upon erythropoietin (Epo) engagement, Epo-receptor (R) homodimerizes to activate JAK2 and Lyn, which phosphorylate STAT5. Although recent investigations have identified key negative regulators of Epo-R signaling, little is known about the role of membrane localization in controlling receptor signal fidelity. Here we show a critical role for membrane raft (MR) microdomains in creation of discrete signaling platforms essential for Epo-R signaling. Treatment of UT7 cells with Epo induced MR assembly and coalescence. Confocal microscopy showed that raft aggregates significantly increased after Epo stimulation (mean, 4.3±1.4(SE) vs. 25.6±3.2 aggregates/cell; p≤0.001), accompanied by a >3-fold increase in cluster size (p≤0.001). Raft fraction immunoblotting showed Epo-R translocation to MR after Epo stimulation and was confirmed by fluorescence microscopy in Epo stimulated UT7 cells and primary erythroid bursts. Receptor recruitment into MR was accompanied by incorporation of JAK2, Lyn, and STAT5 and their activated forms. Raft disruption by cholesterol depletion extinguished Epo induced Jak2, STAT5, Akt and MAPK phosphorylation in UT7 cells and erythroid progenitors. Furthermore, inhibition of the Rho GTPases Rac1 or RhoA blocked receptor recruitment into raft fractions, indicating a role for these GTPases in receptor trafficking. These data establish a critical role for MR in recruitment and assembly of Epo-R and signal intermediates into discrete membrane signaling units. PMID:22509308

Control of discrete time systems based on recurrent Super-Twisting-like algorithm.

PubMed

Salgado, I; Kamal, S; Bandyopadhyay, B; Chairez, I; Fridman, L

2016-09-01

Most of the research in sliding mode theory has been carried out to in continuous time to solve the estimation and control problems. However, in discrete time, the results in high order sliding modes have been less developed. In this paper, a discrete time super-twisting-like algorithm (DSTA) was proposed to solve the problems of control and state estimation. The stability proof was developed in terms of the discrete time Lyapunov approach and the linear matrix inequalities theory. The system trajectories were ultimately bounded inside a small region dependent on the sampling period. Simulation results tested the DSTA. The DSTA was applied as a controller for a Furuta pendulum and for a DC motor supplied by a DSTA signal differentiator. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

FPGA-Based Front-End Electronics for Positron Emission Tomography

PubMed Central

Haselman, Michael; DeWitt, Don; McDougald, Wendy; Lewellen, Thomas K.; Miyaoka, Robert; Hauck, Scott

2010-01-01

Modern Field Programmable Gate Arrays (FPGAs) are capable of performing complex discrete signal processing algorithms with clock rates above 100MHz. This combined with FPGA’s low expense, ease of use, and selected dedicated hardware make them an ideal technology for a data acquisition system for positron emission tomography (PET) scanners. Our laboratory is producing a high-resolution, small-animal PET scanner that utilizes FPGAs as the core of the front-end electronics. For this next generation scanner, functions that are typically performed in dedicated circuits, or offline, are being migrated to the FPGA. This will not only simplify the electronics, but the features of modern FPGAs can be utilizes to add significant signal processing power to produce higher resolution images. In this paper two such processes, sub-clock rate pulse timing and event localization, will be discussed in detail. We show that timing performed in the FPGA can achieve a resolution that is suitable for small-animal scanners, and will outperform the analog version given a low enough sampling period for the ADC. We will also show that the position of events in the scanner can be determined in real time using a statistical positioning based algorithm. PMID:21961085

Comparing performance in discrete and continuous comparison tasks.

PubMed

Leibovich, Tali; Henik, Avishai

2014-05-01

The approximate number system (ANS) theory suggests that all magnitudes, discrete (i.e., number of items) or continuous (i.e., size, density, etc.), are processed by a shared system and comply with Weber's law. The current study reexamined this notion by comparing performance in discrete (comparing numerosities of dot arrays) and continuous (comparisons of area of squares) tasks. We found that: (a) threshold of discrimination was higher for continuous than for discrete comparisons; (b) while performance in the discrete task complied with Weber's law, performance in the continuous task violated it; and (c) performance in the discrete task was influenced by continuous properties (e.g., dot density, dot cumulative area) of the dot array that were not predictive of numerosities or task relevant. Therefore, we propose that the magnitude processing system (MPS) is actually divided into separate (yet interactive) systems for discrete and continuous magnitude processing. Further subdivisions are discussed. We argue that cooperation between these systems results in a holistic comparison of magnitudes, one that takes into account continuous properties in addition to numerosities. Considering the MPS as two systems opens the door to new and important questions that shed light on both normal and impaired development of the numerical system.

Noise deconvolution based on the L1-metric and decomposition of discrete distributions of postsynaptic responses.

PubMed

Astrelin, A V; Sokolov, M V; Behnisch, T; Reymann, K G; Voronin, L L

1997-04-25

A statistical approach to analysis of amplitude fluctuations of postsynaptic responses is described. This includes (1) using a L1-metric in the space of distribution functions for minimisation with application of linear programming methods to decompose amplitude distributions into a convolution of Gaussian and discrete distributions; (2) deconvolution of the resulting discrete distribution with determination of the release probabilities and the quantal amplitude for cases with a small number (< 5) of discrete components. The methods were tested against simulated data over a range of sample sizes and signal-to-noise ratios which mimicked those observed in physiological experiments. In computer simulation experiments, comparisons were made with other methods of 'unconstrained' (generalized) and constrained reconstruction of discrete components from convolutions. The simulation results provided additional criteria for improving the solutions to overcome 'over-fitting phenomena' and to constrain the number of components with small probabilities. Application of the programme to recordings from hippocampal neurones demonstrated its usefulness for the analysis of amplitude distributions of postsynaptic responses.

Superfast algorithms of multidimensional discrete k-wave transforms and Volterra filtering based on superfast radon transform

NASA Astrophysics Data System (ADS)

Labunets, Valeri G.; Labunets-Rundblad, Ekaterina V.; Astola, Jaakko T.

2001-12-01

Fast algorithms for a wide class of non-separable n-dimensional (nD) discrete unitary K-transforms (DKT) are introduced. They need less 1D DKTs than in the case of the classical radix-2 FFT-type approach. The method utilizes a decomposition of the nD K-transform into the product of a new nD discrete Radon transform and of a set of parallel/independ 1D K-transforms. If the nD K-transform has a separable kernel (e.g., the case of the discrete Fourier transform) our approach leads to decrease of multiplicative complexity by the factor of n comparing to the classical row/column separable approach. It is well known that an n-th order Volterra filter of one dimensional signal can be evaluated by an appropriate nD linear convolution. This work describes new superfast algorithm for Volterra filtering. New approach is based on the superfast discrete Radon and Nussbaumer polynomial transforms.

Stochastic Dual Algorithm for Voltage Regulation in Distribution Networks with Discrete Loads: Preprint

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

Dall-Anese, Emiliano; Zhou, Xinyang; Liu, Zhiyuan

This paper considers distribution networks with distributed energy resources and discrete-rate loads, and designs an incentive-based algorithm that allows the network operator and the customers to pursue given operational and economic objectives, while concurrently ensuring that voltages are within prescribed limits. Four major challenges include: (1) the non-convexity from discrete decision variables, (2) the non-convexity due to a Stackelberg game structure, (3) unavailable private information from customers, and (4) different update frequency from two types of devices. In this paper, we first make convex relaxation for discrete variables, then reformulate the non-convex structure into a convex optimization problem together withmore » pricing/reward signal design, and propose a distributed stochastic dual algorithm for solving the reformulated problem while restoring feasible power rates for discrete devices. By doing so, we are able to statistically achieve the solution of the reformulated problem without exposure of any private information from customers. Stability of the proposed schemes is analytically established and numerically corroborated.« less

Discrete Data Qualification System and Method Comprising Noise Series Fault Detection

NASA Technical Reports Server (NTRS)

Fulton, Christopher; Wong, Edmond; Melcher, Kevin; Bickford, Randall

2013-01-01

A Sensor Data Qualification (SDQ) function has been developed that allows the onboard flight computers on NASA s launch vehicles to determine the validity of sensor data to ensure that critical safety and operational decisions are not based on faulty sensor data. This SDQ function includes a novel noise series fault detection algorithm for qualification of the output data from LO2 and LH2 low-level liquid sensors. These sensors are positioned in a launch vehicle s propellant tanks in order to detect propellant depletion during a rocket engine s boost operating phase. This detection capability can prevent the catastrophic situation where the engine operates without propellant. The output from each LO2 and LH2 low-level liquid sensor is a discrete valued signal that is expected to be in either of two states, depending on whether the sensor is immersed (wet) or exposed (dry). Conventional methods for sensor data qualification, such as threshold limit checking, are not effective for this type of signal due to its discrete binary-state nature. To address this data qualification challenge, a noise computation and evaluation method, also known as a noise fault detector, was developed to detect unreasonable statistical characteristics in the discrete data stream. The method operates on a time series of discrete data observations over a moving window of data points and performs a continuous examination of the resulting observation stream to identify the presence of anomalous characteristics. If the method determines the existence of anomalous results, the data from the sensor is disqualified for use by other monitoring or control functions.

Donders revisited: Discrete or continuous temporal processing underlying reaction time distributions?

PubMed

Bao, Yan; Yang, Taoxi; Lin, Xiaoxiong; Pöppel, Ernst

2016-09-01

Differences of reaction times to specific stimulus configurations are used as indicators of cognitive processing stages. In this classical experimental paradigm, continuous temporal processing is implicitly assumed. Multimodal response distributions indicate, however, discrete time sampling, which is often masked by experimental conditions. Differences in reaction times reflect discrete temporal mechanisms that are pre-semantically implemented and suggested to be based on entrained neural oscillations. © 2016 The Institute of Psychology, Chinese Academy of Sciences and John Wiley & Sons Australia, Ltd.

BOOK REVIEW: The Illustrated Wavelet Transform Handbook: Introductory Theory and Applications in Science, Engineering, Medicine and Finance

NASA Astrophysics Data System (ADS)

Ng, J.; Kingsbury, N. G.

2004-02-01

This book provides an overview of the theory and practice of continuous and discrete wavelet transforms. Divided into seven chapters, the first three chapters of the book are introductory, describing the various forms of the wavelet transform and their computation, while the remaining chapters are devoted to applications in fluids, engineering, medicine and miscellaneous areas. Each chapter is well introduced, with suitable examples to demonstrate key concepts. Illustrations are included where appropriate, thus adding a visual dimension to the text. A noteworthy feature is the inclusion, at the end of each chapter, of a list of further resources from the academic literature which the interested reader can consult. The first chapter is purely an introduction to the text. The treatment of wavelet transforms begins in the second chapter, with the definition of what a wavelet is. The chapter continues by defining the continuous wavelet transform and its inverse and a description of how it may be used to interrogate signals. The continuous wavelet transform is then compared to the short-time Fourier transform. Energy and power spectra with respect to scale are also discussed and linked to their frequency counterparts. Towards the end of the chapter, the two-dimensional continuous wavelet transform is introduced. Examples of how the continuous wavelet transform is computed using the Mexican hat and Morlet wavelets are provided throughout. The third chapter introduces the discrete wavelet transform, with its distinction from the discretized continuous wavelet transform having been made clear at the end of the second chapter. In the first half of the chapter, the logarithmic discretization of the wavelet function is described, leading to a discussion of dyadic grid scaling, frames, orthogonal and orthonormal bases, scaling functions and multiresolution representation. The fast wavelet transform is introduced and its computation is illustrated with an example using the Haar wavelet. The second half of the chapter groups together miscellaneous points about the discrete wavelet transform, including coefficient manipulation for signal denoising and smoothing, a description of Daubechies’ wavelets, the properties of translation invariance and biorthogonality, the two-dimensional discrete wavelet transforms and wavelet packets. The fourth chapter is dedicated to wavelet transform methods in the author’s own specialty, fluid mechanics. Beginning with a definition of wavelet-based statistical measures for turbulence, the text proceeds to describe wavelet thresholding in the analysis of fluid flows. The remainder of the chapter describes wavelet analysis of engineering flows, in particular jets, wakes, turbulence and coherent structures, and geophysical flows, including atmospheric and oceanic processes. The fifth chapter describes the application of wavelet methods in various branches of engineering, including machining, materials, dynamics and information engineering. Unlike previous chapters, this (and subsequent) chapters are styled more as literature reviews that describe the findings of other authors. The areas addressed in this chapter include: the monitoring of machining processes, the monitoring of rotating machinery, dynamical systems, chaotic systems, non-destructive testing, surface characterization and data compression. The sixth chapter continues in this vein with the attention now turned to wavelets in the analysis of medical signals. Most of the chapter is devoted to the analysis of one-dimensional signals (electrocardiogram, neural waveforms, acoustic signals etc.), although there is a small section on the analysis of two-dimensional medical images. The seventh and final chapter of the book focuses on the application of wavelets in three seemingly unrelated application areas: fractals, finance and geophysics. The treatment on wavelet methods in fractals focuses on stochastic fractals with a short section on multifractals. The treatment on finance touches on the use of wavelets by other authors in studying stock prices, commodity behaviour, market dynamics and foreign exchange rates. The treatment on geophysics covers what was omitted from the fourth chapter, namely, seismology, well logging, topographic feature analysis and the analysis of climatic data. The text concludes with an assortment of other application areas which could only be mentioned in passing. Unlike most other publications in the subject, this book does not treat wavelet transforms in a mathematically rigorous manner but rather aims to explain the mechanics of the wavelet transform in a way that is easy to understand. Consequently, it serves as an excellent overview of the subject rather than as a reference text. Keeping the mathematics to a minimum and omitting cumbersome and detailed proofs from the text, the book is best-suited to those who are new to wavelets or who want an intuitive understanding of the subject. Such an audience may include graduate students in engineering and professionals and researchers in engineering and the applied sciences.

Effects of sequential and discrete rapid naming on reading in Japanese children with reading difficulty.

PubMed

Wakamiya, Eiji; Okumura, Tomohito; Nakanishi, Makoto; Takeshita, Takashi; Mizuta, Mekumi; Kurimoto, Naoko; Tamai, Hiroshi

2011-06-01

To clarify whether rapid naming ability itself is a main underpinning factor of rapid automatized naming tests (RAN) and how deep an influence the discrete decoding process has on reading, we performed discrete naming tasks and discrete hiragana reading tasks as well as sequential naming tasks and sequential hiragana reading tasks with 38 Japanese schoolchildren with reading difficulty. There were high correlations between both discrete and sequential hiragana reading and sentence reading, suggesting that some mechanism which automatizes hiragana reading makes sentence reading fluent. In object and color tasks, there were moderate correlations between sentence reading and sequential naming, and between sequential naming and discrete naming. But no correlation was found between reading tasks and discrete naming tasks. The influence of rapid naming ability of objects and colors upon reading seemed relatively small, and multi-item processing may work in relation to these. In contrast, in the digit naming task there was moderate correlation between sentence reading and discrete naming, while no correlation was seen between sequential naming and discrete naming. There was moderate correlation between reading tasks and sequential digit naming tasks. Digit rapid naming ability has more direct effect on reading while its effect on RAN is relatively limited. The ratio of how rapid naming ability influences RAN and reading seems to vary according to kind of the stimuli used. An assumption about components in RAN which influence reading is discussed in the context of both sequential processing and discrete naming speed. Copyright © 2010 The Japanese Society of Child Neurology. Published by Elsevier B.V. All rights reserved.

Development of gradient descent adaptive algorithms to remove common mode artifact for improvement of cardiovascular signal quality.

PubMed

Ciaccio, Edward J; Micheli-Tzanakou, Evangelia

2007-07-01

Common-mode noise degrades cardiovascular signal quality and diminishes measurement accuracy. Filtering to remove noise components in the frequency domain often distorts the signal. Two adaptive noise canceling (ANC) algorithms were tested to adjust weighted reference signals for optimal subtraction from a primary signal. Update of weight w was based upon the gradient term of the steepest descent equation: [see text], where the error epsilon is the difference between primary and weighted reference signals. nabla was estimated from Deltaepsilon(2) and Deltaw without using a variable Deltaw in the denominator which can cause instability. The Parallel Comparison (PC) algorithm computed Deltaepsilon(2) using fixed finite differences +/- Deltaw in parallel during each discrete time k. The ALOPEX algorithm computed Deltaepsilon(2)x Deltaw from time k to k + 1 to estimate nabla, with a random number added to account for Deltaepsilon(2) . Deltaw--> 0 near the optimal weighting. Using simulated data, both algorithms stably converged to the optimal weighting within 50-2000 discrete sample points k even with a SNR = 1:8 and weights which were initialized far from the optimal. Using a sharply pulsatile cardiac electrogram signal with added noise so that the SNR = 1:5, both algorithms exhibited stable convergence within 100 ms (100 sample points). Fourier spectral analysis revealed minimal distortion when comparing the signal without added noise to the ANC restored signal. ANC algorithms based upon difference calculations can rapidly and stably converge to the optimal weighting in simulated and real cardiovascular data. Signal quality is restored with minimal distortion, increasing the accuracy of biophysical measurement.

Differential morphology and image processing.

PubMed

Maragos, P

1996-01-01

Image processing via mathematical morphology has traditionally used geometry to intuitively understand morphological signal operators and set or lattice algebra to analyze them in the space domain. We provide a unified view and analytic tools for morphological image processing that is based on ideas from differential calculus and dynamical systems. This includes ideas on using partial differential or difference equations (PDEs) to model distance propagation or nonlinear multiscale processes in images. We briefly review some nonlinear difference equations that implement discrete distance transforms and relate them to numerical solutions of the eikonal equation of optics. We also review some nonlinear PDEs that model the evolution of multiscale morphological operators and use morphological derivatives. Among the new ideas presented, we develop some general 2-D max/min-sum difference equations that model the space dynamics of 2-D morphological systems (including the distance computations) and some nonlinear signal transforms, called slope transforms, that can analyze these systems in a transform domain in ways conceptually similar to the application of Fourier transforms to linear systems. Thus, distance transforms are shown to be bandpass slope filters. We view the analysis of the multiscale morphological PDEs and of the eikonal PDE solved via weighted distance transforms as a unified area in nonlinear image processing, which we call differential morphology, and briefly discuss its potential applications to image processing and computer vision.

Dynamic measurements of CO diffusing capacity using discrete samples of alveolar gas.

PubMed

Graham, B L; Mink, J T; Cotton, D J

1983-01-01

It has been shown that measurements of the diffusing capacity of the lung for CO made during a slow exhalation [DLCO(exhaled)] yield information about the distribution of the diffusing capacity in the lung that is not available from the commonly measured single-breath diffusing capacity [DLCO(SB)]. Current techniques of measuring DLCO(exhaled) require the use of a rapid-responding (less than 240 ms, 10-90%) CO meter to measure the CO concentration in the exhaled gas continuously during exhalation. DLCO(exhaled) is then calculated using two sample points in the CO signal. Because DLCO(exhaled) calculations are highly affected by small amounts of noise in the CO signal, filtering techniques have been used to reduce noise. However, these techniques reduce the response time of the system and may introduce other errors into the signal. We have developed an alternate technique in which DLCO(exhaled) can be calculated using the concentration of CO in large discrete samples of the exhaled gas, thus eliminating the requirement of a rapid response time in the CO analyzer. We show theoretically that this method is as accurate as other DLCO(exhaled) methods but is less affected by noise. These findings are verified in comparisons of the discrete-sample method of calculating DLCO(exhaled) to point-sample methods in normal subjects, patients with emphysema, and patients with asthma.

A neuronal model of a global workspace in effortful cognitive tasks.

PubMed

Dehaene, S; Kerszberg, M; Changeux, J P

1998-11-24

A minimal hypothesis is proposed concerning the brain processes underlying effortful tasks. It distinguishes two main computational spaces: a unique global workspace composed of distributed and heavily interconnected neurons with long-range axons, and a set of specialized and modular perceptual, motor, memory, evaluative, and attentional processors. Workspace neurons are mobilized in effortful tasks for which the specialized processors do not suffice. They selectively mobilize or suppress, through descending connections, the contribution of specific processor neurons. In the course of task performance, workspace neurons become spontaneously coactivated, forming discrete though variable spatio-temporal patterns subject to modulation by vigilance signals and to selection by reward signals. A computer simulation of the Stroop task shows workspace activation to increase during acquisition of a novel task, effortful execution, and after errors. We outline predictions for spatio-temporal activation patterns during brain imaging, particularly about the contribution of dorsolateral prefrontal cortex and anterior cingulate to the workspace.

Research on the Filtering Algorithm in Speed and Position Detection of Maglev Trains

PubMed Central

Dai, Chunhui; Long, Zhiqiang; Xie, Yunde; Xue, Song

2011-01-01

This paper introduces in brief the traction system of a permanent magnet electrodynamic suspension (EDS) train. The synchronous traction mode based on long stators and track cable is described. A speed and position detection system is recommended. It is installed on board and is used as the feedback end. Restricted by the maglev train’s structure, the permanent magnet electrodynamic suspension (EDS) train uses the non-contact method to detect its position. Because of the shake and the track joints, the position signal sent by the position sensor is always aberrant and noisy. To solve this problem, a linear discrete track-differentiator filtering algorithm is proposed. The filtering characters of the track-differentiator (TD) and track-differentiator group are analyzed. The four series of TD are used in the signal processing unit. The result shows that the track-differentiator could have a good effect and make the traction system run normally. PMID:22164012

Research on the filtering algorithm in speed and position detection of maglev trains.

PubMed

Dai, Chunhui; Long, Zhiqiang; Xie, Yunde; Xue, Song

2011-01-01

This paper introduces in brief the traction system of a permanent magnet electrodynamic suspension (EDS) train. The synchronous traction mode based on long stators and track cable is described. A speed and position detection system is recommended. It is installed on board and is used as the feedback end. Restricted by the maglev train's structure, the permanent magnet electrodynamic suspension (EDS) train uses the non-contact method to detect its position. Because of the shake and the track joints, the position signal sent by the position sensor is always aberrant and noisy. To solve this problem, a linear discrete track-differentiator filtering algorithm is proposed. The filtering characters of the track-differentiator (TD) and track-differentiator group are analyzed. The four series of TD are used in the signal processing unit. The result shows that the track-differentiator could have a good effect and make the traction system run normally.

Eduard Strasburger (1844-1912): founder of modern plant cell biology.

PubMed

Volkmann, Dieter; Baluška, František; Menzel, Diedrik

2012-10-01

Eduard Strasburger, director of the Botany Institute and the Botanical Garden at the University of Bonn from 1881 to 1912, was one of the most admirable scientists in the field of plant biology, not just as the founder of modern plant cell biology but in addition as an excellent teacher who strongly believed in "education through science." He contributed to plant cell biology by discovering the discrete stages of karyokinesis and cytokinesis in algae and higher plants, describing cytoplasmic streaming in different systems, and reporting on the growth of the pollen tube into the embryo sac and guidance of the tube by synergides. Strasburger raised many problems which are hot spots in recent plant cell biology, e.g., structure and function of the plasmodesmata in relation to phloem loading (Strasburger cells) and signaling, mechanisms of cell plate formation, vesicle trafficking as a basis for most important developmental processes, and signaling related to fertilization.

Fpga based L-band pulse doppler radar design and implementation

NASA Astrophysics Data System (ADS)

Savci, Kubilay

As its name implies RADAR (Radio Detection and Ranging) is an electromagnetic sensor used for detection and locating targets from their return signals. Radar systems propagate electromagnetic energy, from the antenna which is in part intercepted by an object. Objects reradiate a portion of energy which is captured by the radar receiver. The received signal is then processed for information extraction. Radar systems are widely used for surveillance, air security, navigation, weather hazard detection, as well as remote sensing applications. In this work, an FPGA based L-band Pulse Doppler radar prototype, which is used for target detection, localization and velocity calculation has been built and a general-purpose Pulse Doppler radar processor has been developed. This radar is a ground based stationary monopulse radar, which transmits a short pulse with a certain pulse repetition frequency (PRF). Return signals from the target are processed and information about their location and velocity is extracted. Discrete components are used for the transmitter and receiver chain. The hardware solution is based on Xilinx Virtex-6 ML605 FPGA board, responsible for the control of the radar system and the digital signal processing of the received signal, which involves Constant False Alarm Rate (CFAR) detection and Pulse Doppler processing. The algorithm is implemented in MATLAB/SIMULINK using the Xilinx System Generator for DSP tool. The field programmable gate arrays (FPGA) implementation of the radar system provides the flexibility of changing parameters such as the PRF and pulse length therefore it can be used with different radar configurations as well. A VHDL design has been developed for 1Gbit Ethernet connection to transfer digitized return signal and detection results to PC. An A-Scope software has been developed with C# programming language to display time domain radar signals and detection results on PC. Data are processed both in FPGA chip and on PC. FPGA uses fixed point arithmetic operations as it is fast and facilitates source requirement as it consumes less hardware than floating point arithmetic operations. The software uses floating point arithmetic operations, which ensure precision in processing at the expense of speed. The functionality of the radar system has been tested for experimental validation in the field with a moving car and the validation of submodules are tested with synthetic data simulated on MATLAB.

Mutual information identifies spurious Hurst phenomena in resting state EEG and fMRI data

NASA Astrophysics Data System (ADS)

von Wegner, Frederic; Laufs, Helmut; Tagliazucchi, Enzo

2018-02-01

Long-range memory in time series is often quantified by the Hurst exponent H , a measure of the signal's variance across several time scales. We analyze neurophysiological time series from electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) resting state experiments with two standard Hurst exponent estimators and with the time-lagged mutual information function applied to discretized versions of the signals. A confidence interval for the mutual information function is obtained from surrogate Markov processes with equilibrium distribution and transition matrix identical to the underlying signal. For EEG signals, we construct an additional mutual information confidence interval from a short-range correlated, tenth-order autoregressive model. We reproduce the previously described Hurst phenomenon (H >0.5 ) in the analytical amplitude of alpha frequency band oscillations, in EEG microstate sequences, and in fMRI signals, but we show that the Hurst phenomenon occurs without long-range memory in the information-theoretical sense. We find that the mutual information function of neurophysiological data behaves differently from fractional Gaussian noise (fGn), for which the Hurst phenomenon is a sufficient condition to prove long-range memory. Two other well-characterized, short-range correlated stochastic processes (Ornstein-Uhlenbeck, Cox-Ingersoll-Ross) also yield H >0.5 , whereas their mutual information functions lie within the Markovian confidence intervals, similar to neural signals. In these processes, which do not have long-range memory by construction, a spurious Hurst phenomenon occurs due to slow relaxation times and heteroscedasticity (time-varying conditional variance). In summary, we find that mutual information correctly distinguishes long-range from short-range dependence in the theoretical and experimental cases discussed. Our results also suggest that the stationary fGn process is not sufficient to describe neural data, which seem to belong to a more general class of stochastic processes, in which multiscale variance effects produce Hurst phenomena without long-range dependence. In our experimental data, the Hurst phenomenon and long-range memory appear as different system properties that should be estimated and interpreted independently.

SPHARA - A Generalized Spatial Fourier Analysis for Multi-Sensor Systems with Non-Uniformly Arranged Sensors: Application to EEG

PubMed Central

Graichen, Uwe; Eichardt, Roland; Fiedler, Patrique; Strohmeier, Daniel; Zanow, Frank; Haueisen, Jens

2015-01-01

Important requirements for the analysis of multichannel EEG data are efficient techniques for signal enhancement, signal decomposition, feature extraction, and dimensionality reduction. We propose a new approach for spatial harmonic analysis (SPHARA) that extends the classical spatial Fourier analysis to EEG sensors positioned non-uniformly on the surface of the head. The proposed method is based on the eigenanalysis of the discrete Laplace-Beltrami operator defined on a triangular mesh. We present several ways to discretize the continuous Laplace-Beltrami operator and compare the properties of the resulting basis functions computed using these discretization methods. We apply SPHARA to somatosensory evoked potential data from eleven volunteers and demonstrate the ability of the method for spatial data decomposition, dimensionality reduction and noise suppression. When employing SPHARA for dimensionality reduction, a significantly more compact representation can be achieved using the FEM approach, compared to the other discretization methods. Using FEM, to recover 95% and 99% of the total energy of the EEG data, on average only 35% and 58% of the coefficients are necessary. The capability of SPHARA for noise suppression is shown using artificial data. We conclude that SPHARA can be used for spatial harmonic analysis of multi-sensor data at arbitrary positions and can be utilized in a variety of other applications. PMID:25885290

Generation Algorithm of Discrete Line in Multi-Dimensional Grids

NASA Astrophysics Data System (ADS)

Du, L.; Ben, J.; Li, Y.; Wang, R.

2017-09-01

Discrete Global Grids System (DGGS) is a kind of digital multi-resolution earth reference model, in terms of structure, it is conducive to the geographical spatial big data integration and mining. Vector is one of the important types of spatial data, only by discretization, can it be applied in grids system to make process and analysis. Based on the some constraint conditions, this paper put forward a strict definition of discrete lines, building a mathematic model of the discrete lines by base vectors combination method. Transforming mesh discrete lines issue in n-dimensional grids into the issue of optimal deviated path in n-minus-one dimension using hyperplane, which, therefore realizing dimension reduction process in the expression of mesh discrete lines. On this basis, we designed a simple and efficient algorithm for dimension reduction and generation of the discrete lines. The experimental results show that our algorithm not only can be applied in the two-dimensional rectangular grid, also can be applied in the two-dimensional hexagonal grid and the three-dimensional cubic grid. Meanwhile, when our algorithm is applied in two-dimensional rectangular grid, it can get a discrete line which is more similar to the line in the Euclidean space.

Time-Frequency Domain Analysis of Helicopter Transmission Vibration

DTIC Science & Technology

1991-08-01

Wigner - Ville distribution ( WVD ) have be reported, including speech...FREQUENCY DISTRIBUTIONS . 8 6. THE WIGNER - VILLE DISTRIBUTION . 9 6.1 History. 9 6.2 Definition. 9 6.3 Discrete-Time/Frequency Wigner - Ville Distribution . 10...signals are examined to indicate how various forms of modulation are portrayed using the Wigner - Ville distribution . Practical examples A signal is

DETAILED DATA ANALYSIS OF ECHO I, ECHO II AND MOON REFLECTED SIGNALS. VOLUME 2. AUTOCORRELATION FUNCTIONS OF ECHO II REFLECTED SIGNALS,

DTIC Science & Technology

techniques is presented. Two methods for linearizing the data are given. An expression for the specular-to-spattered power ratio is derived, and the inverse ... transform of the autocorrelation function is discussed. The surface roughness of the reflector, the discrete fading rates, and fading frequencies

A discrete-time adaptive control scheme for robot manipulators

NASA Technical Reports Server (NTRS)

Tarokh, M.

1990-01-01

A discrete-time model reference adaptive control scheme is developed for trajectory tracking of robot manipulators. The scheme utilizes feedback, feedforward, and auxiliary signals, obtained from joint angle measurement through simple expressions. Hyperstability theory is utilized to derive the adaptation laws for the controller gain matrices. It is shown that trajectory tracking is achieved despite gross robot parameter variation and uncertainties. The method offers considerable design flexibility and enables the designer to improve the performance of the control system by adjusting free design parameters. The discrete-time adaptation algorithm is extremely simple and is therefore suitable for real-time implementation. Simulations and experimental results are given to demonstrate the performance of the scheme.

Enhancement of the Wear Particle Monitoring Capability of Oil Debris Sensors Using a Maximal Overlap Discrete Wavelet Transform with Optimal Decomposition Depth

PubMed Central

Li, Chuan; Peng, Juan; Liang, Ming

2014-01-01

Oil debris sensors are effective tools to monitor wear particles in lubricants. For in situ applications, surrounding noise and vibration interferences often distort the oil debris signature of the sensor. Hence extracting oil debris signatures from sensor signals is a challenging task for wear particle monitoring. In this paper we employ the maximal overlap discrete wavelet transform (MODWT) with optimal decomposition depth to enhance the wear particle monitoring capability. The sensor signal is decomposed by the MODWT into different depths for detecting the wear particle existence. To extract the authentic particle signature with minimal distortion, the root mean square deviation of kurtosis value of the segmented signal residue is adopted as a criterion to obtain the optimal decomposition depth for the MODWT. The proposed approach is evaluated using both simulated and experimental wear particles. The results show that the present method can improve the oil debris monitoring capability without structural upgrade requirements. PMID:24686730

Enhancement of the wear particle monitoring capability of oil debris sensors using a maximal overlap discrete wavelet transform with optimal decomposition depth.

PubMed

Li, Chuan; Peng, Juan; Liang, Ming

2014-03-28

Oil debris sensors are effective tools to monitor wear particles in lubricants. For in situ applications, surrounding noise and vibration interferences often distort the oil debris signature of the sensor. Hence extracting oil debris signatures from sensor signals is a challenging task for wear particle monitoring. In this paper we employ the maximal overlap discrete wavelet transform (MODWT) with optimal decomposition depth to enhance the wear particle monitoring capability. The sensor signal is decomposed by the MODWT into different depths for detecting the wear particle existence. To extract the authentic particle signature with minimal distortion, the root mean square deviation of kurtosis value of the segmented signal residue is adopted as a criterion to obtain the optimal decomposition depth for the MODWT. The proposed approach is evaluated using both simulated and experimental wear particles. The results show that the present method can improve the oil debris monitoring capability without structural upgrade requirements.

Effect of boron doping on first-order Raman scattering in superconducting boron doped diamond films

NASA Astrophysics Data System (ADS)

Kumar, Dinesh; Chandran, Maneesh; Ramachandra Rao, M. S.

2017-05-01

Aggregation of impurity levels into an impurity band in heavily boron doped diamond results in a background continuum and discrete zone centre phonon interference during the inelastic light scattering process. In order to understand the Raman scattering effect in granular BDD films, systematically heavily doped samples in the semiconducting and superconducting regimes have been studied using the excitation wavelengths in the UV and visible regions. A comprehensive analysis of the Fano resonance effect as a function of the impurity concentrations and the excitation frequencies is presented. Various Raman modes available in BDD including signals from the grain boundaries are discussed.

Statistical study of generalized nonlinear phase step estimation methods in phase-shifting interferometry.

PubMed

Langoju, Rajesh; Patil, Abhijit; Rastogi, Pramod

2007-11-20

Signal processing methods based on maximum-likelihood theory, discrete chirp Fourier transform, and spectral estimation methods have enabled accurate measurement of phase in phase-shifting interferometry in the presence of nonlinear response of the piezoelectric transducer to the applied voltage. We present the statistical study of these generalized nonlinear phase step estimation methods to identify the best method by deriving the Cramér-Rao bound. We also address important aspects of these methods for implementation in practical applications and compare the performance of the best-identified method with other bench marking algorithms in the presence of harmonics and noise.

A wide-band high-resolution spectrum analyzer

NASA Technical Reports Server (NTRS)

Quirk, Maureen P.; Garyantes, Michael F.; Wilck, Helmut C.; Grimm, Michael J.

1988-01-01

A two-million-channel, 40 MHz bandwidth, digital spectrum analyzer under development at the Jet Propulsion Laboratory is described. The analyzer system will serve as a prototype processor for the sky survey portion of NASA's Search for Extraterrestrial Intelligence program and for other applications in the Deep Space Network. The analyzer digitizes an analog input, performs a 2 (sup 21) point Discrete Fourier Transform, accumulates the output power, normalizes the output to remove frequency-dependent gain, and automates simple detection algorithms. Due to its built-in frequency-domain processing functions and configuration flexibility, the analyzer is a very powerful tool for real-time signal analysis.

Lieb-Robinson bound and locality for general markovian quantum dynamics.

PubMed

Poulin, David

2010-05-14

The Lieb-Robinson bound shows the existence of a maximum speed of signal propagation in discrete quantum mechanical systems with local interactions. This generalizes the concept of relativistic causality beyond field theory, and provides a powerful tool in theoretical condensed matter physics and quantum information science. Here, we extend the scope of this seminal result by considering general markovian quantum evolution, where we prove that an equivalent bound holds. In addition, we use the generalized bound to demonstrate that correlations in the stationary state of a Markov process decay on a length scale set by the Lieb-Robinson velocity and the system's relaxation time.

A case study on Discrete Wavelet Transform based Hurst exponent for epilepsy detection.

PubMed

Madan, Saiby; Srivastava, Kajri; Sharmila, A; Mahalakshmi, P

2018-01-01

Epileptic seizures are manifestations of epilepsy. Careful analysis of EEG records can provide valuable insight and improved understanding of the mechanism causing epileptic disorders. The detection of epileptic form discharges in EEG is an important component in the diagnosis of epilepsy. As EEG signals are non-stationary, the conventional frequency and time domain analysis does not provide better accuracy. So, in this work an attempt has been made to provide an overview of the determination of epilepsy by implementation of Hurst exponent (HE)-based discrete wavelet transform techniques for feature extraction from EEG data sets obtained during ictal and pre ictal stages of affected person and finally classifying EEG signals using SVM and KNN Classifiers. The The highest accuracy of 99% is obtained using SVM.

A non-orthogonal decomposition of flows into discrete events

NASA Astrophysics Data System (ADS)

Boxx, Isaac; Lewalle, Jacques

1998-11-01

This work is based on the formula for the inverse Hermitian wavelet transform. A signal can be interpreted as a (non-unique) superposition of near-singular, partially overlapping events arising from Dirac functions and/or its derivatives combined with diffusion.( No dynamics implied: dimensionless diffusion is related to the definition of the analyzing wavelets.) These events correspond to local maxima of spectral energy density. We successfully fitted model events of various orders on a succession of fields, ranging from elementary signals to one-dimensional hot-wire traces. We document edge effects, event overlap and its implications on the algorithm. The interpretation of the discrete singularities as flow events (such as coherent structures) and the fundamental non-uniqueness of the decomposition are discussed. The dynamics of these events will be examined in the companion paper.

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.

Preliminary Study on Continuous Recognition of Elbow Flexion/Extension Using sEMG Signals for Bilateral Rehabilitation

PubMed Central

Song, Zhibin; Zhang, Songyuan

2016-01-01

Surface electromyography (sEMG) signals are closely related to the activation of human muscles and the motion of the human body, which can be used to estimate the dynamics of human limbs in the rehabilitation field. They also have the potential to be used in the application of bilateral rehabilitation, where hemiplegic patients can train their affected limbs following the motion of unaffected limbs via some rehabilitation devices. Traditional methods to process the sEMG focused on motion pattern recognition, namely, discrete patterns, which are not satisfactory for use in bilateral rehabilitation. In order to overcome this problem, in this paper, we built a relationship between sEMG signals and human motion in elbow flexion and extension on the sagittal plane. During the conducted experiments, four participants were required to perform elbow flexion and extension on the sagittal plane smoothly with only an inertia sensor in their hands, where forearm dynamics were not considered. In these circumstances, sEMG signals were weak compared to those with heavy loads or high acceleration. The contrastive experimental results show that continuous motion can also be obtained within an acceptable precision range. PMID:27775573

Preliminary Study on Continuous Recognition of Elbow Flexion/Extension Using sEMG Signals for Bilateral Rehabilitation.

PubMed

Song, Zhibin; Zhang, Songyuan

2016-10-19

Surface electromyography (sEMG) signals are closely related to the activation of human muscles and the motion of the human body, which can be used to estimate the dynamics of human limbs in the rehabilitation field. They also have the potential to be used in the application of bilateral rehabilitation, where hemiplegic patients can train their affected limbs following the motion of unaffected limbs via some rehabilitation devices. Traditional methods to process the sEMG focused on motion pattern recognition, namely, discrete patterns, which are not satisfactory for use in bilateral rehabilitation. In order to overcome this problem, in this paper, we built a relationship between sEMG signals and human motion in elbow flexion and extension on the sagittal plane. During the conducted experiments, four participants were required to perform elbow flexion and extension on the sagittal plane smoothly with only an inertia sensor in their hands, where forearm dynamics were not considered. In these circumstances, sEMG signals were weak compared to those with heavy loads or high acceleration. The contrastive experimental results show that continuous motion can also be obtained within an acceptable precision range.

A new multiscale noise tuning stochastic resonance for enhanced fault diagnosis in wind turbine drivetrains

NASA Astrophysics Data System (ADS)

Hu, Bingbing; Li, Bing

2016-02-01

It is very difficult to detect weak fault signatures due to the large amount of noise in a wind turbine system. Multiscale noise tuning stochastic resonance (MSTSR) has proved to be an effective way to extract weak signals buried in strong noise. However, the MSTSR method originally based on discrete wavelet transform (DWT) has disadvantages such as shift variance and the aliasing effects in engineering application. In this paper, the dual-tree complex wavelet transform (DTCWT) is introduced into the MSTSR method, which makes it possible to further improve the system output signal-to-noise ratio and the accuracy of fault diagnosis by the merits of DTCWT (nearly shift invariant and reduced aliasing effects). Moreover, this method utilizes the relationship between the two dual-tree wavelet basis functions, instead of matching the single wavelet basis function to the signal being analyzed, which may speed up the signal processing and be employed in on-line engineering monitoring. The proposed method is applied to the analysis of bearing outer ring and shaft coupling vibration signals carrying fault information. The results confirm that the method performs better in extracting the fault features than the original DWT-based MSTSR, the wavelet transform with post spectral analysis, and EMD-based spectral analysis methods.

Is processing of symbols and words influenced by writing system? Evidence from Chinese, Korean, English, and Greek.

PubMed

Altani, Angeliki; Georgiou, George K; Deng, Ciping; Cho, Jeung-Ryeul; Katopodi, Katerina; Wei, Wei; Protopapas, Athanassios

2017-12-01

We examined cross-linguistic effects in the relationship between serial and discrete versions of digit naming and word reading. In total, 113 Mandarin-speaking Chinese children, 100 Korean children, 112 English-speaking Canadian children, and 108 Greek children in Grade 3 were administered tasks of serial and discrete naming of words and digits. Interrelations among tasks indicated that the link between rapid naming and reading is largely determined by the format of the tasks across orthographies. Multigroup path analyses with discrete and serial word reading as dependent variables revealed commonalities as well as significant differences between writing systems. The path coefficient from discrete digits to discrete words was greater for the more transparent orthographies, consistent with more efficient sight-word processing. The effect of discrete word reading on serial word reading was stronger in alphabetic languages, where there was also a suppressive effect of discrete digit naming. However, the effect of serial digit naming on serial word reading did not differ among the four language groups. This pattern of relationships challenges a universal account of reading fluency acquisition while upholding a universal role of rapid serial naming, further distinguishing between multi-element interword and intraword processing. Copyright © 2017 Elsevier Inc. All rights reserved.

Digital transceiver implementation for wavelet packet modulation

NASA Astrophysics Data System (ADS)

Lindsey, Alan R.; Dill, Jeffrey C.

1998-03-01

Current transceiver designs for wavelet-based communication systems are typically reliant on analog waveform synthesis, however, digital processing is an important part of the eventual success of these techniques. In this paper, a transceiver implementation is introduced for the recently introduced wavelet packet modulation scheme which moves the analog processing as far as possible toward the antenna. The transceiver is based on the discrete wavelet packet transform which incorporates level and node parameters for generalized computation of wavelet packets. In this transform no particular structure is imposed on the filter bank save dyadic branching, and a maximum level which is specified a priori and dependent mainly on speed and/or cost considerations. The transmitter/receiver structure takes a binary sequence as input and, based on the desired time- frequency partitioning, processes the signal through demultiplexing, synthesis, analysis, multiplexing and data determination completely in the digital domain - with exception of conversion in and out of the analog domain for transmission.

Transceivers and receivers for quantum key distribution and methods pertaining thereto

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

DeRose, Christopher; Sarovar, Mohan; Soh, Daniel B.S.

Various technologies for performing continuous-variable (CV) and discrete-variable (DV) quantum key distribution (QKD) with integrated electro-optical circuits are described herein. An integrated DV-QKD system uses Mach-Zehnder modulators to modulate a polarization of photons at a transmitter and select a photon polarization measurement basis at a receiver. An integrated CV-QKD system uses wavelength division multiplexing to send and receive amplitude-modulated and phase-modulated optical signals with a local oscillator signal while maintaining phase coherence between the modulated signals and the local oscillator signal.

Observability of discretized partial differential equations

NASA Technical Reports Server (NTRS)

Cohn, Stephen E.; Dee, Dick P.

1988-01-01

It is shown that complete observability of the discrete model used to assimilate data from a linear partial differential equation (PDE) system is necessary and sufficient for asymptotic stability of the data assimilation process. The observability theory for discrete systems is reviewed and applied to obtain simple observability tests for discretized constant-coefficient PDEs. Examples are used to show how numerical dispersion can result in discrete dynamics with multiple eigenvalues, thereby detracting from observability.

Fluorescence molecular tomography reconstruction via discrete cosine transform-based regularization

NASA Astrophysics Data System (ADS)

Shi, Junwei; Liu, Fei; Zhang, Jiulou; Luo, Jianwen; Bai, Jing

2015-05-01

Fluorescence molecular tomography (FMT) as a noninvasive imaging modality has been widely used for biomedical preclinical applications. However, FMT reconstruction suffers from severe ill-posedness, especially when a limited number of projections are used. In order to improve the quality of FMT reconstruction results, a discrete cosine transform (DCT) based reweighted L1-norm regularization algorithm is proposed. In each iteration of the reconstruction process, different reweighted regularization parameters are adaptively assigned according to the values of DCT coefficients to suppress the reconstruction noise. In addition, the permission region of the reconstructed fluorophores is adaptively constructed to increase the convergence speed. In order to evaluate the performance of the proposed algorithm, physical phantom and in vivo mouse experiments with a limited number of projections are carried out. For comparison, different L1-norm regularization strategies are employed. By quantifying the signal-to-noise ratio (SNR) of the reconstruction results in the phantom and in vivo mouse experiments with four projections, the proposed DCT-based reweighted L1-norm regularization shows higher SNR than other L1-norm regularizations employed in this work.

Application of discrete Fourier inter-coefficient difference for assessing genetic sequence similarity.

PubMed

King, Brian R; Aburdene, Maurice; Thompson, Alex; Warres, Zach

2014-01-01

Digital signal processing (DSP) techniques for biological sequence analysis continue to grow in popularity due to the inherent digital nature of these sequences. DSP methods have demonstrated early success for detection of coding regions in a gene. Recently, these methods are being used to establish DNA gene similarity. We present the inter-coefficient difference (ICD) transformation, a novel extension of the discrete Fourier transformation, which can be applied to any DNA sequence. The ICD method is a mathematical, alignment-free DNA comparison method that generates a genetic signature for any DNA sequence that is used to generate relative measures of similarity among DNA sequences. We demonstrate our method on a set of insulin genes obtained from an evolutionarily wide range of species, and on a set of avian influenza viral sequences, which represents a set of highly similar sequences. We compare phylogenetic trees generated using our technique against trees generated using traditional alignment techniques for similarity and demonstrate that the ICD method produces a highly accurate tree without requiring an alignment prior to establishing sequence similarity.

An Efficient Method for Image and Audio Steganography using Least Significant Bit (LSB) Substitution

NASA Astrophysics Data System (ADS)

Chadha, Ankit; Satam, Neha; Sood, Rakshak; Bade, Dattatray

2013-09-01

In order to improve the data hiding in all types of multimedia data formats such as image and audio and to make hidden message imperceptible, a novel method for steganography is introduced in this paper. It is based on Least Significant Bit (LSB) manipulation and inclusion of redundant noise as secret key in the message. This method is applied to data hiding in images. For data hiding in audio, Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) both are used. All the results displayed prove to be time-efficient and effective. Also the algorithm is tested for various numbers of bits. For those values of bits, Mean Square Error (MSE) and Peak-Signal-to-Noise-Ratio (PSNR) are calculated and plotted. Experimental results show that the stego-image is visually indistinguishable from the original cover-image when n<=4, because of better PSNR which is achieved by this technique. The final results obtained after steganography process does not reveal presence of any hidden message, thus qualifying the criteria of imperceptible message.

Multifocus watermarking approach based on discrete cosine transform.

PubMed

Waheed, Safa Riyadh; Alkawaz, Mohammed Hazim; Rehman, Amjad; Almazyad, Abdulaziz S; Saba, Tanzila

2016-05-01

Image fusion process consolidates data and information from various images of same sight into a solitary image. Each of the source images might speak to a fractional perspective of the scene, and contains both "pertinent" and "immaterial" information. In this study, a new image fusion method is proposed utilizing the Discrete Cosine Transform (DCT) to join the source image into a solitary minimized image containing more exact depiction of the sight than any of the individual source images. In addition, the fused image comes out with most ideal quality image without bending appearance or loss of data. DCT algorithm is considered efficient in image fusion. The proposed scheme is performed in five steps: (1) RGB colour image (input image) is split into three channels R, G, and B for source images. (2) DCT algorithm is applied to each channel (R, G, and B). (3) The variance values are computed for the corresponding 8 × 8 blocks of each channel. (4) Each block of R of source images is compared with each other based on the variance value and then the block with maximum variance value is selected to be the block in the new image. This process is repeated for all channels of source images. (5) Inverse discrete cosine transform is applied on each fused channel to convert coefficient values to pixel values, and then combined all the channels to generate the fused image. The proposed technique can potentially solve the problem of unwanted side effects such as blurring or blocking artifacts by reducing the quality of the subsequent image in image fusion process. The proposed approach is evaluated using three measurement units: the average of Q(abf), standard deviation, and peak Signal Noise Rate. The experimental results of this proposed technique have shown good results as compared with older techniques. © 2016 Wiley Periodicals, Inc.

A Summary of Some Discrete-Event System Control Problems

NASA Astrophysics Data System (ADS)

Rudie, Karen

A summary of the area of control of discrete-event systems is given. In this research area, automata and formal language theory is used as a tool to model physical problems that arise in technological and industrial systems. The key ingredients to discrete-event control problems are a process that can be modeled by an automaton, events in that process that cannot be disabled or prevented from occurring, and a controlling agent that manipulates the events that can be disabled to guarantee that the process under control either generates all the strings in some prescribed language or as many strings as possible in some prescribed language. When multiple controlling agents act on a process, decentralized control problems arise. In decentralized discrete-event systems, it is presumed that the agents effecting control cannot each see all event occurrences. Partial observation leads to some problems that cannot be solved in polynomial time and some others that are not even decidable.

Shape memory alloy wire for self-sensing servo actuation

NASA Astrophysics Data System (ADS)

Josephine Selvarani Ruth, D.; Dhanalakshmi, K.

2017-01-01

This paper reports on the development of a straightforward approach to realise self-sensing shape memory alloy (SMA) wire actuated control. A differential electrical resistance measurement circuit (the sensorless signal conditioning (SSC) circuit) is designed; this sensing signal is directly used as the feedback for control. Antagonistic SMA wire actuators designed for servo actuation is realized in self-sensing actuation (SSA) mode for direct control with the differential electrical resistance feedback. The self-sensing scheme is established on a 1-DOF manipulator with the discrete time sliding mode controls which demonstrates good control performance, whatever be the disturbance and loading conditions. The uniqueness of this work is the design of the generic electronic SSC circuit for SMA actuated system, for measurement and control. With a concern to the implementation of self-sensing technique in SMA, this scheme retains the systematic control architecture by using the sensing signal (self-sensed, electrical resistance corresponding to the system position) for feedback, without requiring any processing as that of the methods adopted and reported previously for SSA techniques of SMA.

Wavelet methodology to improve single unit isolation in primary motor cortex cells.

PubMed

Ortiz-Rosario, Alexis; Adeli, Hojjat; Buford, John A

2015-05-15

The proper isolation of action potentials recorded extracellularly from neural tissue is an active area of research in the fields of neuroscience and biomedical signal processing. This paper presents an isolation methodology for neural recordings using the wavelet transform (WT), a statistical thresholding scheme, and the principal component analysis (PCA) algorithm. The effectiveness of five different mother wavelets was investigated: biorthogonal, Daubachies, discrete Meyer, symmetric, and Coifman; along with three different wavelet coefficient thresholding schemes: fixed form threshold, Stein's unbiased estimate of risk, and minimax; and two different thresholding rules: soft and hard thresholding. The signal quality was evaluated using three different statistical measures: mean-squared error, root-mean squared, and signal to noise ratio. The clustering quality was evaluated using two different statistical measures: isolation distance, and L-ratio. This research shows that the selection of the mother wavelet has a strong influence on the clustering and isolation of single unit neural activity, with the Daubachies 4 wavelet and minimax thresholding scheme performing the best. Copyright © 2015. Published by Elsevier B.V.

Nonlinearity-aware 200  Gbit/s DMT transmission for C-band short-reach optical interconnects with a single packaged electro-absorption modulated laser.

PubMed

Zhang, Lu; Hong, Xuezhi; Pang, Xiaodan; Ozolins, Oskars; Udalcovs, Aleksejs; Schatz, Richard; Guo, Changjian; Zhang, Junwei; Nordwall, Fredrik; Engenhardt, Klaus M; Westergren, Urban; Popov, Sergei; Jacobsen, Gunnar; Xiao, Shilin; Hu, Weisheng; Chen, Jiajia

2018-01-15

We experimentally demonstrate the transmission of a 200 Gbit/s discrete multitone (DMT) at the soft forward error correction limit in an intensity-modulation direct-detection system with a single C-band packaged distributed feedback laser and traveling-wave electro absorption modulator (DFB-TWEAM), digital-to-analog converter and photodiode. The bit-power loaded DMT signal is transmitted over 1.6 km standard single-mode fiber with a net rate of 166.7 Gbit/s, achieving an effective electrical spectrum efficiency of 4.93 bit/s/Hz. Meanwhile, net rates of 174.2 Gbit/s and 179.5 Gbit/s are also demonstrated over 0.8 km SSMF and in an optical back-to-back case, respectively. The feature of the packaged DFB-TWEAM is presented. The nonlinearity-aware digital signal processing algorithm for channel equalization is mathematically described, which improves the signal-to-noise ratio up to 3.5 dB.

Recent Advances in Compressed Sensing: Discrete Uncertainty Principles and Fast Hyperspectral Imaging

DTIC Science & Technology

2015-03-26

Fourier Analysis and Applications, vol. 14, pp. 838–858, 2008. 11. D. J. Cooke, “A discrete X - ray transform for chromotomographic hyperspectral imaging ... medical imaging , e.g., magnetic resonance imaging (MRI). Since the early 1980s, MRI has granted doctors the ability to distinguish between healthy tissue...i.e., at most K entries of x are nonzero. In many settings, this is a valid signal model; for example, JPEG2000 exploits the fact that natural images

Systematic parameter estimation in data-rich environments for cell signalling dynamics

PubMed Central

Nim, Tri Hieu; Luo, Le; Clément, Marie-Véronique; White, Jacob K.; Tucker-Kellogg, Lisa

2013-01-01

Motivation: Computational models of biological signalling networks, based on ordinary differential equations (ODEs), have generated many insights into cellular dynamics, but the model-building process typically requires estimating rate parameters based on experimentally observed concentrations. New proteomic methods can measure concentrations for all molecular species in a pathway; this creates a new opportunity to decompose the optimization of rate parameters. Results: In contrast with conventional parameter estimation methods that minimize the disagreement between simulated and observed concentrations, the SPEDRE method fits spline curves through observed concentration points, estimates derivatives and then matches the derivatives to the production and consumption of each species. This reformulation of the problem permits an extreme decomposition of the high-dimensional optimization into a product of low-dimensional factors, each factor enforcing the equality of one ODE at one time slice. Coarsely discretized solutions to the factors can be computed systematically. Then the discrete solutions are combined using loopy belief propagation, and refined using local optimization. SPEDRE has unique asymptotic behaviour with runtime polynomial in the number of molecules and timepoints, but exponential in the degree of the biochemical network. SPEDRE performance is comparatively evaluated on a novel model of Akt activation dynamics including redox-mediated inactivation of PTEN (phosphatase and tensin homologue). Availability and implementation: Web service, software and supplementary information are available at www.LtkLab.org/SPEDRE Supplementary information: Supplementary data are available at Bioinformatics online. Contact: LisaTK@nus.edu.sg PMID:23426255

Analysis of the pathological severity degree of aortic stenosis (AS) and mitral stenosis (MS) using the discrete wavelet transform (DWT).

PubMed

Meziani, F; Debbal, S M; Atbi, A

2013-01-01

The heart is the principal organ that circulates blood. In normal conditions it produces four sounds for each cardiac cycle. However, most often only two sounds appear essential: S1 and S2. Two other sounds: S3 and S4, with lower amplitude than S1 or S2, appear occasionally in the cardiac cycle by the effect of disease or age. The presence of abnormal sounds in one cardiac cycle provide valuable information on various diseases. The aortic stenosis (AS), as being a valvular pathology, is characterized by a systolic murmur due to a narrowing of the aortic valve. The mitral stenosis (MS) is characterized by a diastolic murmur due to a reduction in the mitral valve. Early screening of these diseases is necessary; it's done by a simple technique known as: phonocardiography. Analysis of phonocardiograms signals using signal processing techniques can provide for clinicians useful information considered as a platform for significant decisions in their medical diagnosis. In this work two types of diseases were studied: aortic stenosis (AS) and mitral stenosis (MS). Each one presents six different cases. The application of the discrete wavelet transform (DWT) to analyse pathological severity of the (AS and MS was presented. Then, the calculation of various parameters was performed for each patient. This study examines the possibility of using the DWT in the analysis of pathological severity of AS and MS.

Integrating discrete stochastic models and single-cell experiments to infer predictive models of MAPK-induced transcription dynamics

NASA Astrophysics Data System (ADS)

Munsky, Brian

2015-03-01

MAPK signal-activated transcription plays central roles in myriad biological processes including stress adaptation responses and cell fate decisions. Recent single-cell and single-molecule experiments have advanced our ability to quantify the spatial, temporal, and stochastic fluctuations for such signals and their downstream effects on transcription regulation. This talk explores how integrating such experiments with discrete stochastic computational analyses can yield quantitative and predictive understanding of transcription regulation in both space and time. We use single-molecule mRNA fluorescence in situ hybridization (smFISH) experiments to reveal locations and numbers of multiple endogenous mRNA species in 100,000's of individual cells, at different times and under different genetic and environmental perturbations. We use finite state projection methods to precisely and efficiently compute the full joint probability distributions of these mRNA, which capture measured spatial, temporal and correlative fluctuations. By combining these experimental and computational tools with uncertainty quantification, we systematically compare models of varying complexity and select those which give optimally precise and accurate predictions in new situations. We use these tools to explore two MAPK-activated gene regulation pathways. In yeast adaptation to osmotic shock, we analyze Hog1 kinase activation of transcription for three different genes STL1 (osmotic stress), CTT1 (oxidative stress) and HSP12 (heat shock). In human osteosarcoma cells under serum induction, we analyze ERK activation of c-Fos transcription.

Extracting paleo-climate signals from sediment laminae: A new, automated image processing method

NASA Astrophysics Data System (ADS)

Gan, S. Q.; Scholz, C. A.

2010-12-01

Lake sediment laminations commonly represent depositional seasonality in lacustrine environments. Their occurrence and quantitative attributes contain various signals of their depositional environment, limnological conditions and climate. However, the identification and measurement of laminae remains a mainly manual process that is not only tedious and labor intensive, but also subjective and error prone. We present a batch method to identify laminae and extract lamina properties automatically and accurately from sediment core images. Our algorithm is focused on image enhancement that improves the signal-to-noise ratio and maximizes and normalizes image contrast. The unique feature of these algorithms is that they are all direction-sensitive, i.e., the algorithms treat images in the horizontal direction and vertical direction differently and independently. The core process of lamina identification is to use a one-dimensional (1-D) lamina identification algorithm to produce a lamina map, and to use image blob analyses and lamina connectivity analyses to aggregate and smash two-dimensional (2-D) lamina data for the best representation of fine-scale stratigraphy in the sediment profile. The primary output datasets of the system are definitions of laminae and primary color values for each pixel and each lamina in the depth direction; other derived datasets can be retrieved at users’ discretion. Sediment core images from Lake Hitchcock , USA and Lake Bosumtwi, Ghana, were used for algorithm development and testing. As a demonstration of the utility of the software, we processed sediment core images from the top of 50 meters of drill core (representing the past ~100 ky) from Lake Bosumtwi, Ghana.

Geophysical Inversion with Adaptive Array Processing of Ambient Noise

NASA Astrophysics Data System (ADS)

Traer, James

2011-12-01

Land-based seismic observations of microseisms generated during Tropical Storms Ernesto and Florence are dominated by signals in the 0.15--0.5Hz band. Data from seafloor hydrophones in shallow water (70m depth, 130 km off the New Jersey coast) show dominant signals in the gravity-wave frequency band, 0.02--0.18Hz and low amplitudes from 0.18--0.3Hz, suggesting significant opposing wave components necessary for DF microseism generation were negligible at the site. Both storms produced similar spectra, despite differing sizes, suggesting near-coastal shallow water as the dominant region for observed microseism generation. A mathematical explanation for a sign-inversion induced to the passive fathometer response by minimum variance distortionless response (MVDR) beamforming is presented. This shows that, in the region containing the bottom reflection, the MVDR fathometer response is identical to that obtained with conventional processing multiplied by a negative factor. A model is presented for the complete passive fathometer response to ocean surface noise, interfering discrete noise sources, and locally uncorrelated noise in an ideal waveguide. The leading order term of the ocean surface noise produces the cross-correlation of vertical multipaths and yields the depth of sub-bottom reflectors. Discrete noise incident on the array via multipaths give multiple peaks in the fathometer response. These peaks may obscure the sub-bottom reflections but can be attenuated with use of Minimum Variance Distortionless Response (MVDR) steering vectors. A theory is presented for the Signal-to-Noise-Ratio (SNR) for the seabed reflection peak in the passive fathometer response as a function of seabed depth, seabed reflection coefficient, averaging time, bandwidth and spatial directivity of the noise field. The passive fathometer algorithm was applied to data from two drifting array experiments in the Mediterranean, Boundary 2003 and 2004, with 0.34s of averaging time. In the 2004 experiment, the response showed the array depth varied periodically with an amplitude of 1 m and a period of 7 s consistent with wave driven motion of the array. This introduced a destructive interference which prevents the SNR growing with averaging time, unless the motion is removed by use of a peak tracker.

The impact of negative emotions on self-concept abstraction depends on accessible information processing styles.

PubMed

Isbell, Linda M; Rovenpor, Daniel R; Lair, Elicia C

2016-10-01

Research suggests that anger promotes global, abstract processing whereas sadness and fear promote local, concrete processing (see Schwarz & Clore, 2007 for a review). Contrary to a large and influential body of work suggesting that specific affective experiences are tethered to specific cognitive outcomes, the affect-as-cognitive-feedback account maintains that affective experiences confer positive or negative value on currently dominant processing styles, and thus can lead to either global or local processing (Huntsinger, Isbell, & Clore, 2014). The current work extends this theoretical perspective by investigating the impact of discrete negative emotions on the self-concept. By experimentally manipulating information processing styles and discrete negative emotions that vary in appraisals of certainty, we demonstrate that the impact of discrete negative emotions on the spontaneous self-concept depends on accessible processing styles. When global processing was accessible, individuals in angry (negative, high certainty) states generated more abstract statements about themselves than individuals in either sad (Experiment 1) or fearful (Experiment 2; negative, low certainty) states. When local processing was made accessible, however, the opposite pattern emerged, whereby individuals in angry states generated fewer abstract statements than individuals in sad or fearful states. Together these studies provide new insights into the mechanisms through which discrete emotions influence cognition. In contrast to theories assuming a dedicated link between emotions and processing styles, these results suggest that discrete emotions provide feedback about accessible ways of thinking, and are consistent with recent evidence suggesting that the impact of affect on cognition is highly context-dependent. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

A discrete time-varying internal model-based approach for high precision tracking of a multi-axis servo gantry.

PubMed

Zhang, Zhen; Yan, Peng; Jiang, Huan; Ye, Peiqing

2014-09-01

In this paper, we consider the discrete time-varying internal model-based control design for high precision tracking of complicated reference trajectories generated by time-varying systems. Based on a novel parallel time-varying internal model structure, asymptotic tracking conditions for the design of internal model units are developed, and a low order robust time-varying stabilizer is further synthesized. In a discrete time setting, the high precision tracking control architecture is deployed on a Voice Coil Motor (VCM) actuated servo gantry system, where numerical simulations and real time experimental results are provided, achieving the tracking errors around 3.5‰ for frequency-varying signals. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Generating Discrete Power-Law Distributions from a Death- Multiple Immigration Population Process

NASA Astrophysics Data System (ADS)

Matthews, J. O.; Jakeman, E.; Hopcraft, K. I.

2003-04-01

We consider the evolution of a simple population process governed by deaths and multiple immigrations that arrive with rates particular to their order. For a particular choice of rates, the equilibrium solution has a discrete power-law form. The model is a generalization of a process investigated previously where immigrants arrived in pairs [1]. The general properties of this model are discussed in a companion paper. The population is initiated with precisely M individuals present and evolves to an equilibrium distribution with a power-law tail. However the power-law tails of the equilibrium distribution are established immediately, so that moments and correlation properties of the population are undefined for any non-zero time. The technique we develop to characterize this process utilizes external monitoring that counts the emigrants leaving the population in specified time intervals. This counting distribution also possesses a power-law tail for all sampling times and the resulting time series exhibits two features worthy of note, a large variation in the strength of the signal, reflecting the power-law PDF; and secondly, intermittency of the emissions. We show that counting with a detector of finite dynamic range regularizes naturally the fluctuations, in effect `clipping' the events. All previously undefined characteristics such as the mean, autocorrelation and probabilities to the first event and time between events are well defined and derived. These properties, although obtained by discarding much data, nevertheless possess embedded power-law regimes that characterize the population in a way that is analogous to box averaging determination of fractal-dimension.

Imaging Through Random Discrete-Scatterer Dispersive Media

DTIC Science & Technology

2015-08-27

to that of a conventional, continuous, linear - frequency-modulated chirped signal [3]. Chirped train signals are a particular realization of a class of...continuous chirp signals, characterized by linear frequency modulation [3], we assume the time instances tn to be given by 1 tn = τg ( 1− βg n 2Ng ) n...kernel Dn(z) [9] by sincN (z) = (N + 1)−1DN/2(2πz/N). DISTRIBUTION A: Distribution approved for public release. 4 We use the elementary identity5 π sin

Discrete Fourier transforms of nonuniformly spaced data

NASA Technical Reports Server (NTRS)

Swan, P. R.

1982-01-01

Time series or spatial series of measurements taken with nonuniform spacings have failed to yield fully to analysis using the Discrete Fourier Transform (DFT). This is due to the fact that the formal DFT is the convolution of the transform of the signal with the transform of the nonuniform spacings. Two original methods are presented for deconvolving such transforms for signals containing significant noise. The first method solves a set of linear equations relating the observed data to values defined at uniform grid points, and then obtains the desired transform as the DFT of the uniform interpolates. The second method solves a set of linear equations relating the real and imaginary components of the formal DFT directly to those of the desired transform. The results of numerical experiments with noisy data are presented in order to demonstrate the capabilities and limitations of the methods.

Models for discrete-time self-similar vector processes with application to network traffic

NASA Astrophysics Data System (ADS)

Lee, Seungsin; Rao, Raghuveer M.; Narasimha, Rajesh

2003-07-01

The paper defines self-similarity for vector processes by employing the discrete-time continuous-dilation operation which has successfully been used previously by the authors to define 1-D discrete-time stochastic self-similar processes. To define self-similarity of vector processes, it is required to consider the cross-correlation functions between different 1-D processes as well as the autocorrelation function of each constituent 1-D process in it. System models to synthesize self-similar vector processes are constructed based on the definition. With these systems, it is possible to generate self-similar vector processes from white noise inputs. An important aspect of the proposed models is that they can be used to synthesize various types of self-similar vector processes by choosing proper parameters. Additionally, the paper presents evidence of vector self-similarity in two-channel wireless LAN data and applies the aforementioned systems to simulate the corresponding network traffic traces.

Decomposition of ECG by linear filtering.

PubMed

Murthy, I S; Niranjan, U C

1992-01-01

A simple method is developed for the delineation of a given electrocardiogram (ECG) signal into its component waves. The properties of discrete cosine transform (DCT) are exploited for the purpose. The transformed signal is convolved with appropriate filters and the component waves are obtained by computing the inverse transform (IDCT) of the filtered signals. The filters are derived from the time signal itself. Analysis of continuous strips of ECG signals with various arrhythmias showed that the performance of the method is satisfactory both qualitatively and quantitatively. The small amplitude P wave usually had a high percentage rms difference (PRD) compared to the other large component waves.

Multi-Interval Discretization of Continuous-Valued Attributes for Classification Learning

NASA Technical Reports Server (NTRS)

Fayyad, U.; Irani, K.

1993-01-01

Since most real-world applications of classification learning involve continuous-valued attributes, properly addressing the discretization process is an important problem. This paper addresses the use of the entropy minimization heuristic for discretizing the range of a continuous-valued attribute into multiple intervals.

The Spectrum of Mathematical Models.

ERIC Educational Resources Information Center

Karplus, Walter J.

1983-01-01

Mathematical modeling problems encountered in many disciplines are discussed in terms of the modeling process and applications of models. The models are classified according to three types of abstraction: continuous-space-continuous-time, discrete-space-continuous-time, and discrete-space-discrete-time. Limitations in different kinds of modeling…

Higuchi’s Method applied to detection of changes in timbre of digital sound synthesis of string instruments with the functional transformation method

NASA Astrophysics Data System (ADS)

Kanjanapen, Manorth; Kunsombat, Cherdsak; Chiangga, Surasak

2017-09-01

The functional transformation method (FTM) is a powerful tool for detailed investigation of digital sound synthesis by the physical modeling method, the resulting sound or measured vibrational characteristics at discretized points on real instruments directly solves the underlying physical effect of partial differential equation (PDE). In this paper, we present the Higuchi’s method to examine the difference between the timbre of tone and estimate fractal dimension of musical signals which contains information about their geometrical structure that synthesizes by FTM. With the Higuchi’s method we obtain the whole process is not complicated, fast processing, with the ease of analysis without expertise in the physics or virtuoso musicians and the easiest way for the common people can judge that sounds similarly presented.

The Cultural Evolution of Structured Languages in an Open-Ended, Continuous World

ERIC Educational Resources Information Center

Carr, Jon W.; Smith, Kenny; Cornish, Hannah; Kirby, Simon

2017-01-01

Language maps signals onto meanings through the use of two distinct types of structure. First, the space of meanings is discretized into categories that are shared by all users of the language. Second, the signals employed by the language are compositional: The meaning of the whole is a function of its parts and the way in which those parts are…

Formal modeling and analysis of ER-α associated Biological Regulatory Network in breast cancer.

PubMed

Khalid, Samra; Hanif, Rumeza; Tareen, Samar H K; Siddiqa, Amnah; Bibi, Zurah; Ahmad, Jamil

2016-01-01

Breast cancer (BC) is one of the leading cause of death among females worldwide. The increasing incidence of BC is due to various genetic and environmental changes which lead to the disruption of cellular signaling network(s). It is a complex disease in which several interlinking signaling cascades play a crucial role in establishing a complex regulatory network. The logical modeling approach of René Thomas has been applied to analyze the behavior of estrogen receptor-alpha (ER- α ) associated Biological Regulatory Network (BRN) for a small part of complex events that leads to BC metastasis. A discrete model was constructed using the kinetic logic formalism and its set of logical parameters were obtained using the model checking technique implemented in the SMBioNet software which is consistent with biological observations. The discrete model was further enriched with continuous dynamics by converting it into an equivalent Petri Net (PN) to analyze the logical parameters of the involved entities. In-silico based discrete and continuous modeling of ER- α associated signaling network involved in BC provides information about behaviors and gene-gene interaction in detail. The dynamics of discrete model revealed, imperative behaviors represented as cyclic paths and trajectories leading to pathogenic states such as metastasis. Results suggest that the increased expressions of receptors ER- α , IGF-1R and EGFR slow down the activity of tumor suppressor genes (TSGs) such as BRCA1, p53 and Mdm2 which can lead to metastasis. Therefore, IGF-1R and EGFR are considered as important inhibitory targets to control the metastasis in BC. The in-silico approaches allow us to increase our understanding of the functional properties of living organisms. It opens new avenues of investigations of multiple inhibitory targets (ER- α , IGF-1R and EGFR) for wet lab experiments as well as provided valuable insights in the treatment of cancers such as BC.

Physiological modules for generating discrete and rhythmic movements: component analysis of EMG signals.

PubMed

Bengoetxea, Ana; Leurs, Françoise; Hoellinger, Thomas; Cebolla, Ana Maria; Dan, Bernard; Cheron, Guy; McIntyre, Joseph

2014-01-01

A central question in Neuroscience is that of how the nervous system generates the spatiotemporal commands needed to realize complex gestures, such as handwriting. A key postulate is that the central nervous system (CNS) builds up complex movements from a set of simpler motor primitives or control modules. In this study we examined the control modules underlying the generation of muscle activations when performing different types of movement: discrete, point-to-point movements in eight different directions and continuous figure-eight movements in both the normal, upright orientation and rotated 90°. To test for the effects of biomechanical constraints, movements were performed in the frontal-parallel or sagittal planes, corresponding to two different nominal flexion/abduction postures of the shoulder. In all cases we measured limb kinematics and surface electromyographic activity (EMG) signals for seven different muscles acting around the shoulder. We first performed principal component analysis (PCA) of the EMG signals on a movement-by-movement basis. We found a surprisingly consistent pattern of muscle groupings across movement types and movement planes, although we could detect systematic differences between the PCs derived from movements performed in each shoulder posture and between the principal components associated with the different orientations of the figure. Unexpectedly we found no systematic differences between the figure eights and the point-to-point movements. The first three principal components could be associated with a general co-contraction of all seven muscles plus two patterns of reciprocal activation. From these results, we surmise that both "discrete-rhythmic movements" such as the figure eight, and discrete point-to-point movement may be constructed from three different fundamental modules, one regulating the impedance of the limb over the time span of the movement and two others operating to generate movement, one aligned with the vertical and the other aligned with the horizontal.

Physiological modules for generating discrete and rhythmic movements: component analysis of EMG signals

PubMed Central

Bengoetxea, Ana; Leurs, Françoise; Hoellinger, Thomas; Cebolla, Ana Maria; Dan, Bernard; Cheron, Guy; McIntyre, Joseph

2015-01-01

A central question in Neuroscience is that of how the nervous system generates the spatiotemporal commands needed to realize complex gestures, such as handwriting. A key postulate is that the central nervous system (CNS) builds up complex movements from a set of simpler motor primitives or control modules. In this study we examined the control modules underlying the generation of muscle activations when performing different types of movement: discrete, point-to-point movements in eight different directions and continuous figure-eight movements in both the normal, upright orientation and rotated 90°. To test for the effects of biomechanical constraints, movements were performed in the frontal-parallel or sagittal planes, corresponding to two different nominal flexion/abduction postures of the shoulder. In all cases we measured limb kinematics and surface electromyographic activity (EMG) signals for seven different muscles acting around the shoulder. We first performed principal component analysis (PCA) of the EMG signals on a movement-by-movement basis. We found a surprisingly consistent pattern of muscle groupings across movement types and movement planes, although we could detect systematic differences between the PCs derived from movements performed in each shoulder posture and between the principal components associated with the different orientations of the figure. Unexpectedly we found no systematic differences between the figure eights and the point-to-point movements. The first three principal components could be associated with a general co-contraction of all seven muscles plus two patterns of reciprocal activation. From these results, we surmise that both “discrete-rhythmic movements” such as the figure eight, and discrete point-to-point movement may be constructed from three different fundamental modules, one regulating the impedance of the limb over the time span of the movement and two others operating to generate movement, one aligned with the vertical and the other aligned with the horizontal. PMID:25620928

Subcellular Redox Targeting: Bridging in Vitro and in Vivo Chemical Biology.

PubMed

Long, Marcus J C; Poganik, Jesse R; Ghosh, Souradyuti; Aye, Yimon

2017-03-17

Networks of redox sensor proteins within discrete microdomains regulate the flow of redox signaling. Yet, the inherent reactivity of redox signals complicates the study of specific redox events and pathways by traditional methods. Herein, we review designer chemistries capable of measuring flux and/or mimicking subcellular redox signaling at the cellular and organismal level. Such efforts have begun to decipher the logic underlying organelle-, site-, and target-specific redox signaling in vitro and in vivo. These data highlight chemical biology as a perfect gateway to interrogate how nature choreographs subcellular redox chemistry to drive precision redox biology.

Demonstration of Detection and Ranging Using Solvable Chaos

NASA Technical Reports Server (NTRS)

Corron, Ned J.; Stahl, Mark T.; Blakely, Jonathan N.

2013-01-01

Acoustic experiments demonstrate a novel approach to ranging and detection that exploits the properties of a solvable chaotic oscillator. This nonlinear oscillator includes an ordinary differential equation and a discrete switching condition. The chaotic waveform generated by this hybrid system is used as the transmitted waveform. The oscillator admits an exact analytic solution that can be written as the linear convolution of binary symbols and a single basis function. This linear representation enables coherent reception using a simple analog matched filter and without need for digital sampling or signal processing. An audio frequency implementation of the transmitter and receiver is described. Successful acoustic ranging measurements are presented to demonstrate the viability of the approach.

Radar based Ground Level Reconstruction Utilizing a Hypocycloid Antenna Positioning System

NASA Astrophysics Data System (ADS)

Baer, Christoph; Musch, Thomas

2015-01-01

In this contribution we introduce a novel radar positioning system. It makes use of a mathematical curve, called hypocycloid, for a slanting movement of the radar antenna. By means of a planetary gear, a ball, and a universal joint as well as a stepping motor, a two dimensional positioning is provided by a uniaxial drive shaft exclusively. The fundamental position calculation and different signal processing algorithms are presented. By means of an 80 GHz FMCW radar system we performed several measurements on objects with discrete heights as well as on objects with continuous surfaces. The results of these investigations are essential part of this contribution and are discussed in detail.

Development of a multikilowatt ion thruster power processor

NASA Technical Reports Server (NTRS)

Schoenfeld, A. D.; Goldin, D. S.; Biess, J. J.

1972-01-01

A feasibility study was made of the application of silicon-controlled, rectifier series, resonant inverter, power conditioning technology to electric propulsion power processing operating from a 200 to 400 Vdc solar array bus. A power system block diagram was generated to meet the electrical requirements of a 20 CM hollow cathode, mercury bombardment, ion engine. The SCR series resonant inverter was developed as a primary means of power switching and conversion, and the analog signal-to-discrete-time-interval converter control system was applied to achieve good regulation. A complete breadboard was designed, fabricated, and tested with a resistive load bank, and critical power processor areas relating to efficiency, weight, and part count were identified.

A novel recursive Fourier transform for nonuniform sampled signals: application to heart rate variability spectrum estimation.

PubMed

Holland, Alexander; Aboy, Mateo

2009-07-01

We present a novel method to iteratively calculate discrete Fourier transforms for discrete time signals with sample time intervals that may be widely nonuniform. The proposed recursive Fourier transform (RFT) does not require interpolation of the samples to uniform time intervals, and each iterative transform update of N frequencies has computational order N. Because of the inherent non-uniformity in the time between successive heart beats, an application particularly well suited for this transform is power spectral density (PSD) estimation for heart rate variability. We compare RFT based spectrum estimation with Lomb-Scargle Transform (LST) based estimation. PSD estimation based on the LST also does not require uniform time samples, but the LST has a computational order greater than Nlog(N). We conducted an assessment study involving the analysis of quasi-stationary signals with various levels of randomly missing heart beats. Our results indicate that the RFT leads to comparable estimation performance to the LST with significantly less computational overhead and complexity for applications requiring iterative spectrum estimations.

Implementation of high-gain observer on low-cost fused IR-OS sensor embedded in UAV system

NASA Astrophysics Data System (ADS)

Nor, E. Mohd; Noor, S. B. Mohd; Bahiki, M. R.; Azrad, S.

2017-12-01

This paper presents discrete time implementation of a high gain observer (HGO) and extended term to estimate the state velocity and acceleration from the position measured by a low-cost sensor installed on-board the unmanned aerial vehicle (UAV). Owing to the low-cost sensor, the signal produced from fused IR-OS is noisy and therefore, additional filters are used to remove the noise. This study proposes an alternative to this standard and tedious procedure using HGO. The discrete time implementation of HGO and its extended term is presented and ground tests are conducted to verify the algorithm by inducing a dynamic motion on the UAV platform embedded with the fusion IR-OS onboard. A comparison study is conducted using standard numerical differentiation and ground truth measurement by OptiTrack. The results show that EHGO can produce a velocity signal with the same quality as that of differentiated signal from fused IR-OS using Kalman filter. The novelty of HGO lies in its simplicity and its minimal tuning of parameters.

Distributed delays in a hybrid model of tumor-immune system interplay.

PubMed

Caravagna, Giulio; Graudenzi, Alex; d'Onofrio, Alberto

2013-02-01

A tumor is kinetically characterized by the presence of multiple spatio-temporal scales in which its cells interplay with, for instance, endothelial cells or Immune system effectors, exchanging various chemical signals. By its nature, tumor growth is an ideal object of hybrid modeling where discrete stochastic processes model low-numbers entities, and mean-field equations model abundant chemical signals. Thus, we follow this approach to model tumor cells, effector cells and Interleukin-2, in order to capture the Immune surveillance effect. We here present a hybrid model with a generic delay kernel accounting that, due to many complex phenomena such as chemical transportation and cellular differentiation, the tumor-induced recruitment of effectors exhibits a lag period. This model is a Stochastic Hybrid Automata and its semantics is a Piecewise Deterministic Markov process where a two-dimensional stochastic process is interlinked to a multi-dimensional mean-field system. We instantiate the model with two well-known weak and strong delay kernels and perform simulations by using an algorithm to generate trajectories of this process. Via simulations and parametric sensitivity analysis techniques we (i) relate tumor mass growth with the two kernels, we (ii) measure the strength of the Immune surveillance in terms of probability distribution of the eradication times, and (iii) we prove, in the oscillatory regime, the existence of a stochastic bifurcation resulting in delay-induced tumor eradication.

Species Comparison of the Role of p38 MAP Kinase in the Female Reproductive System.

PubMed

Radi, Zaher A; Marusak, Rosemary A; Morris, Dale L

2009-06-01

The p38 mitogen-activated protein kinases (MAPKs) are members of discrete signal transduction pathways that have significant regulatory roles in a variety of biological processes, depending on the cell, tissue and organ type. p38 MAPKs are involved in inflammation, cell growth and differentiation and cell cycle. In the female reproductive system, p38 MAPKs are known to regulate various aspects of the reproductive process such as mammalian estrous and menstrual cycles as well as early pregnancy and parturition. p38 MAPKs have also been implicated in alterations and pathologies observed in the female reproductive system. Therefore, pharmacologic modulation of p38 MAPKs, and inter-connected signaling pathways (e.g., estrogen receptor signaling, c-fos, c-jun), may influence reproductive physiology and function. This article provides a critical, comparative review of available data on the roles of p38 MAPKs in the mammalian female reproductive system and in reproductive pathophysiology in humans and preclinical species. We first introduce fundamental differences and similarities of the mammalian female reproductive system that should be considered by toxicologists and toxicologic pathologists when assessing the effects of new pharmacologic agents on the female reproductive system. We then explore in detail the known roles for p38 MAPKs and related molecules in female reproduction. This foundation is then extended to pathological conditions in which p38 MAPKs are thought to play an integral role.

FPGA-Based Pulse Pile-Up Correction With Energy and Timing Recovery.

PubMed

Haselman, M D; Pasko, J; Hauck, S; Lewellen, T K; Miyaoka, R S

2012-10-01

Modern field programmable gate arrays (FPGAs) are capable of performing complex discrete signal processing algorithms with clock rates well above 100 MHz. This, combined with FPGA's low expense, ease of use, and selected dedicated hardware make them an ideal technology for a data acquisition system for a positron emission tomography (PET) scanner. The University of Washington is producing a high-resolution, small-animal PET scanner that utilizes FPGAs as the core of the front-end electronics. For this scanner, functions that are typically performed in dedicated circuits, or offline, are being migrated to the FPGA. This will not only simplify the electronics, but the features of modern FPGAs can be utilized to add significant signal processing power to produce higher quality images. In this paper we report on an all-digital pulse pile-up correction algorithm that has been developed for the FPGA. The pile-up mitigation algorithm will allow the scanner to run at higher count rates without incurring large data losses due to the overlapping of scintillation signals. This correction technique utilizes a reference pulse to extract timing and energy information for most pile-up events. Using pulses acquired from a Zecotech Photonics MAPD-N with an LFS-3 scintillator, we show that good timing and energy information can be achieved in the presence of pile-up utilizing a moderate amount of FPGA resources.

Angular Distributions of Discrete Mesoscale Mapping Functions

NASA Astrophysics Data System (ADS)

Kroszczyński, Krzysztof

2015-08-01

The paper presents the results of analyses of numerical experiments concerning GPS signal propagation delays in the atmosphere and the discrete mapping functions defined on their basis. The delays were determined using data from the mesoscale non-hydrostatic weather model operated in the Centre of Applied Geomatics, Military University of Technology. A special attention was paid to investigating angular characteristics of GPS slant delays for low angles of elevation. The investigation proved that the temporal and spatial variability of the slant delays depends to a large extent on current weather conditions.

Air-structure coupling features analysis of mining contra-rotating axial flow fan cascade

NASA Astrophysics Data System (ADS)

Chen, Q. G.; Sun, W.; Li, F.; Zhang, Y. J.

2013-12-01

The interaction between contra-rotating axial flow fan blade and working gas has been studied by means of establishing air-structure coupling control equation and combining Computational Fluid Dynamics (CFD) and Computational solid mechanics (CSM). Based on the single flow channel model, the Finite Volume Method was used to make the field discrete. Additionally, the SIMPLE algorithm, the Standard k-ε model and the Arbitrary Lagrangian-Eulerian dynamic grids technology were utilized to get the airflow motion by solving the discrete governing equations. At the same time, the Finite Element Method was used to make the field discrete to solve dynamic response characteristics of blade. Based on weak coupling method, data exchange from the fluid solver and the solid solver was processed on the coupling interface. Then interpolation was used to obtain the coupling characteristics. The results showed that the blade's maximum amplitude was on the tip of the last-stage blade and aerodynamic force signal could reflect the blade working conditions to some extent. By analyzing the flow regime in contra-rotating axial flow fan, it could be found that the vortex core region was mainly in the blade surface, the hub and the blade clearance. In those regions, the turbulence intensity was very high. The last-stage blade's operating life is shorter than that of the pre-stage blade due to the fatigue fracture occurs much more easily on the last-stage blade which bears more stress.

40 CFR 464.31 - Specialized definitions.

Code of Federal Regulations, 2010 CFR

2010-07-01

... discrete list of toxic organic pollutants for each process segment where it is regulated, as follows: (1... discrete wet scrubbing devices are employed in series in a single melting furnace exhaust gas stream. The ferrous melting furnace scrubber mass allowance shall be given to each discrete wet scrubbing device that...

Wheat mill stream properties for discrete element method modeling

USDA-ARS?s Scientific Manuscript database

A discrete phase approach based on individual wheat kernel characteristics is needed to overcome the limitations of previous statistical models and accurately predict the milling behavior of wheat. As a first step to develop a discrete element method (DEM) model for the wheat milling process, this s...

Robustness of quantum key distribution with discrete and continuous variables to channel noise

NASA Astrophysics Data System (ADS)

Lasota, Mikołaj; Filip, Radim; Usenko, Vladyslav C.

2017-06-01

We study the robustness of quantum key distribution protocols using discrete or continuous variables to the channel noise. We introduce the model of such noise based on coupling of the signal to a thermal reservoir, typical for continuous-variable quantum key distribution, to the discrete-variable case. Then we perform a comparison of the bounds on the tolerable channel noise between these two kinds of protocols using the same noise parametrization, in the case of implementation which is perfect otherwise. Obtained results show that continuous-variable protocols can exhibit similar robustness to the channel noise when the transmittance of the channel is relatively high. However, for strong loss discrete-variable protocols are superior and can overcome even the infinite-squeezing continuous-variable protocol while using limited nonclassical resources. The requirement on the probability of a single-photon production which would have to be fulfilled by a practical source of photons in order to demonstrate such superiority is feasible thanks to the recent rapid development in this field.

Frazzled/DCC facilitates cardiac cell outgrowth and attachment during Drosophila dorsal vessel formation.

PubMed

Macabenta, Frank D; Jensen, Amber G; Cheng, Yi-Shan; Kramer, Joseph J; Kramer, Sunita G

2013-08-15

Drosophila embryonic dorsal vessel (DV) morphogenesis is a highly stereotyped process that involves the migration and morphogenesis of 52 pairs of cardioblasts (CBs) in order to form a linear tube. This process requires spatiotemporally-regulated localization of signaling and adhesive proteins in order to coordinate the formation of a central lumen while maintaining simultaneous adhesion between CBs. Previous studies have shown that the Slit/Roundabout and Netrin/Unc5 repulsive signaling pathways facilitate site-specific loss of adhesion between contralateral CBs in order to form a luminal space. However, the concomitant mechanism by which attraction initiates CB outgrowth and discrete localization of adhesive proteins remains poorly understood. Here we provide genetic evidence that Netrin signals through DCC (Deleted in Colorectal Carcinoma)/UNC-40/Frazzled (Fra) to mediate CB outgrowth and attachment and that this function occurs prior to and independently of Netrin/UNC-5 signaling. fra mRNA is expressed in the CBs prior to and during DV morphogenesis. Loss-of-fra-function results in significant defects in cell shape and alignment between contralateral CB rows. In addition, CB outgrowth and attachment is impaired in both fra loss- and gain-of-function mutants. Deletion of both Netrin genes (NetA and NetB) results in CB attachment phenotypes similar to fra mutants. Similar defects are also seen when both fra and unc5 are deleted. Finally we show that Fra accumulates at dorsal and ventral leading edges of paired CBs, and this localization is dependent upon Netrin. We propose that while repulsive guidance mechanisms contribute to lumen formation by preventing luminal domains from coming together, site-specific Netrin/Frazzled signaling mediates CB attachment. Copyright © 2013 Elsevier Inc. All rights reserved.

Role of stochastic processes in maintaining discrete strain structure in antigenically diverse pathogen populations.

PubMed

Buckee, Caroline O; Recker, Mario; Watkins, Eleanor R; Gupta, Sunetra

2011-09-13

Many highly diverse pathogen populations appear to exist stably as discrete antigenic types despite evidence of genetic exchange. It has been shown that this may arise as a consequence of immune selection on pathogen populations, causing them to segregate permanently into discrete nonoverlapping subsets of antigenic variants to minimize competition for available hosts. However, discrete antigenic strain structure tends to break down under conditions where there are unequal numbers of allelic variants at each locus. Here, we show that the inclusion of stochastic processes can lead to the stable recovery of discrete strain structure through loss of certain alleles. This explains how pathogen populations may continue to behave as independently transmitted strains despite inevitable asymmetries in allelic diversity of major antigens. We present evidence for this type of structuring across global meningococcal isolates in three diverse antigens that are currently being developed as vaccine components.

Apparatus and process for determining the susceptibility of microorganisms to antibiotics

NASA Technical Reports Server (NTRS)

Gibson, Sandra F. (Inventor); Fadler, Norman L. (Inventor)

1976-01-01

A process for determining the susceptibility of microorganisms to antibiotics involves introducing a diluted specimen into discrete quantities of a selective culture medium which favors a specific microorganism in that the microorganism is sustained by the medium and when so sustained will change the optical characteristics of the medium. Only the specific microorganism will alter the optical characteristics. Some of the discrete quantities are blended with known antibiotics, while at least one is not. If the specimen contains the microorganisms favored by the selective medium, the optical characteristics of the discrete quantity of pure selective medium, that is the one without antibiotics, will change. If the antibiotics in any of the other discrete quantities are ineffective against the favored microorganisms, the optical characteristics of those quantities will likewise change. No change in the optical characteristics of a discrete quantity indicates that the favored microorganism is susceptible to the antibiotic in the quantity.

Tape Cassette Bacteria Detection System

NASA Technical Reports Server (NTRS)

1973-01-01

The design, fabrication, and testing of an automatic bacteria detection system with a zero-g capability and based on the filter-capsule approach is described. This system is intended for monitoring the sterility of regenerated water in a spacecraft. The principle of detection is based on measuring the increase in chemiluminescence produced by the action of bacterial porphyrins (i.e., catalase, cytochromes, etc.) on a luminol-hydrogen peroxide mixture. Since viable as well as nonviable organisms initiate this luminescence, viable organisms are detected by comparing the signal of an incubated water sample with an unincubated control. Higher signals for the former indicate the presence of viable organisms. System features include disposable sealed sterile capsules, each containing a filter membrane, for processing discrete water samples and a tape transport for moving these capsules through a processing sequence which involves sample concentration, nutrient addition, incubation, a 4 Molar Urea wash and reaction with luminol-hydrogen peroxide in front of a photomultiplier tube. Liquids are introduced by means of a syringe needle which pierces a rubber septum contained in the wall of the capsule. Detection thresholds obtained with this unit towards E. coli and S. marcescens assuming a 400 ml water sample are indicated.

Tgf-beta induced Erk phosphorylation of smad linker region regulates smad signaling.

PubMed

Hough, Chris; Radu, Maria; Doré, Jules J E

2012-01-01

The Transforming Growth Factor-Beta (TGF-β) family is involved in regulating a variety of cellular processes such as apoptosis, differentiation, and proliferation. TGF-β binding to a Serine/Threonine kinase receptor complex causes the recruitment and subsequent activation of transcription factors known as smad2 and smad3. These proteins subsequently translocate into the nucleus to negatively or positively regulate gene expression. In this study, we define a second signaling pathway leading to TGF-β receptor activation of Extracellular Signal Regulated Kinase (Erk) in a cell-type dependent manner. TGF-β induced Erk activation was found in phenotypically normal mesenchymal cells, but not normal epithelial cells. By activating phosphotidylinositol 3-kinase (PI3K), TGF-β stimulates p21-activated kinase2 (Pak2) to phosphorylate c-Raf, ultimately resulting in Erk activation. Activation of Erk was necessary for TGF-β induced fibroblast replication. In addition, Erk phosphorylated the linker region of nuclear localized smads, resulting in increased half-life of C-terminal phospho-smad 2 and 3 and increased duration of smad target gene transcription. Together, these data show that in mesenchymal cell types the TGF-β/PI3K/Pak2/Raf/MEK/Erk pathway regulates smad signaling, is critical for TGF-β-induced growth and is part of an integrated signaling web containing multiple interacting pathways rather than discrete smad/non-smad pathways.

Analysis of a dynamic model of guard cell signaling reveals the stability of signal propagation

NASA Astrophysics Data System (ADS)

Gan, Xiao; Albert, RéKa

Analyzing the long-term behaviors (attractors) of dynamic models of biological systems can provide valuable insight into biological phenotypes and their stability. We identified the long-term behaviors of a multi-level, 70-node discrete dynamic model of the stomatal opening process in plants. We reduce the model's huge state space by reducing unregulated nodes and simple mediator nodes, and by simplifying the regulatory functions of selected nodes while keeping the model consistent with experimental observations. We perform attractor analysis on the resulting 32-node reduced model by two methods: 1. converting it into a Boolean model, then applying two attractor-finding algorithms; 2. theoretical analysis of the regulatory functions. We conclude that all nodes except two in the reduced model have a single attractor; and only two nodes can admit oscillations. The multistability or oscillations do not affect the stomatal opening level in any situation. This conclusion applies to the original model as well in all the biologically meaningful cases. We further demonstrate the robustness of signal propagation by showing that a large percentage of single-node knockouts does not affect the stomatal opening level. Thus, we conclude that the complex structure of this signal transduction network provides multiple information propagation pathways while not allowing extensive multistability or oscillations, resulting in robust signal propagation. Our innovative combination of methods offers a promising way to analyze multi-level models.

Toward a model for lexical access based on acoustic landmarks and distinctive features

NASA Astrophysics Data System (ADS)

Stevens, Kenneth N.

2002-04-01

This article describes a model in which the acoustic speech signal is processed to yield a discrete representation of the speech stream in terms of a sequence of segments, each of which is described by a set (or bundle) of binary distinctive features. These distinctive features specify the phonemic contrasts that are used in the language, such that a change in the value of a feature can potentially generate a new word. This model is a part of a more general model that derives a word sequence from this feature representation, the words being represented in a lexicon by sequences of feature bundles. The processing of the signal proceeds in three steps: (1) Detection of peaks, valleys, and discontinuities in particular frequency ranges of the signal leads to identification of acoustic landmarks. The type of landmark provides evidence for a subset of distinctive features called articulator-free features (e.g., [vowel], [consonant], [continuant]). (2) Acoustic parameters are derived from the signal near the landmarks to provide evidence for the actions of particular articulators, and acoustic cues are extracted by sampling selected attributes of these parameters in these regions. The selection of cues that are extracted depends on the type of landmark and on the environment in which it occurs. (3) The cues obtained in step (2) are combined, taking context into account, to provide estimates of ``articulator-bound'' features associated with each landmark (e.g., [lips], [high], [nasal]). These articulator-bound features, combined with the articulator-free features in (1), constitute the sequence of feature bundles that forms the output of the model. Examples of cues that are used, and justification for this selection, are given, as well as examples of the process of inferring the underlying features for a segment when there is variability in the signal due to enhancement gestures (recruited by a speaker to make a contrast more salient) or due to overlap of gestures from neighboring segments.

Accuracy of non-resonant laser-induced thermal acoustics (LITA) in a convergent-divergent nozzle flow

NASA Astrophysics Data System (ADS)

Richter, J.; Mayer, J.; Weigand, B.

2018-02-01

Non-resonant laser-induced thermal acoustics (LITA) was applied to measure Mach number, temperature and turbulence level along the centerline of a transonic nozzle flow. The accuracy of the measurement results was systematically studied regarding misalignment of the interrogation beam and frequency analysis of the LITA signals. 2D steady-state Reynolds-averaged Navier-Stokes (RANS) simulations were performed for reference. The simulations were conducted using ANSYS CFX 18 employing the shear-stress transport turbulence model. Post-processing of the LITA signals is performed by applying a discrete Fourier transformation (DFT) to determine the beat frequencies. It is shown that the systematical error of the DFT, which depends on the number of oscillations, signal chirp, and damping rate, is less than 1.5% for our experiments resulting in an average error of 1.9% for Mach number. Further, the maximum calibration error is investigated for a worst-case scenario involving maximum in situ readjustment of the interrogation beam within the limits of constructive interference. It is shown that the signal intensity becomes zero if the interrogation angle is altered by 2%. This, together with the accuracy of frequency analysis, results in an error of about 5.4% for temperature throughout the nozzle. Comparison with numerical results shows good agreement within the error bars.

A wavelet-based statistical analysis of FMRI data: I. motivation and data distribution modeling.

PubMed

Dinov, Ivo D; Boscardin, John W; Mega, Michael S; Sowell, Elizabeth L; Toga, Arthur W

2005-01-01

We propose a new method for statistical analysis of functional magnetic resonance imaging (fMRI) data. The discrete wavelet transformation is employed as a tool for efficient and robust signal representation. We use structural magnetic resonance imaging (MRI) and fMRI to empirically estimate the distribution of the wavelet coefficients of the data both across individuals and spatial locations. An anatomical subvolume probabilistic atlas is used to tessellate the structural and functional signals into smaller regions each of which is processed separately. A frequency-adaptive wavelet shrinkage scheme is employed to obtain essentially optimal estimations of the signals in the wavelet space. The empirical distributions of the signals on all the regions are computed in a compressed wavelet space. These are modeled by heavy-tail distributions because their histograms exhibit slower tail decay than the Gaussian. We discovered that the Cauchy, Bessel K Forms, and Pareto distributions provide the most accurate asymptotic models for the distribution of the wavelet coefficients of the data. Finally, we propose a new model for statistical analysis of functional MRI data using this atlas-based wavelet space representation. In the second part of our investigation, we will apply this technique to analyze a large fMRI dataset involving repeated presentation of sensory-motor response stimuli in young, elderly, and demented subjects.

Peak load demand forecasting using two-level discrete wavelet decomposition and neural network algorithm

NASA Astrophysics Data System (ADS)

Bunnoon, Pituk; Chalermyanont, Kusumal; Limsakul, Chusak

2010-02-01

This paper proposed the discrete transform and neural network algorithms to obtain the monthly peak load demand in mid term load forecasting. The mother wavelet daubechies2 (db2) is employed to decomposed, high pass filter and low pass filter signals from the original signal before using feed forward back propagation neural network to determine the forecasting results. The historical data records in 1997-2007 of Electricity Generating Authority of Thailand (EGAT) is used as reference. In this study, historical information of peak load demand(MW), mean temperature(Tmean), consumer price index (CPI), and industrial index (economic:IDI) are used as feature inputs of the network. The experimental results show that the Mean Absolute Percentage Error (MAPE) is approximately 4.32%. This forecasting results can be used for fuel planning and unit commitment of the power system in the future.

Using an Artificial Neural Bypass to Restore Cortical Control of Rhythmic Movements in a Human with Quadriplegia

NASA Astrophysics Data System (ADS)

Sharma, Gaurav; Friedenberg, David A.; Annetta, Nicholas; Glenn, Bradley; Bockbrader, Marcie; Majstorovic, Connor; Domas, Stephanie; Mysiw, W. Jerry; Rezai, Ali; Bouton, Chad

2016-09-01

Neuroprosthetic technology has been used to restore cortical control of discrete (non-rhythmic) hand movements in a paralyzed person. However, cortical control of rhythmic movements which originate in the brain but are coordinated by Central Pattern Generator (CPG) neural networks in the spinal cord has not been demonstrated previously. Here we show a demonstration of an artificial neural bypass technology that decodes cortical activity and emulates spinal cord CPG function allowing volitional rhythmic hand movement. The technology uses a combination of signals recorded from the brain, machine-learning algorithms to decode the signals, a numerical model of CPG network, and a neuromuscular electrical stimulation system to evoke rhythmic movements. Using the neural bypass, a quadriplegic participant was able to initiate, sustain, and switch between rhythmic and discrete finger movements, using his thoughts alone. These results have implications in advancing neuroprosthetic technology to restore complex movements in people living with paralysis.

Method and apparatus for generating motor current spectra to enhance motor system fault detection

DOEpatents

Linehan, Daniel J.; Bunch, Stanley L.; Lyster, Carl T.

1995-01-01

A method and circuitry for sampling periodic amplitude modulations in a nonstationary periodic carrier wave to determine frequencies in the amplitude modulations. The method and circuit are described in terms of an improved motor current signature analysis. The method insures that the sampled data set contains an exact whole number of carrier wave cycles by defining the rate at which samples of motor current data are collected. The circuitry insures that a sampled data set containing stationary carrier waves is recreated from the analog motor current signal containing nonstationary carrier waves by conditioning the actual sampling rate to adjust with the frequency variations in the carrier wave. After the sampled data is transformed to the frequency domain via the Discrete Fourier Transform, the frequency distribution in the discrete spectra of those components due to the carrier wave and its harmonics will be minimized so that signals of interest are more easily analyzed.

Networked event-triggered control: an introduction and research trends

NASA Astrophysics Data System (ADS)

Mahmoud, Magdi S.; Sabih, Muhammad

2014-11-01

A physical system can be studied as either continuous time or discrete-time system depending upon the control objectives. Discrete-time control systems can be further classified into two categories based on the sampling: (1) time-triggered control systems and (2) event-triggered control systems. Time-triggered systems sample states and calculate controls at every sampling instant in a periodic fashion, even in cases when states and calculated control do not change much. This indicates unnecessary and useless data transmission and computation efforts of a time-triggered system, thus inefficiency. For networked systems, the transmission of measurement and control signals, thus, cause unnecessary network traffic. Event-triggered systems, on the other hand, have potential to reduce the communication burden in addition to reducing the computation of control signals. This paper provides an up-to-date survey on the event-triggered methods for control systems and highlights the potential research directions.

Small-signal model for the series resonant converter

NASA Technical Reports Server (NTRS)

King, R. J.; Stuart, T. A.

1985-01-01

The results of a previous discrete-time model of the series resonant dc-dc converter are reviewed and from these a small signal dynamic model is derived. This model is valid for low frequencies and is based on the modulation of the diode conduction angle for control. The basic converter is modeled separately from its output filter to facilitate the use of these results for design purposes. Experimental results are presented.

Regional Seismic Arrays and Nuclear Test Ban Verification

DTIC Science & Technology

1990-12-01

estimation has been difficult to automate, at least for regional and teleseismic signals. A neural network approach might be applicable here. The data must...use of trained neural networks . Of the 95 events examined, 66 were selected for the classification study based on high signal-to-noise ratio and...the International Joint Conference on Neural Networks , Washington, D.C., June, 1989. Menke, W. Geophysical Data Analysis : Discrete Inverse Theory

The short time Fourier transform and local signals

NASA Astrophysics Data System (ADS)

Okumura, Shuhei

In this thesis, I examine the theoretical properties of the short time discrete Fourier transform (STFT). The STFT is obtained by applying the Fourier transform by a fixed-sized, moving window to input series. We move the window by one time point at a time, so we have overlapping windows. I present several theoretical properties of the STFT, applied to various types of complex-valued, univariate time series inputs, and their outputs in closed forms. In particular, just like the discrete Fourier transform, the STFT's modulus time series takes large positive values when the input is a periodic signal. One main point is that a white noise time series input results in the STFT output being a complex-valued stationary time series and we can derive the time and time-frequency dependency structure such as the cross-covariance functions. Our primary focus is the detection of local periodic signals. I present a method to detect local signals by computing the probability that the squared modulus STFT time series has consecutive large values exceeding some threshold after one exceeding observation following one observation less than the threshold. We discuss a method to reduce the computation of such probabilities by the Box-Cox transformation and the delta method, and show that it works well in comparison to the Monte Carlo simulation method.

Exact reconstruction with directional wavelets on the sphere

NASA Astrophysics Data System (ADS)

Wiaux, Y.; McEwen, J. D.; Vandergheynst, P.; Blanc, O.

2008-08-01

A new formalism is derived for the analysis and exact reconstruction of band-limited signals on the sphere with directional wavelets. It represents an evolution of a previously developed wavelet formalism developed by Antoine & Vandergheynst and Wiaux et al. The translations of the wavelets at any point on the sphere and their proper rotations are still defined through the continuous three-dimensional rotations. The dilations of the wavelets are directly defined in harmonic space through a new kernel dilation, which is a modification of an existing harmonic dilation. A family of factorized steerable functions with compact harmonic support which are suitable for this kernel dilation are first identified. A scale-discretized wavelet formalism is then derived, relying on this dilation. The discrete nature of the analysis scales allows the exact reconstruction of band-limited signals. A corresponding exact multi-resolution algorithm is finally described and an implementation is tested. The formalism is of interest notably for the denoising or the deconvolution of signals on the sphere with a sparse expansion in wavelets. In astrophysics, it finds a particular application for the identification of localized directional features in the cosmic microwave background data, such as the imprint of topological defects, in particular, cosmic strings, and for their reconstruction after separation from the other signal components.

Finite Volume Element (FVE) discretization and multilevel solution of the axisymmetric heat equation

NASA Astrophysics Data System (ADS)

Litaker, Eric T.

1994-12-01

The axisymmetric heat equation, resulting from a point-source of heat applied to a metal block, is solved numerically; both iterative and multilevel solutions are computed in order to compare the two processes. The continuum problem is discretized in two stages: finite differences are used to discretize the time derivatives, resulting is a fully implicit backward time-stepping scheme, and the Finite Volume Element (FVE) method is used to discretize the spatial derivatives. The application of the FVE method to a problem in cylindrical coordinates is new, and results in stencils which are analyzed extensively. Several iteration schemes are considered, including both Jacobi and Gauss-Seidel; a thorough analysis of these schemes is done, using both the spectral radii of the iteration matrices and local mode analysis. Using this discretization, a Gauss-Seidel relaxation scheme is used to solve the heat equation iteratively. A multilevel solution process is then constructed, including the development of intergrid transfer and coarse grid operators. Local mode analysis is performed on the components of the amplification matrix, resulting in the two-level convergence factors for various combinations of the operators. A multilevel solution process is implemented by using multigrid V-cycles; the iterative and multilevel results are compared and discussed in detail. The computational savings resulting from the multilevel process are then discussed.

15 CFR 301.5 - Processing of applications by the Department of Commerce.

Code of Federal Regulations, 2010 CFR

2010-01-01

... the information contained in the prior submission, shall not be considered in making the decision on... his discretion, may take into account factual information contained in untimely comments. (6... discretion at any stage of processing to insert into the record and consider in making his decision any...

Precision analysis of the photomultiplier response to ultra low signals

NASA Astrophysics Data System (ADS)

Degtiarenko, Pavel

2017-11-01

A new computational model for the description of the photon detector response functions measured in conditions of low light is presented, together with examples of the observed photomultiplier signal amplitude distributions, successfully described using the parameterized model equation. In extension to the previously known approximations, the new model describes the underlying discrete statistical behavior of the photoelectron cascade multiplication processes in photon detectors with complex non-uniform gain structure of the first dynode. Important features of the model include the ability to represent the true single-photoelectron spectra from different photomultipliers with a variety of parameterized shapes, reflecting the variability in the design and in the individual parameters of the detectors. The new software tool is available for evaluation of the detectors' performance, response, and efficiency parameters that may be used in various applications including the ultra low background experiments such as the searches for Dark Matter and rare decays, underground neutrino studies, optimizing operations of the Cherenkov light detectors, help in the detector selection procedures, and in the experiment simulations.

Optimum quantum receiver for detecting weak signals in PAM communication systems

NASA Astrophysics Data System (ADS)

Sharma, Navneet; Rawat, Tarun Kumar; Parthasarathy, Harish; Gautam, Kumar

2017-09-01

This paper deals with the modeling of an optimum quantum receiver for pulse amplitude modulator (PAM) communication systems. The information bearing sequence {I_k}_{k=0}^{N-1} is estimated using the maximum likelihood (ML) method. The ML method is based on quantum mechanical measurements of an observable X in the Hilbert space of the quantum system at discrete times, when the Hamiltonian of the system is perturbed by an operator obtained by modulating a potential V with a PAM signal derived from the information bearing sequence {I_k}_{k=0}^{N-1}. The measurement process at each time instant causes collapse of the system state to an observable eigenstate. All probabilities of getting different outcomes from an observable are calculated using the perturbed evolution operator combined with the collapse postulate. For given probability densities, calculation of the mean square error evaluates the performance of the receiver. Finally, we present an example involving estimating an information bearing sequence that modulates a quantum electromagnetic field incident on a quantum harmonic oscillator.

Estimation of images degraded by film-grain noise.

PubMed

Naderi, F; Sawchuk, A A

1978-04-15

Film-grain noise describes the intrinsic noise produced by a photographic emulsion during the process of image recording and reproduction. In this paper we consider the restoration of images degraded by film-grain noise. First a detailed model for the over-all photographic imaging system is presented. The model includes linear blurring effects and the signal-dependent effect of film-grain noise. The accuracy of this model is tested by simulating images according to it and comparing the results to images of similar targets that were actually recorded on film. The restoration of images degraded by film-grain noise is then considered in the context of estimation theory. A discrete Wiener filer is developed which explicitly allows for the signal dependence of the noise. The filter adaptively alters its characteristics based on the nonstationary first order statistics of an image and is shown to have advantages over the conventional Wiener filter. Experimental results for modeling and the adaptive estimation filter are presented.

X-chromosome-counting mechanisms that determine nematode sex.

PubMed

Nicoll, M; Akerib, C C; Meyer, B J

1997-07-10

Sex is determined in Caenorhabditis elegans by an X-chromosome-counting mechanism that reliably distinguishes the twofold difference in X-chromosome dose between males (1X) and hermaphrodites (2X). This small quantitative difference is translated into the 'on/off' response of the target gene, xol-1, a switch that specifies the male fate when active and the hermaphrodite fate when inactive. Specific regions of X contain counted signal elements whose combined dose sets the activity of xol-1. Here we ascribe the dose effects of one region to a discrete, protein-encoding gene, fox-1. We demonstrate that the dose-sensitive signal elements on chromosome X control xol-1 through two different molecular mechanisms. One involves the transcriptional repression of xol-1 in XX animals. The other uses the putative RNA-binding protein encoded by fox-1 to reduce the level of xol-1 protein. These two mechanisms of repression act together to ensure the fidelity of the X-chromosome counting process.

System for memorizing maximum values

NASA Technical Reports Server (NTRS)

Bozeman, Richard J., Jr. (Inventor)

1992-01-01

The invention discloses a system capable of memorizing maximum sensed values. The system includes conditioning circuitry which receives the analog output signal from a sensor transducer. The conditioning circuitry rectifies and filters the analog signal and provides an input signal to a digital driver, which may be either linear or logarithmic. The driver converts the analog signal to discrete digital values, which in turn triggers an output signal on one of a plurality of driver output lines n. The particular output lines selected is dependent on the converted digital value. A microfuse memory device connects across the driver output lines, with n segments. Each segment is associated with one driver output line, and includes a microfuse that is blown when a signal appears on the associated driver output line.

System for memorizing maximum values

NASA Astrophysics Data System (ADS)

Bozeman, Richard J., Jr.

1992-08-01

The invention discloses a system capable of memorizing maximum sensed values. The system includes conditioning circuitry which receives the analog output signal from a sensor transducer. The conditioning circuitry rectifies and filters the analog signal and provides an input signal to a digital driver, which may be either linear or logarithmic. The driver converts the analog signal to discrete digital values, which in turn triggers an output signal on one of a plurality of driver output lines n. The particular output lines selected is dependent on the converted digital value. A microfuse memory device connects across the driver output lines, with n segments. Each segment is associated with one driver output line, and includes a microfuse that is blown when a signal appears on the associated driver output line.

System for Memorizing Maximum Values

NASA Technical Reports Server (NTRS)

Bozeman, Richard J., Jr. (Inventor)

1996-01-01

The invention discloses a system capable of memorizing maximum sensed values. The system includes conditioning circuitry which receives the analog output signal from a sensor transducer. The conditioning circuitry rectifies and filters the analog signal and provides an input signal to a digital driver, which may be either liner or logarithmic. The driver converts the analog signal to discrete digital values, which in turn triggers an output signal on one of a plurality of driver output lines n. The particular output lines selected is dependent on the converted digital value. A microfuse memory device connects across the driver output lines, with n segments. Each segment is associated with one driver output line, and includes a microfuse that is blown when a signal appears on the associated driver output line.

ECG Signal Analysis and Arrhythmia Detection using Wavelet Transform

NASA Astrophysics Data System (ADS)

Kaur, Inderbir; Rajni, Rajni; Marwaha, Anupma

2016-12-01

Electrocardiogram (ECG) is used to record the electrical activity of the heart. The ECG signal being non-stationary in nature, makes the analysis and interpretation of the signal very difficult. Hence accurate analysis of ECG signal with a powerful tool like discrete wavelet transform (DWT) becomes imperative. In this paper, ECG signal is denoised to remove the artifacts and analyzed using Wavelet Transform to detect the QRS complex and arrhythmia. This work is implemented in MATLAB software for MIT/BIH Arrhythmia database and yields the sensitivity of 99.85 %, positive predictivity of 99.92 % and detection error rate of 0.221 % with wavelet transform. It is also inferred that DWT outperforms principle component analysis technique in detection of ECG signal.

Estimation of effect of hydrogen on the parameters of magnetoacoustic emission signals

NASA Astrophysics Data System (ADS)

Skalskyi, Valentyn; Stankevych, Olena; Dubytskyi, Olexandr

2018-05-01

The features of the magnetoacoustic emission (MAE) signals during magnetization of structural steels with the different degree of hydrogenating were investigated by the wavelet transform. The dominant frequency ranges of MAE signals for the different magnetic field strength were determined using Discrete Wavelet Transform (DWT), and the energy and spectral parameters of MAE signals were determined using Continuous Wavelet Transform (CWT). The characteristic differences of the local maximums of signals according to energy, bandwidth, duration and frequency were found. The methodology of estimation of state of local degradation of materials by parameters of wavelet transform of MAE signals was proposed. This methodology was approbated for investigate of state of long-time exploitations structural steels of oil and gas pipelines.

Dynamic multiprotein assemblies shape the spatial structure of cell signaling.

PubMed

Nussinov, Ruth; Jang, Hyunbum

2014-01-01

Cell signaling underlies critical cellular decisions. Coordination, efficiency as well as fail-safe mechanisms are key elements. How the cell ensures that these hallmarks are at play are important questions. Cell signaling is often viewed as taking place through discrete and cross-talking pathways; oftentimes these are modularized to emphasize distinct functions. While simple, convenient and clear, such models largely neglect the spatial structure of cell signaling; they also convey inter-modular (or inter-protein) spatial separation that may not exist. Here our thesis is that cell signaling is shaped by a network of multiprotein assemblies. While pre-organized, the assemblies and network are loose and dynamic. They contain transiently-associated multiprotein complexes which are often mediated by scaffolding proteins. They are also typically anchored in the membrane, and their continuum may span the cell. IQGAP1 scaffolding protein which binds proteins including Raf, calmodulin, Mek, Erk, actin, and tens more, with actin shaping B-cell (and likely other) membrane-anchored nanoclusters and allosterically polymerizing in dynamic cytoskeleton formation, and Raf anchoring in the membrane along with Ras, provides a striking example. The multivalent network of dynamic proteins and lipids, with specific interactions forming and breaking, can be viewed as endowing gel-like properties. Collectively, this reasons that efficient, productive and reliable cell signaling takes place primarily through transient, preorganized and cooperative protein-protein interactions spanning the cell rather than stochastic, diffusion-controlled processes. Copyright © 2014 Elsevier Ltd. All rights reserved.

Signal Processing Methods for Liquid Rocket Engine Combustion Stability Assessments

NASA Technical Reports Server (NTRS)

Kenny, R. Jeremy; Lee, Erik; Hulka, James R.; Casiano, Matthew

2011-01-01

The J2X Gas Generator engine design specifications include dynamic, spontaneous, and broadband combustion stability requirements. These requirements are verified empirically based high frequency chamber pressure measurements and analyses. Dynamic stability is determined with the dynamic pressure response due to an artificial perturbation of the combustion chamber pressure (bomb testing), and spontaneous and broadband stability are determined from the dynamic pressure responses during steady operation starting at specified power levels. J2X Workhorse Gas Generator testing included bomb tests with multiple hardware configurations and operating conditions, including a configuration used explicitly for engine verification test series. This work covers signal processing techniques developed at Marshall Space Flight Center (MSFC) to help assess engine design stability requirements. Dynamic stability assessments were performed following both the CPIA 655 guidelines and a MSFC in-house developed statistical-based approach. The statistical approach was developed to better verify when the dynamic pressure amplitudes corresponding to a particular frequency returned back to pre-bomb characteristics. This was accomplished by first determining the statistical characteristics of the pre-bomb dynamic levels. The pre-bomb statistical characterization provided 95% coverage bounds; these bounds were used as a quantitative measure to determine when the post-bomb signal returned to pre-bomb conditions. The time for post-bomb levels to acceptably return to pre-bomb levels was compared to the dominant frequency-dependent time recommended by CPIA 655. Results for multiple test configurations, including stable and unstable configurations, were reviewed. Spontaneous stability was assessed using two processes: 1) characterization of the ratio of the peak response amplitudes to the excited chamber acoustic mode amplitudes and 2) characterization of the variability of the peak response's frequency over the test duration. This characterization process assists in evaluating the discreteness of a signal as well as the stability of the chamber response. Broadband stability was assessed using a running root-mean-square evaluation. These techniques were also employed, in a comparative analysis, on available Fastrac data, and these results are presented here.

Mortar and artillery variants classification by exploiting characteristics of the acoustic signature

NASA Astrophysics Data System (ADS)

Hohil, Myron E.; Grasing, David; Desai, Sachi; Morcos, Amir

2007-10-01

Feature extraction methods based on the discrete wavelet transform and multiresolution analysis facilitate the development of a robust classification algorithm that reliably discriminates mortar and artillery variants via acoustic signals produced during the launch/impact events. Utilizing acoustic sensors to exploit the sound waveform generated from the blast for the identification of mortar and artillery variants. Distinct characteristics arise within the different mortar variants because varying HE mortar payloads and related charges emphasize concussive and shrapnel effects upon impact employing varying magnitude explosions. The different mortar variants are characterized by variations in the resulting waveform of the event. The waveform holds various harmonic properties distinct to a given mortar/artillery variant that through advanced signal processing techniques can employed to classify a given set. The DWT and other readily available signal processing techniques will be used to extract the predominant components of these characteristics from the acoustic signatures at ranges exceeding 2km. Exploiting these techniques will help develop a feature set highly independent of range, providing discrimination based on acoustic elements of the blast wave. Highly reliable discrimination will be achieved with a feed-forward neural network classifier trained on a feature space derived from the distribution of wavelet coefficients, frequency spectrum, and higher frequency details found within different levels of the multiresolution decomposition. The process that will be described herein extends current technologies, which emphasis multi modal sensor fusion suites to provide such situational awareness. A two fold problem of energy consumption and line of sight arise with the multi modal sensor suites. The process described within will exploit the acoustic properties of the event to provide variant classification as added situational awareness to the solider.

Adaptive NN controller design for a class of nonlinear MIMO discrete-time systems.

PubMed

Liu, Yan-Jun; Tang, Li; Tong, Shaocheng; Chen, C L Philip

2015-05-01

An adaptive neural network tracking control is studied for a class of multiple-input multiple-output (MIMO) nonlinear systems. The studied systems are in discrete-time form and the discretized dead-zone inputs are considered. In addition, the studied MIMO systems are composed of N subsystems, and each subsystem contains unknown functions and external disturbance. Due to the complicated framework of the discrete-time systems, the existence of the dead zone and the noncausal problem in discrete-time, it brings about difficulties for controlling such a class of systems. To overcome the noncausal problem, by defining the coordinate transformations, the studied systems are transformed into a special form, which is suitable for the backstepping design. The radial basis functions NNs are utilized to approximate the unknown functions of the systems. The adaptation laws and the controllers are designed based on the transformed systems. By using the Lyapunov method, it is proved that the closed-loop system is stable in the sense that the semiglobally uniformly ultimately bounded of all the signals and the tracking errors converge to a bounded compact set. The simulation examples and the comparisons with previous approaches are provided to illustrate the effectiveness of the proposed control algorithm.

Optoelectronic image scanning with high spatial resolution and reconstruction fidelity

NASA Astrophysics Data System (ADS)

Craubner, Siegfried I.

2002-02-01

In imaging systems the detector arrays deliver at the output time-discrete signals, where the spatial frequencies of the object scene are mapped into the electrical signal frequencies. Since the spatial frequency spectrum cannot be bandlimited by the front optics, the usual detector arrays perform a spatial undersampling and as a consequence aliasing occurs. A means to partially suppress the backfolded alias band is bandwidth limitation in the reconstruction low-pass, at the price of resolution loss. By utilizing a bilinear detector array in a pushbroom-type scanner, undersampling and aliasing can be overcome. For modeling the perception, the theory of discrete systems and multirate digital filter banks is applied, where aliasing cancellation and perfect reconstruction play an important role. The discrete transfer function of a bilinear array can be imbedded into the scheme of a second-order filter bank. The detector arrays already build the analysis bank and the overall filter bank is completed with the synthesis bank, for which stabilized inverse filters are proposed, to compensate for the low-pass characteristics and to approximate perfect reconstruction. The synthesis filter branch can be realized in a so-called `direct form,' or the `polyphase form,' where the latter is an expenditure-optimal solution, which gives advantages when implemented in a signal processor. This paper attempts to introduce well-established concepts of the theory of multirate filter banks into the analysis of scanning imagers, which is applicable in a much broader sense than for the problems addressed here. To the author's knowledge this is also a novelty.

Discrete wavelet-aided delineation of PCG signal events via analysis of an area curve length-based decision statistic.

PubMed

Homaeinezhad, M R; Atyabi, S A; Daneshvar, E; Ghaffari, A; Tahmasebi, M

2010-12-01

The aim of this study is to describe a robust unified framework for segmentation of the phonocardiogram (PCG) signal sounds based on the false-alarm probability (FAP) bounded segmentation of a properly calculated detection measure. To this end, first the original PCG signal is appropriately pre-processed and then, a fixed sample size sliding window is moved on the pre-processed signal. In each slid, the area under the excerpted segment is multiplied by its curve-length to generate the Area Curve Length (ACL) metric to be used as the segmentation decision statistic (DS). Afterwards, histogram parameters of the nonlinearly enhanced DS metric are used for regulation of the α-level Neyman-Pearson classifier for FAP-bounded delineation of the PCG events. The proposed method was applied to all 85 records of Nursing Student Heart Sounds database (NSHSDB) including stenosis, insufficiency, regurgitation, gallop, septal defect, split sound, rumble, murmur, clicks, friction rub and snap disorders with different sampling frequencies. Also, the method was applied to the records obtained from an electronic stethoscope board designed for fulfillment of this study in the presence of high-level power-line noise and external disturbing sounds and as the results, no false positive (FP) or false negative (FN) errors were detected. High noise robustness, acceptable detection-segmentation accuracy of PCG events in various cardiac system conditions, and having no parameters dependency to the acquisition sampling frequency can be mentioned as the principal virtues and abilities of the proposed ACL-based PCG events detection-segmentation algorithm.

Molecular, pharmacological, and signaling properties of octopamine receptors from honeybee (Apis mellifera) brain.

PubMed

Balfanz, Sabine; Jordan, Nadine; Langenstück, Teresa; Breuer, Johanna; Bergmeier, Vera; Baumann, Arnd

2014-04-01

G protein-coupled receptors are important regulators of cellular signaling processes. Within the large family of rhodopsin-like receptors, those binding to biogenic amines form a discrete subgroup. Activation of biogenic amine receptors leads to transient changes of intracellular Ca²⁺-([Ca²⁺](i)) or 3',5'-cyclic adenosine monophosphate ([cAMP](i)) concentrations. Both second messengers modulate cellular signaling processes and thereby contribute to long-lasting behavioral effects in an organism. In vivo pharmacology has helped to reveal the functional effects of different biogenic amines in honeybees. The phenolamine octopamine is an important modulator of behavior. Binding of octopamine to its receptors causes elevation of [Ca²⁺](i) or [cAMP](i). To date, only one honeybee octopamine receptor that induces Ca²⁺ signals has been molecularly and pharmacologically characterized. Here, we examined the pharmacological properties of four additional honeybee octopamine receptors. When heterologously expressed, all receptors induced cAMP production after binding to octopamine with EC₅₀(s) in the nanomolar range. Receptor activity was most efficiently blocked by mianserin, a substance with antidepressant activity in vertebrates. The rank order of inhibitory potency for potential receptor antagonists was very similar on all four honeybee receptors with mianserin > cyproheptadine > metoclopramide > chlorpromazine > phentolamine. The subroot of octopamine receptors activating adenylyl cyclases is the largest that has so far been characterized in arthropods, and it should now be possible to unravel the contribution of individual receptors to the physiology and behavior of honeybees. © 2013 International Society for Neurochemistry.

Hybrid Discrete-Continuous Markov Decision Processes

NASA Technical Reports Server (NTRS)

Feng, Zhengzhu; Dearden, Richard; Meuleau, Nicholas; Washington, Rich

2003-01-01

This paper proposes a Markov decision process (MDP) model that features both discrete and continuous state variables. We extend previous work by Boyan and Littman on the mono-dimensional time-dependent MDP to multiple dimensions. We present the principle of lazy discretization, and piecewise constant and linear approximations of the model. Having to deal with several continuous dimensions raises several new problems that require new solutions. In the (piecewise) linear case, we use techniques from partially- observable MDPs (POMDPS) to represent value functions as sets of linear functions attached to different partitions of the state space.

Amplifying (Im)perfection: The Impact of Crystallinity in Discrete and Disperse Block Co-oligomers

PubMed Central

2017-01-01

Crystallinity is seldomly utilized as part of the microphase segregation process in ultralow-molecular-weight block copolymers. Here, we show the preparation of two types of discrete, semicrystalline block co-oligomers, comprising an amorphous oligodimethylsiloxane block and a crystalline oligo-l-lactic acid or oligomethylene block. The self-assembly of these discrete materials results in lamellar structures with unforeseen uniformity in the domain spacing. A systematic introduction of dispersity reveals the extreme sensitivity of the microphase segregation process toward chain length dispersity in the crystalline block. PMID:28994585

Amplifying (Im)perfection: The Impact of Crystallinity in Discrete and Disperse Block Co-oligomers.

PubMed

van Genabeek, Bas; Lamers, Brigitte A G; de Waal, Bas F M; van Son, Martin H C; Palmans, Anja R A; Meijer, E W

2017-10-25

Crystallinity is seldomly utilized as part of the microphase segregation process in ultralow-molecular-weight block copolymers. Here, we show the preparation of two types of discrete, semicrystalline block co-oligomers, comprising an amorphous oligodimethylsiloxane block and a crystalline oligo-l-lactic acid or oligomethylene block. The self-assembly of these discrete materials results in lamellar structures with unforeseen uniformity in the domain spacing. A systematic introduction of dispersity reveals the extreme sensitivity of the microphase segregation process toward chain length dispersity in the crystalline block.

78 FR 61113 - Acquisition Process: Task and Delivery Order Contracts, Bundling, Consolidation

Federal Register 2010, 2011, 2012, 2013, 2014

2013-10-02

... that a total set-aside is not appropriate but the procurement can be broken up into smaller discrete... discrete components to support a partial set-aside and market research shows that either: at least two... could divide a multiple award contract for divergent goods and services into discrete categories (which...

Discrete Photodetection and Susskind-Glogower Phase Operators

NASA Technical Reports Server (NTRS)

Ben-Aryeh, Y.

1996-01-01

State reduction processes in different types of photodetection experiments are described by using different kinds of ladder operators. A special model of discrete photodetection is developed by the use of superoperators which are based on the Susskind-Glogower raising and lower operators. The possibility to realize experimentally the discrete photodetection scheme in a micromaser is discussed.

Non-verbal numerical cognition: from reals to integers.

PubMed

Gallistel; Gelman

2000-02-01

Data on numerical processing by verbal (human) and non-verbal (animal and human) subjects are integrated by the hypothesis that a non-verbal counting process represents discrete (countable) quantities by means of magnitudes with scalar variability. These appear to be identical to the magnitudes that represent continuous (uncountable) quantities such as duration. The magnitudes representing countable quantity are generated by a discrete incrementing process, which defines next magnitudes and yields a discrete ordering. In the case of continuous quantities, the continuous accumulation process does not define next magnitudes, so the ordering is also continuous ('dense'). The magnitudes representing both countable and uncountable quantity are arithmetically combined in, for example, the computation of the income to be expected from a foraging patch. Thus, on the hypothesis presented here, the primitive machinery for arithmetic processing works with real numbers (magnitudes).

Generalized predictive control for a coupled four tank MIMO system using a continuous-discrete time observer.

PubMed

Gouta, Houssemeddine; Hadj Saïd, Salim; Barhoumi, Nabil; M'Sahli, Faouzi

2017-03-01

This paper deals with the problem of the observer based control design for a coupled four-tank liquid level system. For this MIMO system's dynamics, motivated by a desire to provide precise and sensorless liquid level control, a nonlinear predictive controller based on a continuous-discrete observer is presented. First, an analytical solution from the model predictive control (MPC) technique is developed for a particular class of nonlinear MIMO systems and its corresponding exponential stability is proven. Then, a high gain observer that runs in continuous-time with an output error correction time that is updated in a mixed continuous-discrete fashion is designed in order to estimate the liquid levels in the two upper tanks. The effectiveness of the designed control schemes are validated by two tests; The first one is maintaining a constant level in the first bottom tank while making the level in the second bottom tank to follow a sinusoidal reference signal. The second test is more difficult and it is made using two trapezoidal reference signals in order to see the decoupling performance of the system's outputs. Simulation and experimental results validate the objective of the paper. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

(Small) Resonant non-Gaussianities: Signatures of a Discrete Shift Symmetry in the Effective Field Theory of Inflation

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

Behbahani, Siavosh R.; /SLAC /Stanford U., Phys. Dept. /Boston U.; Dymarsky, Anatoly

2012-06-06

We apply the Effective Field Theory of Inflation to study the case where the continuous shift symmetry of the Goldstone boson {pi} is softly broken to a discrete subgroup. This case includes and generalizes recently proposed String Theory inspired models of Inflation based on Axion Monodromy. The models we study have the property that the 2-point function oscillates as a function of the wavenumber, leading to oscillations in the CMB power spectrum. The non-linear realization of time diffeomorphisms induces some self-interactions for the Goldstone boson that lead to a peculiar non-Gaussianity whose shape oscillates as a function of the wavenumber.more » We find that in the regime of validity of the effective theory, the oscillatory signal contained in the n-point correlation functions, with n > 2, is smaller than the one contained in the 2-point function, implying that the signature of oscillations, if ever detected, will be easier to find first in the 2-point function, and only then in the higher order correlation functions. Still the signal contained in higher-order correlation functions, that we study here in generality, could be detected at a subleading level, providing a very compelling consistency check for an approximate discrete shift symmetry being realized during inflation.« less

Identification of the fragmentation of brittle particles during compaction process by the acoustic emission technique.

PubMed

Favretto-Cristini, Nathalie; Hégron, Lise; Sornay, Philippe

2016-04-01

Some nuclear fuels are currently manufactured by a powder metallurgy process that consists of three main steps, namely preparation of the powders, powder compaction, and sintering of the compact. An optimum between size, shape and cohesion of the particles of the nuclear fuels must be sought in order to obtain a compact with a sufficient mechanical strength, and to facilitate the release of helium and fission gases during irradiation through pores connected to the outside of the pellet after sintering. Being simple to adapt to nuclear-oriented purposes, the Acoustic Emission (AE) technique is used to control the microstructure of the compact by monitoring the compaction of brittle Uranium Dioxide (UO2) particles of a few hundred micrometers. The objective is to identify in situ the mechanisms that occur during the UO2 compaction, and more specifically the particle fragmentation that is linked to the open porosity of the nuclear matter. Three zones of acoustic activity, strongly related to the applied stress, can be clearly defined from analysis of the continuous signals recorded during the compaction process. They correspond to particle rearrangement and/or fragmentation. The end of the noteworthy fragmentation process is clearly defined as the end of the significant process that increases the compactness of the material. Despite the fact that the wave propagation strongly evolves during the compaction process, the acoustic signature of the fragmentation of a single UO2 particle and a bed of UO2 particles under compaction is well identified. The waveform, with a short rise time and an exponential-like decay of the signal envelope, is the most reliable descriptor. The impact of the particle size and cohesion on the AE activity, and then on the fragmentation domain, is analyzed through the discrete AE signals. The maximum amplitude of the burst signals, as well as the mean stress corresponding to the end of the recorded AE, increase with increasing mean diameter of the particles. Moreover, the maximum burst amplitude increases with increasing particle cohesion. Copyright © 2015 Elsevier B.V. All rights reserved.

Resolving ability and image discretization in the visual system.

PubMed

Shelepin, Yu E; Bondarko, V M

2004-02-01

Psychophysiological studies were performed to measure the spatial threshold for resolution of two "points" and the thresholds for discriminating their orientations depending on the distance between the two points. Data were compared with the scattering of the "point" by the eye's optics, the packing density of cones in the fovea, and the characteristics of the receptive fields of ganglion cells in the foveal area of the retina and neurons in the corresponding projection zones of the primary visual cortex. The effective zone was shown to have to contain a scattering function for several receptors, as this allowed preliminary blurring of the image by the eye's optics to decrease the subsequent (at the level of receptors) discretization noise created by a matrix of receptors. The concordance of these parameters supports the optical operation of the spatial elements of the neural network determining the resolving ability of the visual system at different levels of visual information processing. It is suggested that the special geometry of the receptive fields of neurons in the striate cortex, which are concordant with the statistics of natural scenes, results in a further increase in the signal:noise ratio.

Causal Correlation Functions and Fourier Transforms: Application in Calculating Pressure Induced Shifts

NASA Technical Reports Server (NTRS)

Ma, Q.; Tipping, R. H.; Lavrentieva, N. N.

2012-01-01

By adopting a concept from signal processing, instead of starting from the correlation functions which are even, one considers the causal correlation functions whose Fourier transforms become complex. Their real and imaginary parts multiplied by 2 are the Fourier transforms of the original correlations and the subsequent Hilbert transforms, respectively. Thus, by taking this step one can complete the two previously needed transforms. However, to obviate performing the Cauchy principal integrations required in the Hilbert transforms is the greatest advantage. Meanwhile, because the causal correlations are well-bounded within the time domain and band limited in the frequency domain, one can replace their Fourier transforms by the discrete Fourier transforms and the latter can be carried out with the FFT algorithm. This replacement is justified by sampling theory because the Fourier transforms can be derived from the discrete Fourier transforms with the Nyquis rate without any distortions. We apply this method in calculating pressure induced shifts of H2O lines and obtain more reliable values. By comparing the calculated shifts with those in HITRAN 2008 and by screening both of them with the pair identity and the smooth variation rules, one can conclude many of shift values in HITRAN are not correct.

Feature extraction using extrema sampling of discrete derivatives for spike sorting in implantable upper-limb neural prostheses.

PubMed

Zamani, Majid; Demosthenous, Andreas

2014-07-01

Next generation neural interfaces for upper-limb (and other) prostheses aim to develop implantable interfaces for one or more nerves, each interface having many neural signal channels that work reliably in the stump without harming the nerves. To achieve real-time multi-channel processing it is important to integrate spike sorting on-chip to overcome limitations in transmission bandwidth. This requires computationally efficient algorithms for feature extraction and clustering suitable for low-power hardware implementation. This paper describes a new feature extraction method for real-time spike sorting based on extrema analysis (namely positive peaks and negative peaks) of spike shapes and their discrete derivatives at different frequency bands. Employing simulation across different datasets, the accuracy and computational complexity of the proposed method are assessed and compared with other methods. The average classification accuracy of the proposed method in conjunction with online sorting (O-Sort) is 91.6%, outperforming all the other methods tested with the O-Sort clustering algorithm. The proposed method offers a better tradeoff between classification error and computational complexity, making it a particularly strong choice for on-chip spike sorting.

Single Protein Structural Analysis with a Solid-state Nanopore Sensor

NASA Astrophysics Data System (ADS)

Li, Jiali; Golovchenko, Jene; McNabb, David

2005-03-01

We report on the use of solid-state nanopore sensors to detect single polypeptides. These solid-state nanopores are fabricated in thin membranes of silicon nitride by ion beam sculpting...[1]. When an electrically biased nanopore is exposed to denatured proteins in ionic solution, discrete transient electronic signals: current blockages are observed. We demonstrate examples of such transient electronic signals for Bovine Serum Albumin (BSA) and human placental laminin M proteins in Guanidine hydrochloride solution, which suggest that these polypeptides are individually translocating through the nanopore during the detecting process. The amplitude of the current blockages is proportional to the bias voltage. No transient current blockages are observed when proteins are not present in the solution. To probe protein-folding state, pH and temperature dependence experiments are performed. The results demonstrate a solid-state nanopore sensor can be used to detect and analyze single polypeptide chains. Similarities and differences with signals obtained from double stranded DNA in a solid-state nanopore and single stranded DNA in a biological nanopore are discussed. [.1] Li, J., D. Stein, C. McMullan, D. Branton, M.J. Aziz, and J.A. Golovchenko, Ion-beam sculpting at nanometre length scales. Nature, 2001. 412(12 July): p. 166-169.

Detecting the Length of Double-stranded DNA with Solid State Nanopores

NASA Astrophysics Data System (ADS)

Li, Jiali; Gershow, Marc; Stein, Derek; Qun, Cai; Brandin, Eric; Wang, Hui; Huang, Albert; Branton, Dan; Golovchenko, Jene

2003-03-01

We report on the use of nanometer scale diameter, solid-state nanopores as single molecule detectors of double stranded DNA molecules. These solid-state nanopores are fabricated in thin membranes of silicon nitride, by ion beam sculpting 1. They produce discrete electronic signals: current blockages, when an electrically biased nanopore is exposed to DNA molecules in aqueous salt solutions. We demonstrate examples of such electronic signals for 3k base pairs (bp) and 10k bp double stranded DNA molecules, which suggest that these molecules are individually translocating through the nanopore during the detection process. The translocating time for the 10k bp double stranded DNA is about 3 times longer than the 3k bp, demonstrating that a solid-state nanopore device can be used to detect the lengths of double stranded DNA molecules. Similarities and differences with signals obtained from single stranded DNA in a biological nanopores are discussed 2. 1. Li, J., Stein, D., McMullan, C., Branton, D. Aziz, M. J. and Golovchenko, J. Ion Beam Sculpting at nanometer length scales. Nature 412, 166-169 (2001). 2. Meller, A., L. Nivon, E. Brandin, Golovchenko, J. & Branton, D. Proc. Natl. Acad. Sci. USA 97, 1079-1084 (2000).

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.

High-resolution space-time characterization of convective rain cells: implications on spatial aggregation and temporal sampling operated by coarser resolution instruments

NASA Astrophysics Data System (ADS)

Marra, Francesco; Morin, Efrat

2017-04-01

Forecasting the occurrence of flash floods and debris flows is fundamental to save lives and protect infrastructures and properties. These natural hazards are generated by high-intensity convective storms, on space-time scales that cannot be properly monitored by conventional instrumentation. Consequently, a number of early-warning systems are nowadays based on remote sensing precipitation observations, e.g. from weather radars or satellites, that proved effective in a wide range of situations. However, the uncertainty affecting rainfall estimates represents an important issue undermining the operational use of early-warning systems. The uncertainty related to remote sensing estimates results from (a) an instrumental component, intrinsic of the measurement operation, and (b) a discretization component, caused by the discretization of the continuous rainfall process. Improved understanding on these sources of uncertainty will provide crucial information to modelers and decision makers. This study aims at advancing knowledge on the (b) discretization component. To do so, we take advantage of an extremely-high resolution X-Band weather radar (60 m, 1 min) recently installed in the Eastern Mediterranean. The instrument monitors a semiarid to arid transition area also covered by an accurate C-Band weather radar and by a relatively sparse rain gauge network ( 1 gauge/ 450 km2). Radar quantitative precipitation estimation includes corrections reducing the errors due to ground echoes, orographic beam blockage and attenuation of the signal in heavy rain. Intense, convection-rich, flooding events recently occurred in the area serve as study cases. We (i) describe with very high detail the spatiotemporal characteristics of the convective cores, and (ii) quantify the uncertainty due to spatial aggregation (spatial discretization) and temporal sampling (temporal discretization) operated by coarser resolution remote sensing instruments. We show that instantaneous rain intensity decreases very steeply with the distance from the core of convection with intensity observed at 1 km (2 km) being 10-40% (1-20%) of the core value. The use of coarser temporal resolutions leads to gaps in the observed rainfall and even relatively high resolutions (5 min) can be affected by the problem. We conclude providing to the final user indications about the effects of the discretization component of estimation uncertainty and suggesting viable ways to decrease them.

General visual robot controller networks via artificial evolution

NASA Astrophysics Data System (ADS)

Cliff, David; Harvey, Inman; Husbands, Philip

1993-08-01

We discuss recent results from our ongoing research concerning the application of artificial evolution techniques (i.e., an extended form of genetic algorithm) to the problem of developing `neural' network controllers for visually guided robots. The robot is a small autonomous vehicle with extremely low-resolution vision, employing visual sensors which could readily be constructed from discrete analog components. In addition to visual sensing, the robot is equipped with a small number of mechanical tactile sensors. Activity from the sensors is fed to a recurrent dynamical artificial `neural' network, which acts as the robot controller, providing signals to motors governing the robot's motion. Prior to presentation of new results, this paper summarizes our rationale and past work, which has demonstrated that visually guided control networks can arise without any explicit specification that visual processing should be employed: the evolutionary process opportunistically makes use of visual information if it is available.

Study regarding the spline interpolation accuracy of the experimentally acquired data

NASA Astrophysics Data System (ADS)

Oanta, Emil M.; Danisor, Alin; Tamas, Razvan

2016-12-01

Experimental data processing is an issue that must be solved in almost all the domains of science. In engineering we usually have a large amount of data and we try to extract the useful signal which is relevant for the phenomenon under investigation. The criteria used to consider some points more relevant then some others may take into consideration various conditions which may be either phenomenon dependent, or general. The paper presents some of the ideas and tests regarding the identification of the best set of criteria used to filter the initial set of points in order to extract a subset which best fits the approximated function. If the function has regions where it is either constant, or it has a slow variation, fewer discretization points may be used. This means to create a simpler solution to process the experimental data, keeping the accuracy in some fair good limits.

Copula-based analysis of rhythm

NASA Astrophysics Data System (ADS)

García, J. E.; González-López, V. A.; Viola, M. L. Lanfredi

2016-06-01

In this paper we establish stochastic profiles of the rhythm for three languages: English, Japanese and Spanish. We model the increase or decrease of the acoustical energy, collected into three bands coming from the acoustic signal. The number of parameters needed to specify a discrete multivariate Markov chain grows exponentially with the order and dimension of the chain. In this case the size of the database is not large enough for a consistent estimation of the model. We apply a strategy to estimate a multivariate process with an order greater than the order achieved using standard procedures. The new strategy consist on obtaining a partition of the state space which is constructed from a combination of the partitions corresponding to the three marginal processes, one for each band of energy, and the partition coming from to the multivariate Markov chain. Then, all the partitions are linked using a copula, in order to estimate the transition probabilities.

Ultraweak photon emission in the brain.

PubMed

Salari, V; Valian, H; Bassereh, H; Bókkon, I; Barkhordari, A

2015-09-01

Besides the low-frequency electromagnetic body-processes measurable through the electroencephalography (EEG), electrocardiography (ECG), etc. there are processes that do not need external excitation, emitting light within or close to the visible spectra. Such ultraweak photon emission (UPE), also named biophoton emission, reflects the cellular (and body) oxidative status. Recently, a growing body of evidence shows that UPE may play an important role in the basic functioning of living cells. Moreover, interesting evidences are beginning to emerge that UPE may well play an important role in neuronal functions. In fact, biophotons are byproducts in cellular metabolism and produce false signals (e.g., retinal discrete dark noise) but on the other side neurons contain many light sensitive molecules that makes it hard to imagine how they might not be influenced by UPE, and thus UPE may carry informational contents. Here, we investigate UPE in the brain from different points of view such as experimental evidences, theoretical modeling, and physiological significance.

Is Accessing of Words Affected by Affective Valence Only? A Discrete Emotion View on the Emotional Congruency Effect

PubMed Central

Chen, Xuqian; Liu, Bo; Lin, Shouwen

2016-01-01

This paper advances the discussion on which emotion information affects word accessing. Emotion information, which is formed as a result of repeated experiences, is primary and necessary in learning and representing word meanings. Previous findings suggested that valence (i.e., positive or negative) denoted by words can be automatically activated and plays a role in many significant cognitive processes. However, there has been a lack of discussion about whether discrete emotion information (i.e., happiness, anger, sadness, and fear) is also involved in these processes. According to the hierarchy model, emotions are considered organized within an abstract-to-concrete hierarchy, in which emotion prototypes are organized following affective valence. By controlling different congruencies of emotion relations (i.e., matches or mismatches between valences and prototypes of emotion), the present study showed both an evaluative congruency effect (Experiment 1) and a discrete emotional congruency effect (Experiment 2). These findings indicate that not only affective valences but also discrete emotions can be activated under the present priming lexical decision task. However, the present findings also suggest that discrete emotions might be activated at the later priming stage as compared to valences. The present work provides evidence that information about discrete emotion could be involved in word processing. This might be a result of subjects’ embodied experiences. PMID:27379000

Is Accessing of Words Affected by Affective Valence Only? A Discrete Emotion View on the Emotional Congruency Effect.

PubMed

Chen, Xuqian; Liu, Bo; Lin, Shouwen

2016-01-01

This paper advances the discussion on which emotion information affects word accessing. Emotion information, which is formed as a result of repeated experiences, is primary and necessary in learning and representing word meanings. Previous findings suggested that valence (i.e., positive or negative) denoted by words can be automatically activated and plays a role in many significant cognitive processes. However, there has been a lack of discussion about whether discrete emotion information (i.e., happiness, anger, sadness, and fear) is also involved in these processes. According to the hierarchy model, emotions are considered organized within an abstract-to-concrete hierarchy, in which emotion prototypes are organized following affective valence. By controlling different congruencies of emotion relations (i.e., matches or mismatches between valences and prototypes of emotion), the present study showed both an evaluative congruency effect (Experiment 1) and a discrete emotional congruency effect (Experiment 2). These findings indicate that not only affective valences but also discrete emotions can be activated under the present priming lexical decision task. However, the present findings also suggest that discrete emotions might be activated at the later priming stage as compared to valences. The present work provides evidence that information about discrete emotion could be involved in word processing. This might be a result of subjects' embodied experiences.

How far could we make ourselves understood by the Andromedans? - an evolutionary cybernetic problem in hierarchical dynamics

NASA Astrophysics Data System (ADS)

Santoli, Salvatore

1994-01-01

The mechanistic interpretation of the communication process between cognitive hierarchical systems as an iterated pair of convolutions between the incoming discrete time series signals and the chaotic dynamics (CD) at the nm-scale of the perception (energy) wetware level, with the consequent feeding of the resulting collective properties to the CD software (symbolic) level, shows that the category of quality, largely present in Galilean quantitative-minded science, is to be increasingly made into quantity for finding optimum common codes for communication between different intelligent beings. The problem is similar to that solved by biological evolution, of communication between the conscious logic brain and the underlying unfelt ultimate extra-logical processes, as well as to the problem of the mind-body or the structure-function dichotomies. Perspective cybernated nanotechnological and/or nanobiological interfaces, and time evolution of the 'contact language' (the iterated dialogic process) as a self-organising system might improve human-alien understanding.

Alcohol-Seeking Triggered by Discrete Pavlovian Cues is Invigorated by Alcohol Contexts and Mediated by Glutamate Signaling in the Basolateral Amygdala

PubMed Central

Sciascia, Joanna M; Reese, Rebecca M; Janak, Patricia H; Chaudhri, Nadia

2015-01-01

The environmental context in which a discrete Pavlovian conditioned stimulus (CS) is experienced can profoundly impact conditioned responding elicited by the CS. We hypothesized that alcohol-seeking behavior elicited by a discrete CS that predicted alcohol would be influenced by context and require glutamate signaling in the basolateral amygdala (BLA). Male, Long-Evans rats were allowed to drink 15% ethanol (v/v) until consumption stabilized. Next, rats received Pavlovian conditioning sessions in which a 10 s CS (15 trials/session) was paired with ethanol (0.2 ml/CS). Entries into a port where ethanol was delivered were measured. Pavlovian conditioning occurred in a specific context (alcohol context) and was alternated with sessions in a different context (non-alcohol context) where neither the CS nor ethanol was presented. At test, the CS was presented without ethanol in the alcohol context or the non-alcohol context, following a bilateral microinfusion (0.3 μl/hemisphere) of saline or the AMPA glutamate receptor antagonist NBQX (2,3-dioxo-6-nitro-1,2,3,4-tetrahydrobenzo[f]quinoxaline-7-sulfonamide disodium salt) in the BLA (0, 0.3, or 1.0 μg/0.3 μl). The effect of NBQX (0, 0.3 μg/0.3 μl) in the caudate putamen (CPu) on CS responding in the non-alcohol context was also tested. The discrete alcohol CS triggered more alcohol-seeking behavior in the alcohol context than the non-alcohol context. NBQX in the BLA reduced CS responding in both contexts but had no effect in the CPu. These data indicate that AMPA glutamate receptors in the BLA are critical for alcohol-seeking elicited by a discrete CS and that behavior triggered by the CS is strongly invigorated by an alcohol context. PMID:25953360

Realization of pure frequency modulation of DFB laser via combined optical and electrical tuning.

PubMed

Tian, Chao; Chen, I-Chun Anderson; Park, Seong-Wook; Martini, Rainer

2013-04-08

In this paper we present a novel approach to convert AM signal into FM signal in semiconductor lasers via off resonance optical pumping and report on experimental results obtained with a commercial DFB laser. Aside of demonstrating discrete and fast frequency modulation, we achieve pure frequency modulation through combination with electrical modulation suppressing the associated amplitude modulation, which is detrimental to application such as spectroscopy and communication.

Robust reconstruction of a signal from its unthresholded recurrence plot subject to disturbances

NASA Astrophysics Data System (ADS)

Sipers, Aloys; Borm, Paul; Peeters, Ralf

2017-02-01

To make valid inferences from recurrence plots for time-delay embedded signals, two underlying key questions are: (1) to what extent does an unthresholded recurrence (URP) plot carry the same information as the signal that generated it, and (2) how does the information change when the URP gets distorted. We studied the first question in our earlier work [1], where it was shown that the URP admits the reconstruction of the underlying signal (up to its mean and a choice of sign) if and only if an associated graph is connected. Here we refine this result and we give an explicit condition in terms of the embedding parameters and the discrete Fourier spectrum of the URP. We also develop a method for the reconstruction of the underlying signal which overcomes several drawbacks that earlier approaches had. To address the second question we investigate robustness of the proposed reconstruction method under disturbances. We carry out two simulation experiments which are characterized by a broad band and a narrow band spectrum respectively. For each experiment we choose a noise level and two different pairs of embedding parameters. The conventional binary recurrence plot (RP) is obtained from the URP by thresholding and zero-one conversion, which can be viewed as severe distortion acting on the URP. Typically the reconstruction of the underlying signal from an RP is expected to be rather inaccurate. However, by introducing the concept of a multi-level recurrence plot (MRP) we propose to bridge the information gap between the URP and the RP, while still achieving a high data compression rate. We demonstrate the working of the proposed reconstruction procedure on MRPs, indicating that MRPs with just a few discretization levels can usually capture signal properties and morphologies more accurately than conventional RPs.

An algebra of discrete event processes

NASA Technical Reports Server (NTRS)

Heymann, Michael; Meyer, George

1991-01-01

This report deals with an algebraic framework for modeling and control of discrete event processes. The report consists of two parts. The first part is introductory, and consists of a tutorial survey of the theory of concurrency in the spirit of Hoare's CSP, and an examination of the suitability of such an algebraic framework for dealing with various aspects of discrete event control. To this end a new concurrency operator is introduced and it is shown how the resulting framework can be applied. It is further shown that a suitable theory that deals with the new concurrency operator must be developed. In the second part of the report the formal algebra of discrete event control is developed. At the present time the second part of the report is still an incomplete and occasionally tentative working paper.

Doppler radar with multiphase modulation of transmitted and reflected signal

NASA Technical Reports Server (NTRS)

Shores, Paul W. (Inventor); Griffin, John W. (Inventor); Kobayashi, Herbert S. (Inventor)

1989-01-01

A microwave radar signal is generated and split by a circulator. A phase shifter introduces a series of phase shifts into a first part of the split signal which is then transmitted by antenna. A like number of phase shifts is introduced by the phase shifter into the return signal from the target. The circulator delivers the phase shifted return signal and the leakage signal from the circulator to a mixer which generates an IF signal output at the Doppler frequency. The IF signal is amplified, filtered, counted per unit of time, and the result displayed to provide indications of target sense and range rate. An oscillator controls rate of phase shift in the transmitted and received radar signals and provides a time base for the counter. The phase shift magnitude increases may be continuous and linear or discrete functions of time.

Covariant information-density cutoff in curved space-time.

PubMed

Kempf, Achim

2004-06-04

In information theory, the link between continuous information and discrete information is established through well-known sampling theorems. Sampling theory explains, for example, how frequency-filtered music signals are reconstructible perfectly from discrete samples. In this Letter, sampling theory is generalized to pseudo-Riemannian manifolds. This provides a new set of mathematical tools for the study of space-time at the Planck scale: theories formulated on a differentiable space-time manifold can be equivalent to lattice theories. There is a close connection to generalized uncertainty relations which have appeared in string theory and other studies of quantum gravity.

Nonlinear single-spin spectrum analyzer.

PubMed

Kotler, Shlomi; Akerman, Nitzan; Glickman, Yinnon; Ozeri, Roee

2013-03-15

Qubits have been used as linear spectrum analyzers of their environments. Here we solve the problem of nonlinear spectral analysis, required for discrete noise induced by a strongly coupled environment. Our nonperturbative analytical model shows a nonlinear signal dependence on noise power, resulting in a spectral resolution beyond the Fourier limit as well as frequency mixing. We develop a noise characterization scheme adapted to this nonlinearity. We then apply it using a single trapped ion as a sensitive probe of strong, non-Gaussian, discrete magnetic field noise. Finally, we experimentally compared the performance of equidistant vs Uhrig modulation schemes for spectral analysis.

Conditions for extinction events in chemical reaction networks with discrete state spaces.

PubMed

Johnston, Matthew D; Anderson, David F; Craciun, Gheorghe; Brijder, Robert

2018-05-01

We study chemical reaction networks with discrete state spaces and present sufficient conditions on the structure of the network that guarantee the system exhibits an extinction event. The conditions we derive involve creating a modified chemical reaction network called a domination-expanded reaction network and then checking properties of this network. Unlike previous results, our analysis allows algorithmic implementation via systems of equalities and inequalities and suggests sequences of reactions which may lead to extinction events. We apply the results to several networks including an EnvZ-OmpR signaling pathway in Escherichia coli.

Neuroendocrine integration of nutritional signals on reproduction.

PubMed

Evans, Maggie C; Anderson, Greg M

2017-02-01

Reproductive function in mammals is energetically costly and therefore tightly regulated by nutritional status. To enable this integration of metabolic and reproductive function, information regarding peripheral nutritional status must be relayed centrally to the gonadotropin-releasing hormone (GNRH) neurons that drive reproductive function. The metabolically relevant hormones leptin, insulin and ghrelin have been identified as key mediators of this 'metabolic control of fertility'. However, the neural circuitry through which they act to exert their control over GNRH drive remains incompletely understood. With the advent of Cre-LoxP technology, it has become possible to perform targeted gene-deletion and gene-rescue experiments and thus test the functional requirement and sufficiency, respectively, of discrete hormone-neuron signaling pathways in the metabolic control of reproductive function. This review discusses the findings from these investigations, and attempts to put them in context with what is known from clinical situations and wild-type animal models. What emerges from this discussion is clear evidence that the integration of nutritional signals on reproduction is complex and highly redundant, and therefore, surprisingly difficult to perturb. Consequently, the deletion of individual hormone-neuron signaling pathways often fails to cause reproductive phenotypes, despite strong evidence that the targeted pathway plays a role under normal physiological conditions. Although transgenic studies rarely reveal a critical role for discrete signaling pathways, they nevertheless prove to be a good strategy for identifying whether a targeted pathway is absolutely required, critically involved, sufficient or dispensable in the metabolic control of fertility. © 2017 Society for Endocrinology.

Discrete Emotion Effects on Lexical Decision Response Times

PubMed Central

Briesemeister, Benny B.; Kuchinke, Lars; Jacobs, Arthur M.

2011-01-01

Our knowledge about affective processes, especially concerning effects on cognitive demands like word processing, is increasing steadily. Several studies consistently document valence and arousal effects, and although there is some debate on possible interactions and different notions of valence, broad agreement on a two dimensional model of affective space has been achieved. Alternative models like the discrete emotion theory have received little interest in word recognition research so far. Using backward elimination and multiple regression analyses, we show that five discrete emotions (i.e., happiness, disgust, fear, anger and sadness) explain as much variance as two published dimensional models assuming continuous or categorical valence, with the variables happiness, disgust and fear significantly contributing to this account. Moreover, these effects even persist in an experiment with discrete emotion conditions when the stimuli are controlled for emotional valence and arousal levels. We interpret this result as evidence for discrete emotion effects in visual word recognition that cannot be explained by the two dimensional affective space account. PMID:21887307

Discrete emotion effects on lexical decision response times.

PubMed

Briesemeister, Benny B; Kuchinke, Lars; Jacobs, Arthur M

2011-01-01

Our knowledge about affective processes, especially concerning effects on cognitive demands like word processing, is increasing steadily. Several studies consistently document valence and arousal effects, and although there is some debate on possible interactions and different notions of valence, broad agreement on a two dimensional model of affective space has been achieved. Alternative models like the discrete emotion theory have received little interest in word recognition research so far. Using backward elimination and multiple regression analyses, we show that five discrete emotions (i.e., happiness, disgust, fear, anger and sadness) explain as much variance as two published dimensional models assuming continuous or categorical valence, with the variables happiness, disgust and fear significantly contributing to this account. Moreover, these effects even persist in an experiment with discrete emotion conditions when the stimuli are controlled for emotional valence and arousal levels. We interpret this result as evidence for discrete emotion effects in visual word recognition that cannot be explained by the two dimensional affective space account.

40 CFR 420.111 - Specialized definitions.

Code of Federal Regulations, 2010 CFR

2010-07-01

... steel products such as coiled wire, rods, and tubes in discrete batches or bundles. (b) The term continuous means those alkaline cleaning operations which process steel products other than in discrete...

Application of the high resolution return beam vidicon

NASA Technical Reports Server (NTRS)

Cantella, M. J.

1977-01-01

The Return Beam Vidicon (RBV) is a high-performance electronic image sensor and electrical storage component. It can accept continuous or discrete exposures. Information can be read out with a single scan or with many repetitive scans for either signal processing or display. Resolution capability is 10,000 TV lines/height, and at 100 lp/mm, performance matches or exceeds that of film, particularly with low-contrast imagery. Electronic zoom can be employed effectively for image magnification and data compression. The high performance and flexibility of the RBV permit wide application in systems for reconnaissance, scan conversion, information storage and retrieval, and automatic inspection and test. This paper summarizes the characteristics and performance parameters of the RBV and cites examples of feasible applications.

Advanced 3-V semiconductor technology assessment

NASA Technical Reports Server (NTRS)

Nowogrodzki, M.

1983-01-01

Components required for extensions of currently planned space communications systems are discussed for large antennas, crosslink systems, single sideband systems, Aerostat systems, and digital signal processing. Systems using advanced modulation concepts and new concepts in communications satellites are included. The current status and trends in materials technology are examined with emphasis on bulk growth of semi-insulating GaAs and InP, epitaxial growth, and ion implantation. Microwave solid state discrete active devices, multigigabit rate GaAs digital integrated circuits, microwave integrated circuits, and the exploratory development of GaInAs devices, heterojunction devices, and quasi-ballistic devices is considered. Competing technologies such as RF power generation, filter structures, and microwave circuit fabrication are discussed. The fundamental limits of semiconductor devices and problems in implementation are explored.

Using Serial and Discrete Digit Naming to Unravel Word Reading Processes

PubMed Central

Altani, Angeliki; Protopapas, Athanassios; Georgiou, George K.

2018-01-01

During reading acquisition, word recognition is assumed to undergo a developmental shift from slow serial/sublexical processing of letter strings to fast parallel processing of whole word forms. This shift has been proposed to be detected by examining the size of the relationship between serial- and discrete-trial versions of word reading and rapid naming tasks. Specifically, a strong association between serial naming of symbols and single word reading suggests that words are processed serially, whereas a strong association between discrete naming of symbols and single word reading suggests that words are processed in parallel as wholes. In this study, 429 Grade 1, 3, and 5 English-speaking Canadian children were tested on serial and discrete digit naming and word reading. Across grades, single word reading was more strongly associated with discrete naming than with serial naming of digits, indicating that short high-frequency words are processed as whole units early in the development of reading ability in English. In contrast, serial naming was not a unique predictor of single word reading across grades, suggesting that within-word sequential processing was not required for the successful recognition for this set of words. Factor mixture analysis revealed that our participants could be clustered into two classes, namely beginning and more advanced readers. Serial naming uniquely predicted single word reading only among the first class of readers, indicating that novice readers rely on a serial strategy to decode words. Yet, a considerable proportion of Grade 1 students were assigned to the second class, evidently being able to process short high-frequency words as unitized symbols. We consider these findings together with those from previous studies to challenge the hypothesis of a binary distinction between serial/sublexical and parallel/lexical processing in word reading. We argue instead that sequential processing in word reading operates on a continuum, depending on the level of reading proficiency, the degree of orthographic transparency, and word-specific characteristics. PMID:29706918

Using Serial and Discrete Digit Naming to Unravel Word Reading Processes.

PubMed

Altani, Angeliki; Protopapas, Athanassios; Georgiou, George K

2018-01-01

During reading acquisition, word recognition is assumed to undergo a developmental shift from slow serial/sublexical processing of letter strings to fast parallel processing of whole word forms. This shift has been proposed to be detected by examining the size of the relationship between serial- and discrete-trial versions of word reading and rapid naming tasks. Specifically, a strong association between serial naming of symbols and single word reading suggests that words are processed serially, whereas a strong association between discrete naming of symbols and single word reading suggests that words are processed in parallel as wholes. In this study, 429 Grade 1, 3, and 5 English-speaking Canadian children were tested on serial and discrete digit naming and word reading. Across grades, single word reading was more strongly associated with discrete naming than with serial naming of digits, indicating that short high-frequency words are processed as whole units early in the development of reading ability in English. In contrast, serial naming was not a unique predictor of single word reading across grades, suggesting that within-word sequential processing was not required for the successful recognition for this set of words. Factor mixture analysis revealed that our participants could be clustered into two classes, namely beginning and more advanced readers. Serial naming uniquely predicted single word reading only among the first class of readers, indicating that novice readers rely on a serial strategy to decode words. Yet, a considerable proportion of Grade 1 students were assigned to the second class, evidently being able to process short high-frequency words as unitized symbols. We consider these findings together with those from previous studies to challenge the hypothesis of a binary distinction between serial/sublexical and parallel/lexical processing in word reading. We argue instead that sequential processing in word reading operates on a continuum, depending on the level of reading proficiency, the degree of orthographic transparency, and word-specific characteristics.

Synchronization Of Parallel Discrete Event Simulations

NASA Technical Reports Server (NTRS)

Steinman, Jeffrey S.

1992-01-01

Adaptive, parallel, discrete-event-simulation-synchronization algorithm, Breathing Time Buckets, developed in Synchronous Parallel Environment for Emulation and Discrete Event Simulation (SPEEDES) operating system. Algorithm allows parallel simulations to process events optimistically in fluctuating time cycles that naturally adapt while simulation in progress. Combines best of optimistic and conservative synchronization strategies while avoiding major disadvantages. Algorithm processes events optimistically in time cycles adapting while simulation in progress. Well suited for modeling communication networks, for large-scale war games, for simulated flights of aircraft, for simulations of computer equipment, for mathematical modeling, for interactive engineering simulations, and for depictions of flows of information.

Signaling and sensory adaptation in Escherichia coli chemoreceptors: 2015 update

PubMed Central

Parkinson, John S.; Hazelbauer, Gerald L.; Falke, Joseph J.

2015-01-01

Motile Escherichia coli cells track gradients of attractant and repellent chemicals in their environment with transmembrane chemoreceptor proteins. These receptors operate in cooperative arrays to produce large changes in the activity of a signaling kinase CheA in response to small changes in chemoeffector concentration. Recent research has provided much deeper understanding of the structure and function of core receptor signaling complexes and the architecture of higher-order receptor arrays, which in turn has led to new insights into the molecular signaling mechanisms of chemoreceptor networks. Current evidence supports a new view of receptor signaling in which stimulus information travels within receptor molecules through shifts in the dynamic properties of adjoining structural elements rather than through a few discrete conformational states. PMID:25834953

Circuit and Method for Communication Over DC Power Line

NASA Technical Reports Server (NTRS)

Krasowski, Michael J.; Prokop, Norman F.

2007-01-01

A circuit and method for transmitting and receiving on-off-keyed (OOK) signals with fractional signal-to-noise ratios uses available high-temperature silicon- on-insulator (SOI) components to move computational, sensing, and actuation abilities closer to high-temperature or high-ionizing radiation environments such as vehicle engine compartments, deep-hole drilling environments, industrial control and monitoring of processes like smelting, and operations near nuclear reactors and in space. This device allows for the networking of multiple, like nodes to each other and to a central processor. It can do this with nothing more than the already in-situ power wiring of the system. The device s microprocessor allows it to make intelligent decisions within the vehicle operational loop and to effect control outputs to its associated actuators. The figure illustrates how each node converts digital serial data to OOK 18-kHz in transmit mode and vice-versa in receive mode; though operations at lower frequencies or up to a megahertz are within reason using this method and these parts. This innovation s technique modulates a DC power bus with millivolt-level signals through a MOSFET (metal oxide semiconductor field effect transistor) and resistor by OOK. It receives and demodulates this signal from the DC power bus through capacitive coupling at high temperature and in high ionizing radiation environments. The demodulation of the OOK signal is accomplished by using an asynchronous quadrature detection technique realized by a quasi-discrete Fourier transform through use of the quadrature components (0 and 90 phases) of the carrier frequency as generated by the microcontroller and as a function of the selected crystal frequency driving its oscillator. The detected signal is rectified using an absolute-value circuit containing no diodes (diodes being non-operational at high temperatures), and only operational amplifiers. The absolute values of the two phases of the received signal are then summed and hard limited (digitized) by comparing them to a reference level and are then input into a microprocessor as a serial bit stream. The quasi-discrete Fourier transform is performed in high-temperature components (operational amplifiers, analog switches, resistors, and capacitors). The demodulated signal is a serial data stream that is input to the UART (universal asynchronous receiver transmitter) receiver pin of the microprocessor. The OOK of the carrier frequency uses the output of the UART pin as an enabling signal that drives the gate of the MOSFET. Logic low bits enable the carrier frequency (realized by using the 0 phase signal from the microcontroller, though either phase may be used) to be DC-coupled to the power supply bus through a current-limiting resistor mounted between the MOSFET drain and the supply rail. The presence of logic lows on the power supply rail is realized by carrier bursts while logic highs are realized by the absence of bursts.

Non-Lipschitz Dynamics Approach to Discrete Event Systems

NASA Technical Reports Server (NTRS)

Zak, M.; Meyers, R.

1995-01-01

This paper presents and discusses a mathematical formalism for simulation of discrete event dynamics (DED) - a special type of 'man- made' system designed to aid specific areas of information processing. A main objective is to demonstrate that the mathematical formalism for DED can be based upon the terminal model of Newtonian dynamics which allows one to relax Lipschitz conditions at some discrete points.

Regularized spherical polar fourier diffusion MRI with optimal dictionary learning.

PubMed

Cheng, Jian; Jiang, Tianzi; Deriche, Rachid; Shen, Dinggang; Yap, Pew-Thian

2013-01-01

Compressed Sensing (CS) takes advantage of signal sparsity or compressibility and allows superb signal reconstruction from relatively few measurements. Based on CS theory, a suitable dictionary for sparse representation of the signal is required. In diffusion MRI (dMRI), CS methods proposed for reconstruction of diffusion-weighted signal and the Ensemble Average Propagator (EAP) utilize two kinds of Dictionary Learning (DL) methods: 1) Discrete Representation DL (DR-DL), and 2) Continuous Representation DL (CR-DL). DR-DL is susceptible to numerical inaccuracy owing to interpolation and regridding errors in a discretized q-space. In this paper, we propose a novel CR-DL approach, called Dictionary Learning - Spherical Polar Fourier Imaging (DL-SPFI) for effective compressed-sensing reconstruction of the q-space diffusion-weighted signal and the EAP. In DL-SPFI, a dictionary that sparsifies the signal is learned from the space of continuous Gaussian diffusion signals. The learned dictionary is then adaptively applied to different voxels using a weighted LASSO framework for robust signal reconstruction. Compared with the start-of-the-art CR-DL and DR-DL methods proposed by Merlet et al. and Bilgic et al., respectively, our work offers the following advantages. First, the learned dictionary is proved to be optimal for Gaussian diffusion signals. Second, to our knowledge, this is the first work to learn a voxel-adaptive dictionary. The importance of the adaptive dictionary in EAP reconstruction will be demonstrated theoretically and empirically. Third, optimization in DL-SPFI is only performed in a small subspace resided by the SPF coefficients, as opposed to the q-space approach utilized by Merlet et al. We experimentally evaluated DL-SPFI with respect to L1-norm regularized SPFI (L1-SPFI), which uses the original SPF basis, and the DR-DL method proposed by Bilgic et al. The experiment results on synthetic and real data indicate that the learned dictionary produces sparser coefficients than the original SPF basis and results in significantly lower reconstruction error than Bilgic et al.'s method.

Activation of dorsolateral prefrontal cortex in a dual neuropsychological screening test: an fMRI approach.

PubMed

Tachibana, Atsumichi; Noah, J Adam; Bronner, Shaw; Ono, Yumie; Hirano, Yoshiyuki; Niwa, Masami; Watanabe, Kazuko; Onozuka, Minoru

2012-05-28

The Kana Pick-out Test (KPT), which uses Kana or Japanese symbols that represent syllables, requires parallel processing of discrete (pick-out) and continuous (reading) dual tasks. As a dual task, the KPT is thought to test working memory and executive function, particularly in the prefrontal cortex (PFC), and is widely used in Japan as a clinical screen for dementia. Nevertheless, there has been little neurological investigation into PFC activity during this test. We used functional magnetic resonance imaging (fMRI) to evaluate changes in the blood oxygenation level-dependent (BOLD) signal in young healthy adults during performance of a computerized KPT dual task (comprised of reading comprehension and picking out vowels) and compared it to its single task components (reading or vowel pick-out alone). Behavioral performance of the KPT degraded compared to its single task components. Performance of the KPT markedly increased BOLD signal intensity in the PFC, and also activated sensorimotor, parietal association, and visual cortex areas. In conjunction analyses, bilateral BOLD signal in the dorsolateral PFC (Brodmann's areas 45, 46) was present only in the KPT. Our results support the central bottleneck theory and suggest that the dorsolateral PFC is an important mediator of neural activity for both short-term storage and executive processes. Quantitative evaluation of the KPT with fMRI in healthy adults is the first step towards understanding the effects of aging or cognitive impairment on KPT performance.

40 CFR 420.91 - Specialized definitions.

Code of Federal Regulations, 2010 CFR

2010-07-01

... wire, rods, and tubes in discrete batches or bundles. (f) The term continuous means those pickling operations which process steel products other than in discrete batches or bundles. (g) The term acid recovery...

Statistical physics inspired energy-efficient coded-modulation for optical communications.

PubMed

Djordjevic, Ivan B; Xu, Lei; Wang, Ting

2012-04-15

Because Shannon's entropy can be obtained by Stirling's approximation of thermodynamics entropy, the statistical physics energy minimization methods are directly applicable to the signal constellation design. We demonstrate that statistical physics inspired energy-efficient (EE) signal constellation designs, in combination with large-girth low-density parity-check (LDPC) codes, significantly outperform conventional LDPC-coded polarization-division multiplexed quadrature amplitude modulation schemes. We also describe an EE signal constellation design algorithm. Finally, we propose the discrete-time implementation of D-dimensional transceiver and corresponding EE polarization-division multiplexed system. © 2012 Optical Society of America

Numerical study of signal propagation in corrugated coaxial cables

DOE PAGES

Li, Jichun; Machorro, Eric A.; Shields, Sidney

2017-01-01

Our article focuses on high-fidelity modeling of signal propagation in corrugated coaxial cables. Taking advantage of the axisymmetry, the authors reduce the 3-D problem to a 2-D problem by solving time-dependent Maxwell's equations in cylindrical coordinates.They then develop a nodal discontinuous Galerkin method for solving their model equations. We prove stability and error analysis for the semi-discrete scheme. We we present our numerical results, we demonstrate that our algorithm not only converges as our theoretical analysis predicts, but it is also very effective in solving a variety of signal propagation problems in practical corrugated coaxial cables.

Digital Filtering of Three-Dimensional Lower Extremity Kinematics: an Assessment

PubMed Central

Sinclair, Jonathan; Taylor, Paul John; Hobbs, Sarah Jane

2013-01-01

Errors in kinematic data are referred to as noise and are an undesirable portion of any waveform. Noise is typically removed using a low-pass filter which removes the high frequency components of the signal. The selection of an optimal frequency cut-off is very important when processing kinematic information and a number of techniques exists for the determination of an optimal frequency cut-off. Despite the importance of cut-off frequency to the efficacy of kinematic analyses there is currently a paucity of research examining the influence of different cut-off frequencies on the resultant 3-D kinematic waveforms and discrete parameters. Twenty participants ran at 4.0 m•s−1 as lower extremity kinematics in the sagittal, coronal and transverse planes were measured using an eight camera motion analysis system. The data were filtered at a range of cut-off frequencies and the discrete kinematic parameters were examined using repeated measures ANOVA’s. The similarity between the raw and filtered waveforms were examined using intra-class correlations. The results show that the cut-off frequency has a significant influence on the discrete kinematic measure across displacement and derivative information in all three planes of rotation. Furthermore, it was also revealed that as the cut-off frequency decreased the attenuation of the kinematic waveforms became more pronounced, particularly in the coronal and transverse planes at the second derivative. In conclusion, this investigation provides new information regarding the influence of digital filtering on lower extremity kinematics and re-emphasizes the importance of selecting the correct cut-off frequency. PMID:24511338

A brief review of models of DC-DC power electronic converters for analysis of their stability

NASA Astrophysics Data System (ADS)

Siewniak, Piotr; Grzesik, Bogusław

2014-10-01

A brief review of models of DC-DC power electronic converters (PECs) is presented in this paper. It contains the most popular, continuous-time and discrete-time models used for PEC simulation, design, stability analysis and other applications. Both large-signal and small-signal models are considered. Special attention is paid to models that are used in practice for the analysis of the global and local stability of PECs.

Automatic identification and removal of ocular artifacts in EEG--improved adaptive predictor filtering for portable applications.

PubMed

Zhao, Qinglin; Hu, Bin; Shi, Yujun; Li, Yang; Moore, Philip; Sun, Minghou; Peng, Hong

2014-06-01

Electroencephalogram (EEG) signals have a long history of use as a noninvasive approach to measure brain function. An essential component in EEG-based applications is the removal of Ocular Artifacts (OA) from the EEG signals. In this paper we propose a hybrid de-noising method combining Discrete Wavelet Transformation (DWT) and an Adaptive Predictor Filter (APF). A particularly novel feature of the proposed method is the use of the APF based on an adaptive autoregressive model for prediction of the waveform of signals in the ocular artifact zones. In our test, based on simulated data, the accuracy of noise removal in the proposed model was significantly increased when compared to existing methods including: Wavelet Packet Transform (WPT) and Independent Component Analysis (ICA), Discrete Wavelet Transform (DWT) and Adaptive Noise Cancellation (ANC). The results demonstrate that the proposed method achieved a lower mean square error and higher correlation between the original and corrected EEG. The proposed method has also been evaluated using data from calibration trials for the Online Predictive Tools for Intervention in Mental Illness (OPTIMI) project. The results of this evaluation indicate an improvement in performance in terms of the recovery of true EEG signals with EEG tracking and computational speed in the analysis. The proposed method is well suited to applications in portable environments where the constraints with respect to acceptable wearable sensor attachments usually dictate single channel devices.

Characterization of Geiger mode avalanche photodiodes for fluorescence decay measurements

NASA Astrophysics Data System (ADS)

Jackson, John C.; Phelan, Don; Morrison, Alan P.; Redfern, R. Michael; Mathewson, Alan

2002-05-01

Geiger mode avalanche photodiodes (APD) can be biased above the breakdown voltage to allow detection of single photons. Because of the increase in quantum efficiency, magnetic field immunity, robustness, longer operating lifetime and reduction in costs, solid-state detectors capable of operating at non-cryogenic temperatures and providing single photon detection capabilities provide attractive alternatives to the photomultiplier tube (PMT). Shallow junction Geiger mode APD detectors provide the ability to manufacture photon detectors and detector arrays with CMOS compatible processing steps and allows the use of novel Silicon-on-Insulator(SoI) technology to provide future integrated sensing solutions. Previous work on Geiger mode APD detectors has focused on increasing the active area of the detector to make it more PMT like, easing the integration of discrete reaction, detection and signal processing into laboratory experimental systems. This discrete model for single photon detection works well for laboratory sized test and measurement equipment, however the move towards microfluidics and systems on a chip requires integrated sensing solutions. As we move towards providing integrated functionality of increasingly nanoscopic sized emissions, small area detectors and detector arrays that can be easily integrated into marketable systems, with sensitive small area single photon counting detectors will be needed. This paper will demonstrate the 2-dimensional and 3-dimensional simulation of optical coupling that occurs in Geiger mode APDs. Fabricated Geiger mode APD detectors optimized for fluorescence decay measurements were characterized and preliminary results show excellent results for their integration into fluorescence decay measurement systems.

Electrical Connector Mechanical Seating Sensor

NASA Technical Reports Server (NTRS)

Arens, Ellen; Captain, Janine; Youngquist, Robert

2011-01-01

A sensor provides a measurement of the degree of seating of an electrical connector. This sensor provides a number of discrete distances that a plug is inserted into a socket or receptacle. The number of measurements is equal to the number of pins available in the connector for sensing. On at least two occasions, the Shuttle Program has suffered serious time delays and incurred excessive costs simply because a plug was not seated well within a receptacle. Two methods were designed to address this problem: (1) the resistive pin technique and (2) the discrete length pins technique. In the resistive pin approach, a standard pin in a male connector is replaced with a pin that has a uniform resistivity along its length. This provides a variable resistance on that pin that is dependent on how far the pin is inserted into a socket. This is essentially a linear potentiometer. The discrete approach uses a pin (or a few pins) in the connector as a displacement indicator by truncating the pin length so it sits shorter in the connector than the other pins. A loss of signal on this pin would indicate a discrete amount of displacement of the connector. This approach would only give discrete values of connector displacement, and at least one pin would be needed for each displacement value that would be of interest.

Potential accuracy of methods of laser Doppler anemometry in the single-particle scattering mode

NASA Astrophysics Data System (ADS)

Sobolev, V. S.; Kashcheeva, G. A.

2017-05-01

Potential accuracy of methods of laser Doppler anemometry is determined for the singleparticle scattering mode where the only disturbing factor is shot noise generated by the optical signal itself. The problem is solved by means of computer simulations with the maximum likelihood method. The initial parameters of simulations are chosen to be the number of real or virtual interference fringes in the measurement volume of the anemometer, the signal discretization frequency, and some typical values of the signal/shot noise ratio. The parameters to be estimated are the Doppler frequency as the basic parameter carrying information about the process velocity, the signal amplitude containing information about the size and concentration of scattering particles, and the instant when the particles arrive at the center of the measurement volume of the anemometer, which is needed for reconstruction of the examined flow velocity as a function of time. The estimates obtained in this study show that shot noise produces a minor effect (0.004-0.04%) on the frequency determination accuracy in the entire range of chosen values of the initial parameters. For the signal amplitude and the instant when the particles arrive at the center of the measurement volume of the anemometer, the errors induced by shot noise are in the interval of 0.2-3.5%; if the number of interference fringes is sufficiently large (more than 20), the errors do not exceed 0.2% regardless of the shot noise level.

Overview of MAVEN Particle and Fields Package (PFP) Measurements During Observations of Discrete Aurora at Mars by the MAVEN Imaging Ultraviolet Spectrograph (IUVS)

NASA Astrophysics Data System (ADS)

Soobiah, Y. I. J.; Espley, J. R.; Connerney, J. E. P.; Gruesbeck, J.; DiBraccio, G. A.; Schneider, N.; Jain, S.; Brain, D.; Andersson, L.; Halekas, J. S.; Lillis, R. J.; McFadden, J. P.; Mitchell, D. L.; Mazelle, C. X.; Deighan, J.; McClintock, W. E.; Ergun, R.; Jakosky, B. M.

2016-12-01

NASA's Mars Atmosphere and Volatile EvolutioN (MAVEN) spacecraft has observed a variety of aurora at Mars and related processes that impact the escape of the Martian atmosphere. So far MAVEN's Imaging Ultraviolet Spectrograph (IUVS) instrument has observed 1) Diffuse aurora over widespread regions of Mars' northern hemisphere; 2) Discrete aurora that is spatially confined to localized patches around regions of crustal magnetic field; and 3) Proton aurora from the limb brightening of Lyman-α emission. MAVEN's Solar Energetic Particle (SEP) instrument has shown the diffuse aurora to be coincident with outbursts of solar energetic particles and disturbed solar wind and magnetospheric conditions. MAVEN Particle and Fields Package (PFP) Solar Wind Ion Analyzer (SWIA) has shown the limb brightening of Lyman-α to correlate with increased upstream solar wind dynamic pressure as associated with increased penetrating protons. So far a conclusive explanation for the discrete aurora has yet to be determined. This study aims to explore the plasma processes related to discrete Martian aurora in greater detail by presenting an overview of PFP measurements during orbits when IUVS observed discrete aurora at Mars. Initial observations from orbit 1600 of MAVEN has shown the almost side-by-side occurrence of a crustal magnetic field associated current sheet measured by MAVEN's Magnetometer Investigation (MAG) near the Mars terminator and IUVS limb observations of discrete aurora in Mars shadow (similar co-latitudes but separated by nearly 1800 km across longitude). This study includes further analysis of magnetic field current sheets and the particle acceleration/energization to investigate the space plasma processes involved in discrete aurora at Mars.

Beta oscillations define discrete perceptual cycles in the somatosensory domain.

PubMed

Baumgarten, Thomas J; Schnitzler, Alfons; Lange, Joachim

2015-09-29

Whether seeing a movie, listening to a song, or feeling a breeze on the skin, we coherently experience these stimuli as continuous, seamless percepts. However, there are rare perceptual phenomena that argue against continuous perception but, instead, suggest discrete processing of sensory input. Empirical evidence supporting such a discrete mechanism, however, remains scarce and comes entirely from the visual domain. Here, we demonstrate compelling evidence for discrete perceptual sampling in the somatosensory domain. Using magnetoencephalography (MEG) and a tactile temporal discrimination task in humans, we find that oscillatory alpha- and low beta-band (8-20 Hz) cycles in primary somatosensory cortex represent neurophysiological correlates of discrete perceptual cycles. Our results agree with several theoretical concepts of discrete perceptual sampling and empirical evidence of perceptual cycles in the visual domain. Critically, these results show that discrete perceptual cycles are not domain-specific, and thus restricted to the visual domain, but extend to the somatosensory domain.

Discretization of 3d gravity in different polarizations

NASA Astrophysics Data System (ADS)

Dupuis, Maïté; Freidel, Laurent; Girelli, Florian

2017-10-01

We study the discretization of three-dimensional gravity with Λ =0 following the loop quantum gravity framework. In the process, we realize that different choices of polarization are possible. This allows us to introduce a new discretization based on the triad as opposed to the connection as in the standard loop quantum gravity framework. We also identify the classical nontrivial symmetries of discrete gravity, namely the Drinfeld double, given in terms of momentum maps. Another choice of polarization is given by the Chern-Simons formulation of gravity. Our framework also provides a new discretization scheme of Chern-Simons, which keeps track of the link between the continuum variables and the discrete ones. We show how the Poisson bracket we recover between the Chern-Simons holonomies allows us to recover the Goldman bracket. There is also a transparent link between the discrete Chern-Simons formulation and the discretization of gravity based on the connection (loop gravity) or triad variables (dual loop gravity).

A discrete-time chaos synchronization system for electronic locking devices

NASA Astrophysics Data System (ADS)

Minero-Ramales, G.; López-Mancilla, D.; Castañeda, Carlos E.; Huerta Cuellar, G.; Chiu Z., R.; Hugo García López, J.; Jaimes Reátegui, R.; Villafaña Rauda, E.; Posadas-Castillo, C.

2016-11-01

This paper presents a novel electronic locking key based on discrete-time chaos synchronization. Two Chen chaos generators are synchronized using the Model-Matching Approach, from non-linear control theory, in order to perform the encryption/decryption of the signal to be transmitted. A model/transmitter system is designed, generating a key of chaotic pulses in discrete-time. A plant/receiver system uses the above mentioned key to unlock the mechanism. Two alternative schemes to transmit the private chaotic key are proposed. The first one utilizes two transmission channels. One channel is used to encrypt the chaotic key and the other is used to achieve output synchronization. The second alternative uses only one transmission channel for obtaining synchronization and encryption of the chaotic key. In both cases, the private chaotic key is encrypted again with chaos to solve secure communication-related problems. The results obtained via simulations contribute to enhance the electronic locking devices.

Adaptive NN control for discrete-time pure-feedback systems with unknown control direction under amplitude and rate actuator constraints.

PubMed

Chen, Weisheng

2009-07-01

This paper focuses on the problem of adaptive neural network tracking control for a class of discrete-time pure-feedback systems with unknown control direction under amplitude and rate actuator constraints. Two novel state-feedback and output-feedback dynamic control laws are established where the function tanh(.) is employed to solve the saturation constraint problem. Implicit function theorem and mean value theorem are exploited to deal with non-affine variables that are used as actual control. Radial basis function neural networks are used to approximate the desired input function. Discrete Nussbaum gain is used to estimate the unknown sign of control gain. The uniform boundedness of all closed-loop signals is guaranteed. The tracking error is proved to converge to a small residual set around the origin. A simulation example is provided to illustrate the effectiveness of control schemes proposed in this paper.

Design of an optimal preview controller for linear discrete-time descriptor systems with state delay

NASA Astrophysics Data System (ADS)

Cao, Mengjuan; Liao, Fucheng

2015-04-01

In this paper, the linear discrete-time descriptor system with state delay is studied, and a design method for an optimal preview controller is proposed. First, by using the discrete lifting technique, the original system is transformed into a general descriptor system without state delay in form. Then, taking advantage of the first-order forward difference operator, we construct a descriptor augmented error system, including the state vectors of the lifted system, error vectors, and desired target signals. Rigorous mathematical proofs are given for the regularity, stabilisability, causal controllability, and causal observability of the descriptor augmented error system. Based on these, the optimal preview controller with preview feedforward compensation for the original system is obtained by using the standard optimal regulator theory of the descriptor system. The effectiveness of the proposed method is shown by numerical simulation.

Investigations of 2.9-GHz Resonant Microwave-Sensitive Ag/MgO/Ge/Ag Tunneling Diodes

NASA Astrophysics Data System (ADS)

Qasrawi, A. F.; Khanfar, H. K.

2013-12-01

In this work, a resonant microwave-sensitive tunneling diode has been designed and investigated. The device, which is composed of a magnesium oxide (MgO) layer on an amorphous germanium (Ge) thin film, was characterized by means of temperature-dependent current ( I)-voltage ( V), room-temperature differential resistance ( R)-voltage, and capacitance ( C)-voltage characteristics. The device resonating signal was also tested and evaluated at 2.9 GHz. The I- V curves reflected weak temperature dependence and a wide tunneling region with peak-to-valley current ratio of ˜1.1. The negative differential resistance region shifts toward lower biasing voltages as temperature increases. The true operational limit of the device was determined as 350 K. A novel response of the measured R- V and C- V to the incident alternating-current (ac) signal was observed at 300 K. Particularly, the response to a 100-MHz signal power ranging from the standard Bluetooth limit to the maximum output power of third-generation mobile phones reflects a wide range of tunability with discrete switching property at particular power limits. In addition, when the tunnel device was implanted as an amplifier for a 2.90-GHz resonating signal of the power of wireless local-area network (LAN) levels, signal gain of 80% with signal quality factor of 4.6 × 104 was registered. These remarkable properties make devices based on MgO-Ge interfaces suitable as electronic circuit elements for microwave applications, bias- and time-dependent electronic switches, and central processing unit (CPU) clocks.

Stochastic thermodynamics across scales: Emergent inter-attractoral discrete Markov jump process and its underlying continuous diffusion

NASA Astrophysics Data System (ADS)

Santillán, Moisés; Qian, Hong

2013-01-01

We investigate the internal consistency of a recently developed mathematical thermodynamic structure across scales, between a continuous stochastic nonlinear dynamical system, i.e., a diffusion process with Langevin and Fokker-Planck equations, and its emergent discrete, inter-attractoral Markov jump process. We analyze how the system’s thermodynamic state functions, e.g. free energy F, entropy S, entropy production ep, free energy dissipation Ḟ, etc., are related when the continuous system is described with coarse-grained discrete variables. It is shown that the thermodynamics derived from the underlying, detailed continuous dynamics gives rise to exactly the free-energy representation of Gibbs and Helmholtz. That is, the system’s thermodynamic structure is the same as if one only takes a middle road and starts with the natural discrete description, with the corresponding transition rates empirically determined. By natural we mean in the thermodynamic limit of a large system, with an inherent separation of time scales between inter- and intra-attractoral dynamics. This result generalizes a fundamental idea from chemistry, and the theory of Kramers, by incorporating thermodynamics: while a mechanical description of a molecule is in terms of continuous bond lengths and angles, chemical reactions are phenomenologically described by a discrete representation, in terms of exponential rate laws and a stochastic thermodynamics.

Detection of structural damage in multiwire cables by monitoring the entropy evolution of wavelet coefficients

NASA Astrophysics Data System (ADS)

Ibáñez, Flor; Baltazar, Arturo; Mijarez, Rito; Aranda, Jorge

2015-03-01

Multiwire cables are widely used in important civil structures. Since they are exposed to several dynamic and static loads, their structural health can be compromised. The cables can also be submitted to mechanical contact, tension and energy propagation in addition to changes in size and material within their wires. Due to the critical role played by multiwire cables, it is necessary to develop a non-destructive health monitoring method to maintain their structure and proper performance. Ultrasonic inspection using guided waves is a promising non-destructive damage monitoring technique for rods, single wires and multiwire cables. The propagated guided waves are composed by an infinite number of vibrational modes making their analysis difficult. In this work, an entropy-based method to identify small changes in non-stationary signals is proposed. A system to capture and post-process acoustic signals is implemented. The Discrete Wavelet Transform (DWT) is computed in order to obtain the reconstructed wavelet coefficients of the signals and to analyze the energy at different scales. The feasibility of using the concept of entropy evolution of non-stationary signals to detect damage in multiwire cables is evaluated. The results show that there is a high correlation between the entropy value and damage level of the cable. The proposed method has low sensitivity to noise and reduces the computational complexity found in a typical time-frequency analysis.