Information Acquisition, Analysis and Integration

DTIC Science & Technology

2016-08-03

of sensing and processing, theory, applications, signal processing, image and video processing, machine learning , technology transfer. 16. SECURITY... learning . 5. Solved elegantly old problems like image and video debluring, intro- ducing new revolutionary approaches. 1 DISTRIBUTION A: Distribution...Polatkan, G. Sapiro, D. Blei, D. B. Dunson, and L. Carin, “ Deep learning with hierarchical convolution factor analysis,” IEEE 6 DISTRIBUTION A

Drosophila glypicans Dally and Dally-like are essential regulators for JAK/STAT signaling and Unpaired distribution in eye development

PubMed Central

Zhang, Yan; You, Jia; Ren, Wenyan; Lin, Xinhua

2013-01-01

The highly conserved janus kinase (JAK)-signal transducer and activator of transcription (STAT) pathway is a well-known signaling system that is involved in many biological processes. In Drosophila, this signaling cascade is activated by ligands of the Unpaired (Upd) family. Therefore, the regulation of Upd distribution is one of the key issues in controlling the JAK/STAT signaling activity and function. Heparan sulfate proteoglycans (HSPGs) are macromolecules that regulate the distribution of many ligand proteins including Wingless, Hedgehog and Decapentaplegic (Dpp). Here we show that during Drosophila eye development, HSPGs are also required in normal Upd distribution and JAK/STAT signaling activity. Loss of HSPG biosynthesis enzyme Brother of tout-velu (Botv), Sulfateless (Sfl), or glypicans Division abnormally delayed (Dally) and Dally-like protein (Dlp) led to reduced levels of extracellular Upd and reduction in JAK/STAT signaling activity. Overexpression of dally resulted in the accumulation of Upd and up-regulation of the signaling activity. Luciferase assay also showed that Dally promotes JAK/STAT signaling activity, and is dependent on its heparin sulfate chains. These data suggest that Dally and Dlp are essential for Upd distribution and JAK/STAT signaling activity. PMID:23313126

Gene regulatory and signaling networks exhibit distinct topological distributions of motifs

NASA Astrophysics Data System (ADS)

Ferreira, Gustavo Rodrigues; Nakaya, Helder Imoto; Costa, Luciano da Fontoura

2018-04-01

The biological processes of cellular decision making and differentiation involve a plethora of signaling pathways and gene regulatory circuits. These networks in turn exhibit a multitude of motifs playing crucial parts in regulating network activity. Here we compare the topological placement of motifs in gene regulatory and signaling networks and observe that it suggests different evolutionary strategies in motif distribution for distinct cellular subnetworks.

Recurrent neural network approach to quantum signal: coherent state restoration for continuous-variable quantum key distribution

NASA Astrophysics Data System (ADS)

Lu, Weizhao; Huang, Chunhui; Hou, Kun; Shi, Liting; Zhao, Huihui; Li, Zhengmei; Qiu, Jianfeng

2018-05-01

In continuous-variable quantum key distribution (CV-QKD), weak signal carrying information transmits from Alice to Bob; during this process it is easily influenced by unknown noise which reduces signal-to-noise ratio, and strongly impacts reliability and stability of the communication. Recurrent quantum neural network (RQNN) is an artificial neural network model which can perform stochastic filtering without any prior knowledge of the signal and noise. In this paper, a modified RQNN algorithm with expectation maximization algorithm is proposed to process the signal in CV-QKD, which follows the basic rule of quantum mechanics. After RQNN, noise power decreases about 15 dBm, coherent signal recognition rate of RQNN is 96%, quantum bit error rate (QBER) drops to 4%, which is 6.9% lower than original QBER, and channel capacity is notably enlarged.

Distributed digital signal processors for multi-body structures

NASA Technical Reports Server (NTRS)

Lee, Gordon K.

1990-01-01

Several digital filter designs were investigated which may be used to process sensor data from large space structures and to design digital hardware to implement the distributed signal processing architecture. Several experimental tests articles are available at NASA Langley Research Center to evaluate these designs. A summary of some of the digital filter designs is presented, an evaluation of their characteristics relative to control design is discussed, and candidate hardware microcontroller/microcomputer components are given. Future activities include software evaluation of the digital filter designs and actual hardware inplementation of some of the signal processor algorithms on an experimental testbed at NASA Langley.

Code Optimization for the Choi-Williams Distribution for ELINT Applications

DTIC Science & Technology

2009-12-01

Probability of Intercept N Number of Samples NPS Naval Postgraduate School SNR Signal To Noise Ratio WVD Wigner - Ville Distribution xvi THIS PAGE...Many of the optimizations developed can be applied to the computation of the Wigner - Ville distribution as well. This work is highly applicable in the...made can also be used to increase the speed at which the Wigner - Ville distribution (another signal processing algorithm) can be computed. These

Signal processing in urodynamics: towards high definition urethral pressure profilometry.

PubMed

Klünder, Mario; Sawodny, Oliver; Amend, Bastian; Ederer, Michael; Kelp, Alexandra; Sievert, Karl-Dietrich; Stenzl, Arnulf; Feuer, Ronny

2016-03-22

Urethral pressure profilometry (UPP) is used in the diagnosis of stress urinary incontinence (SUI) which is a significant medical, social, and economic problem. Low spatial pressure resolution, common occurrence of artifacts, and uncertainties in data location limit the diagnostic value of UPP. To overcome these limitations, high definition urethral pressure profilometry (HD-UPP) combining enhanced UPP hardware and signal processing algorithms has been developed. In this work, we present the different signal processing steps in HD-UPP and show experimental results from female minipigs. We use a special microtip catheter with high angular pressure resolution and an integrated inclination sensor. Signals from the catheter are filtered and time-correlated artifacts removed. A signal reconstruction algorithm processes pressure data into a detailed pressure image on the urethra's inside. Finally, the pressure distribution on the urethra's outside is calculated through deconvolution. A mathematical model of the urethra is contained in a point-spread-function (PSF) which is identified depending on geometric and material properties of the urethra. We additionally investigate the PSF's frequency response to determine the relevant frequency band for pressure information on the urinary sphincter. Experimental pressure data are spatially located and processed into high resolution pressure images. Artifacts are successfully removed from data without blurring other details. The pressure distribution on the urethra's outside is reconstructed and compared to the one on the inside. Finally, the pressure images are mapped onto the urethral geometry calculated from inclination and position data to provide an integrated image of pressure distribution, anatomical shape, and location. With its advanced sensing capabilities, the novel microtip catheter collects an unprecedented amount of urethral pressure data. Through sequential signal processing steps, physicians are provided with detailed information on the pressure distribution in and around the urethra. Therefore, HD-UPP overcomes many current limitations of conventional UPP and offers the opportunity to evaluate urethral structures, especially the sphincter, in context of the correct anatomical location. This could enable the development of focal therapy approaches in the treatment of SUI.

Revealing the spatial region of a future fracture nucleation in heterogeneous materials at the initial deformation stage

NASA Astrophysics Data System (ADS)

Damaskinskaya, Ekaterina; Hilarov, Vladimir; Frolov, Dmitriy

2016-11-01

The energy distributions of acoustic emission (AE) signals have been analyzed on two scaling levels corresponding to deformation of granite samples and processes on a commercial mining enterprise. It is established that, in cases of localized fracture, the energy distribution of AE signals has shape described by a power law, while a dispersed fracture is characterized by an exponential energy distribution of the AE signals. Analysis of the functional form of the energy distribution performed at the initial stage of loading allows one to recognize a spatial region in the sample where localization of the defect formation will subsequently take place.

Defense Applications of Signal Processing

DTIC Science & Technology

1999-08-27

class of multiscale autoregressive moving average (MARMA) processes. These are generalisations of ARMA models in time series analysis , and they contain...including the two theoretical sinusoidal components. Analysis of the amplitude and frequency time series provided some novel insight into the real...communication channels, underwater acoustic signals, radar systems , economic time series and biomedical signals [7]. The alpha stable (aS) distribution has

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

DTIC Science & Technology

2016-06-14

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

Demonstration of fundamental statistics by studying timing of electronics signals in a physics-based laboratory

NASA Astrophysics Data System (ADS)

Beach, Shaun E.; Semkow, Thomas M.; Remling, David J.; Bradt, Clayton J.

2017-07-01

We have developed accessible methods to demonstrate fundamental statistics in several phenomena, in the context of teaching electronic signal processing in a physics-based college-level curriculum. A relationship between the exponential time-interval distribution and Poisson counting distribution for a Markov process with constant rate is derived in a novel way and demonstrated using nuclear counting. Negative binomial statistics is demonstrated as a model for overdispersion and justified by the effect of electronic noise in nuclear counting. The statistics of digital packets on a computer network are shown to be compatible with the fractal-point stochastic process leading to a power-law as well as generalized inverse Gaussian density distributions of time intervals between packets.

Experiments with Sensor Motes and Java-DSP

ERIC Educational Resources Information Center

Kwon, Homin; Berisha, V.; Atti, V.; Spanias, A.

2009-01-01

Distributed wireless sensor networks (WSNs) are being proposed for various applications including defense, security, and smart stages. The introduction of hardware wireless sensors in a signal processing education setting can serve as a paradigm for data acquisition, collaborative signal processing, or simply as a platform for obtaining,…

Review of Vibration-Based Helicopters Health and Usage Monitoring Methods

DTIC Science & Technology

2001-04-05

FM4, NA4, NA4*, NB4 and NB48* (Polyshchuk et al., 1998). The Wigner - Ville distribution ( WVD ) is a joint time-frequency signal analysis. The WVD is one...signal processing methodologies that are of relevance to vibration based damage detection (e.g., Wavelet Transform and Wigner - Ville distribution ) will be...operation cost, reduce maintenance flights, and increase flight safety. Key Words: HUMS; Wavelet Transform; Wigner - Ville distribution ; O&S; Machinery

Ultra-stable long distance optical frequency distribution using the Internet fiber network.

PubMed

Lopez, Olivier; Haboucha, Adil; Chanteau, Bruno; Chardonnet, Christian; Amy-Klein, Anne; Santarelli, Giorgio

2012-10-08

We report an optical link of 540 km for ultrastable frequency distribution over the Internet fiber network. The stable frequency optical signal is processed enabling uninterrupted propagation on both directions. The robustness and the performance of the link are enhanced by a cost effective fully automated optoelectronic station. This device is able to coherently regenerate the return optical signal with a heterodyne optical phase locking of a low noise laser diode. Moreover the incoming signal polarization variation are tracked and processed in order to maintain beat note amplitudes within the operation range. Stable fibered optical interferometer enables optical detection of the link round trip phase signal. The phase-noise compensated link shows a fractional frequency instability in 10 Hz bandwidth of 5 × 10(-15) at one second measurement time and 2 × 10(-19) at 30,000 s. This work is a significant step towards a sustainable wide area ultrastable optical frequency distribution and comparison network.

Distributed Peer-to-Peer Target Tracking in Wireless Sensor Networks

PubMed Central

Wang, Xue; Wang, Sheng; Bi, Dao-Wei; Ma, Jun-Jie

2007-01-01

Target tracking is usually a challenging application for wireless sensor networks (WSNs) because it is always computation-intensive and requires real-time processing. This paper proposes a practical target tracking system based on the auto regressive moving average (ARMA) model in a distributed peer-to-peer (P2P) signal processing framework. In the proposed framework, wireless sensor nodes act as peers that perform target detection, feature extraction, classification and tracking, whereas target localization requires the collaboration between wireless sensor nodes for improving the accuracy and robustness. For carrying out target tracking under the constraints imposed by the limited capabilities of the wireless sensor nodes, some practically feasible algorithms, such as the ARMA model and the 2-D integer lifting wavelet transform, are adopted in single wireless sensor nodes due to their outstanding performance and light computational burden. Furthermore, a progressive multi-view localization algorithm is proposed in distributed P2P signal processing framework considering the tradeoff between the accuracy and energy consumption. Finally, a real world target tracking experiment is illustrated. Results from experimental implementations have demonstrated that the proposed target tracking system based on a distributed P2P signal processing framework can make efficient use of scarce energy and communication resources and achieve target tracking successfully.

Radar signal analysis of ballistic missile with micro-motion based on time-frequency distribution

NASA Astrophysics Data System (ADS)

Wang, Jianming; Liu, Lihua; Yu, Hua

2015-12-01

The micro-motion of ballistic missile targets induces micro-Doppler modulation on the radar return signal, which is a unique feature for the warhead discrimination during flight. In order to extract the micro-Doppler feature of ballistic missile targets, time-frequency analysis is employed to process the micro-Doppler modulated time-varying radar signal. The images of time-frequency distribution (TFD) reveal the micro-Doppler modulation characteristic very well. However, there are many existing time-frequency analysis methods to generate the time-frequency distribution images, including the short-time Fourier transform (STFT), Wigner distribution (WD) and Cohen class distribution, etc. Under the background of ballistic missile defence, the paper aims at working out an effective time-frequency analysis method for ballistic missile warhead discrimination from the decoys.

Research and design of intelligent distributed traffic signal light control system based on CAN bus

NASA Astrophysics Data System (ADS)

Chen, Yu

2007-12-01

Intelligent distributed traffic signal light control system was designed based on technologies of infrared, CAN bus, single chip microprocessor (SCM), etc. The traffic flow signal is processed with the core of SCM AT89C51. At the same time, the SCM controls the CAN bus controller SJA1000/transceiver PCA82C250 to build a CAN bus communication system to transmit data. Moreover, up PC realizes to connect and communicate with SCM through USBCAN chip PDIUSBD12. The distributed traffic signal light control system with three control styles of Vehicle flux, remote and PC is designed. This paper introduces the system composition method and parts of hardware/software design in detail.

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

The Development of Design Guides for the Implementation of Multiprocessing Element Systems.

DTIC Science & Technology

1985-09-01

Conclusions............................ 30 -~-.4 IMPLEMENTATION OF CHILL SIGNALS . COMMUNICATION PRIMITIVES ON A DISTRIBUTED SYSTEM ........................ 31...Architecture of a Distributed System .......... ........................... 32 4.2 Algorithm for the SEND Signal Operation ...... 35 4.3 Algorithm for the...elements operating concurrently. Such Multi Processing-element Systems are clearly going to be complex and it is important that the designers of such

Frequency-Wavenumber (F-K) Processing for Infrasound Distributed Arrays

DTIC Science & Technology

2012-10-01

UNCLASSIFIED Approved for public release; distribution is unlimited (U) Frequency-Wavenumber (F-K) Processing for Infrasound Distributed...have conventionally been used to detect infrasound . Pipe arrays, used in conjunction with microbarometers, provide noise reduction by averaging wind...signals. This is especially true for infrasound and low-frequency acoustic sources of tactical interest in the 1 to 100 Hz range. The work described

Adaptive Temporal Matched Filtering for Noise Suppression in Fiber Optic Distributed Acoustic Sensing.

PubMed

Ölçer, İbrahim; Öncü, Ahmet

2017-06-05

Distributed vibration sensing based on phase-sensitive optical time domain reflectometry ( ϕ -OTDR) is being widely used in several applications. However, one of the main challenges in coherent detection-based ϕ -OTDR systems is the fading noise, which impacts the detection performance. In addition, typical signal averaging and differentiating techniques are not suitable for detecting high frequency events. This paper presents a new approach for reducing the effect of fading noise in fiber optic distributed acoustic vibration sensing systems without any impact on the frequency response of the detection system. The method is based on temporal adaptive processing of ϕ -OTDR signals. The fundamental theory underlying the algorithm, which is based on signal-to-noise ratio (SNR) maximization, is presented, and the efficacy of our algorithm is demonstrated with laboratory experiments and field tests. With the proposed digital processing technique, the results show that more than 10 dB of SNR values can be achieved without any reduction in the system bandwidth and without using additional optical amplifier stages in the hardware. We believe that our proposed adaptive processing approach can be effectively used to develop fiber optic-based distributed acoustic vibration sensing systems.

Adaptive Temporal Matched Filtering for Noise Suppression in Fiber Optic Distributed Acoustic Sensing

PubMed Central

Ölçer, İbrahim; Öncü, Ahmet

2017-01-01

Distributed vibration sensing based on phase-sensitive optical time domain reflectometry (ϕ-OTDR) is being widely used in several applications. However, one of the main challenges in coherent detection-based ϕ-OTDR systems is the fading noise, which impacts the detection performance. In addition, typical signal averaging and differentiating techniques are not suitable for detecting high frequency events. This paper presents a new approach for reducing the effect of fading noise in fiber optic distributed acoustic vibration sensing systems without any impact on the frequency response of the detection system. The method is based on temporal adaptive processing of ϕ-OTDR signals. The fundamental theory underlying the algorithm, which is based on signal-to-noise ratio (SNR) maximization, is presented, and the efficacy of our algorithm is demonstrated with laboratory experiments and field tests. With the proposed digital processing technique, the results show that more than 10 dB of SNR values can be achieved without any reduction in the system bandwidth and without using additional optical amplifier stages in the hardware. We believe that our proposed adaptive processing approach can be effectively used to develop fiber optic-based distributed acoustic vibration sensing systems. PMID:28587240

ELINT Signal Processing Using Choi-Williams Distribution on Reconfigurable Computers for Detection and Classification of LPI Emitters

DTIC Science & Technology

2008-03-01

WVD Wigner - Ville Distribution xiv THIS PAGE INTENTIONALLY LEFT BLANK xv ACKNOWLEDGMENTS Many thanks to David Caliga of SRC Computer for his...11 2. Wigner - Ville Distribution .................................................................11 3. Choi-Williams... Ville Distribution ...................................12 Table 3. C Code Output for Wigner - Ville Distribution

Analysis of digital communication signals and extraction of parameters

NASA Astrophysics Data System (ADS)

Al-Jowder, Anwar

1994-12-01

The signal classification performance of four types of electronics support measure (ESM) communications detection systems is compared from the standpoint of the unintended receiver (interceptor). Typical digital communication signals considered include binary phase shift keying (BPSK), quadrature phase shift keying (QPSK), frequency shift keying (FSK), and on-off keying (OOK). The analysis emphasizes the use of available signal processing software. Detection methods compared include broadband energy detection, FFT-based narrowband energy detection, and two correlation methods which employ the fast Fourier transform (FFT). The correlation methods utilize modified time-frequency distributions, where one of these is based on the Wigner-Ville distribution (WVD). Gaussian white noise is added to the signal to simulate various signal-to-noise ratios (SNR's).

Probe for optically monitoring progress of in-situ vitrification of soil

DOEpatents

Timmerman, Craig L.; Oma, Kenton H.; Davis, Karl C.

1988-01-01

A detector system for sensing the progress of an ISV process along an expected path comprises multiple sensors each having an input port. The input ports are distributed along the expected path of the ISV process between a starting location and an expected ending location. Each sensor generates an electrical signal representative of the temperature in the vicinity of its input port. A signal processor is coupled to the sensors to receive an electrical signal generated by a sensor, and generate a signal which is encoded with information which identifies the sensor and whether the ISV process has reached the sensor's input port. A transmitter propagates the encoded signal. The signal processor and the transmitter are below ground at a location beyond the expected ending location of the ISV process in the direction from the starting location to the expected ending location. A signal receiver and a decoder are located above ground for receiving the encoded signal propagated by the transmitter, decoding the encoded signal and providing a human-perceptible indication of the progress of the ISV process.

Probe for optically monitoring progress of in-situ vitrification of soil

DOEpatents

Timmerman, C.L.; Oma, K.H.; Davis, K.C.

1988-08-09

A detector system for sensing the progress of an ISV process along an expected path comprises multiple sensors each having an input port. The input ports are distributed along the expected path of the ISV process between a starting location and an expected ending location. Each sensor generates an electrical signal representative of the temperature in the vicinity of its input port. A signal processor is coupled to the sensors to receive an electrical signal generated by a sensor, and generate a signal which is encoded with information which identifies the sensor and whether the ISV process has reached the sensor's input port. A transmitter propagates the encoded signal. The signal processor and the transmitter are below ground at a location beyond the expected ending location of the ISV process in the direction from the starting location to the expected ending location. A signal receiver and a decoder are located above ground for receiving the encoded signal propagated by the transmitter, decoding the encoded signal and providing a human-perceptible indication of the progress of the ISV process. 7 figs.

An electronic circuit that detects left ventricular ejection events by processing the arterial pressure waveform

NASA Technical Reports Server (NTRS)

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

1972-01-01

An electronic circuit for processing arterial blood pressure waveform signals is described. The circuit detects blood pressure as the heart pumps blood through the aortic valve and the pressure distribution caused by aortic valve closure. From these measurements, timing signals for use in measuring the left ventricular ejection time is determined, and signals are provided for computer monitoring of the cardiovascular system. Illustrations are given of the circuit and pressure waveforms.

A tone analyzer based on a piezoelectric polymer and organic thin film transistors.

PubMed

Hsu, Yu-Jen; Kymissis, Ioannis

2012-12-01

A tone analyzer is demonstrated using a distributed resonator architecture on a tensioned piezoelectric polyvinyledene diuoride (PVDF) sheet. This sheet is used as both the resonator and detection element. Two architectures are demonstrated; one uses distributed, directly addressed elements as a proof of concept, and the other integrates organic thin film transistor-based transimpedance amplifiers directly with the PVDF to convert the piezoelectric charge signal into a current signal. The PVDF sheet material is instrumented along its length, and the amplitude response at 15 sites is recorded and analyzed as a function of the frequency of excitation. The determination of the dominant component of an incoming tone is demonstrated using linear system decomposition of the time-averaged response of the sheet and is performed without any time domain analysis. This design allows for the determination of the spectral composition of a sound using the mechanical signal processing provided by the amplitude response and eliminates the need for time-domain downstream signal processing of the incoming signal.

BioSigPlot: an opensource tool for the visualization of multi-channel biomedical signals with Matlab.

PubMed

Boudet, Samuel; Peyrodie, Laurent; Gallois, Philippe; de l'Aulnoit, Denis Houzé; Cao, Hua; Forzy, Gérard

2013-01-01

This paper presents a Matlab-based software (MathWorks inc.) called BioSigPlot for the visualization of multi-channel biomedical signals, particularly for the EEG. This tool is designed for researchers on both engineering and medicine who have to collaborate to visualize and analyze signals. It aims to provide a highly customizable interface for signal processing experimentation in order to plot several kinds of signals while integrating the common tools for physician. The main advantages compared to other existing programs are the multi-dataset displaying, the synchronization with video and the online processing. On top of that, this program uses object oriented programming, so that the interface can be controlled by both graphic controls and command lines. It can be used as EEGlab plug-in but, since it is not limited to EEG, it would be distributed separately. BioSigPlot is distributed free of charge (http://biosigplot.sourceforge.net), under the terms of GNU Public License for non-commercial use and open source development.

On the degree distribution of horizontal visibility graphs associated with Markov processes and dynamical systems: diagrammatic and variational approaches

NASA Astrophysics Data System (ADS)

Lacasa, Lucas

2014-09-01

Dynamical processes can be transformed into graphs through a family of mappings called visibility algorithms, enabling the possibility of (i) making empirical time series analysis and signal processing and (ii) characterizing classes of dynamical systems and stochastic processes using the tools of graph theory. Recent works show that the degree distribution of these graphs encapsulates much information on the signals' variability, and therefore constitutes a fundamental feature for statistical learning purposes. However, exact solutions for the degree distributions are only known in a few cases, such as for uncorrelated random processes. Here we analytically explore these distributions in a list of situations. We present a diagrammatic formalism which computes for all degrees their corresponding probability as a series expansion in a coupling constant which is the number of hidden variables. We offer a constructive solution for general Markovian stochastic processes and deterministic maps. As case tests we focus on Ornstein-Uhlenbeck processes, fully chaotic and quasiperiodic maps. Whereas only for certain degree probabilities can all diagrams be summed exactly, in the general case we show that the perturbation theory converges. In a second part, we make use of a variational technique to predict the complete degree distribution for special classes of Markovian dynamics with fast-decaying correlations. In every case we compare the theory with numerical experiments.

Vehicular headways on signalized intersections: theory, models, and reality

NASA Astrophysics Data System (ADS)

Krbálek, Milan; Šleis, Jiří

2015-01-01

We discuss statistical properties of vehicular headways measured on signalized crossroads. On the basis of mathematical approaches, we formulate theoretical and empirically inspired criteria for the acceptability of theoretical headway distributions. Sequentially, the multifarious families of statistical distributions (commonly used to fit real-road headway statistics) are confronted with these criteria, and with original empirical time clearances gauged among neighboring vehicles leaving signal-controlled crossroads after a green signal appears. Using three different numerical schemes, we demonstrate that an arrangement of vehicles on an intersection is a consequence of the general stochastic nature of queueing systems, rather than a consequence of traffic rules, driver estimation processes, or decision-making procedures.

Range Sidelobe Suppression Using Complementary Sets in Distributed Multistatic Radar Networks

PubMed Central

Wang, Xuezhi; Song, Yongping; Huang, Xiaotao; Moran, Bill

2017-01-01

We propose an alternative waveform scheme built on mutually-orthogonal complementary sets for a distributed multistatic radar. Our analysis and simulation show a reduced frequency band requirement for signal separation between antennas with centralized signal processing using the same carrier frequency. While the scheme can tolerate fluctuations of carrier frequencies and phases, range sidelobes arise when carrier frequencies between antennas are significantly different. PMID:29295566

Optical Signal Processing: Poisson Image Restoration and Shearing Interferometry

NASA Technical Reports Server (NTRS)

Hong, Yie-Ming

1973-01-01

Optical signal processing can be performed in either digital or analog systems. Digital computers and coherent optical systems are discussed as they are used in optical signal processing. Topics include: image restoration; phase-object visualization; image contrast reversal; optical computation; image multiplexing; and fabrication of spatial filters. Digital optical data processing deals with restoration of images degraded by signal-dependent noise. When the input data of an image restoration system are the numbers of photoelectrons received from various areas of a photosensitive surface, the data are Poisson distributed with mean values proportional to the illuminance of the incoherently radiating object and background light. Optical signal processing using coherent optical systems is also discussed. Following a brief review of the pertinent details of Ronchi's diffraction grating interferometer, moire effect, carrier-frequency photography, and achromatic holography, two new shearing interferometers based on them are presented. Both interferometers can produce variable shear.

Two Dimensional Processing Of Speech And Ecg Signals Using The Wigner-Ville Distribution

NASA Astrophysics Data System (ADS)

Boashash, Boualem; Abeysekera, Saman S.

1986-12-01

The Wigner-Ville Distribution (WVD) has been shown to be a valuable tool for the analysis of non-stationary signals such as speech and Electrocardiogram (ECG) data. The one-dimensional real data are first transformed into a complex analytic signal using the Hilbert Transform and then a 2-dimensional image is formed using the Wigner-Ville Transform. For speech signals, a contour plot is determined and used as a basic feature. for a pattern recognition algorithm. This method is compared with the classical Short Time Fourier Transform (STFT) and is shown, to be able to recognize isolated words better in a noisy environment. The same method together with the concept of instantaneous frequency of the signal is applied to the analysis of ECG signals. This technique allows one to classify diseased heart-beat signals. Examples are shown.

A dynamic multi-channel speech enhancement system for distributed microphones in a car environment

NASA Astrophysics Data System (ADS)

Matheja, Timo; Buck, Markus; Fingscheidt, Tim

2013-12-01

Supporting multiple active speakers in automotive hands-free or speech dialog applications is an interesting issue not least due to comfort reasons. Therefore, a multi-channel system for enhancement of speech signals captured by distributed distant microphones in a car environment is presented. Each of the potential speakers in the car has a dedicated directional microphone close to his position that captures the corresponding speech signal. The aim of the resulting overall system is twofold: On the one hand, a combination of an arbitrary pre-defined subset of speakers' signals can be performed, e.g., to create an output signal in a hands-free telephone conference call for a far-end communication partner. On the other hand, annoying cross-talk components from interfering sound sources occurring in multiple different mixed output signals are to be eliminated, motivated by the possibility of other hands-free applications being active in parallel. The system includes several signal processing stages. A dedicated signal processing block for interfering speaker cancellation attenuates the cross-talk components of undesired speech. Further signal enhancement comprises the reduction of residual cross-talk and background noise. Subsequently, a dynamic signal combination stage merges the processed single-microphone signals to obtain appropriate mixed signals at the system output that may be passed to applications such as telephony or a speech dialog system. Based on signal power ratios between the particular microphone signals, an appropriate speaker activity detection and therewith a robust control mechanism of the whole system is presented. The proposed system may be dynamically configured and has been evaluated for a car setup with four speakers sitting in the car cabin disturbed in various noise conditions.

802.11ac WLAN MIMO radio-over-fiber distributed antenna system for in-building networks based on multicore fiber

NASA Astrophysics Data System (ADS)

Morant, Maria; Llorente, Roberto

2017-01-01

In this work we propose and evaluate experimentally the performance of IEEE 802.11ac WLAN standard signals in radio-over-fiber (RoF) distributed-antenna systems based on multicore fiber (MCF) for in-building WLAN connectivity. The RoF performance of WLAN signals with different bandwidth is investigated considering up to IEEE 802.11ac maximum of 160 MHz per user. We evaluate experimentally the performance of WLAN signals employing different modulation and coding schemes achieving bitrates from 78 Mbps to 1404 Mbps per user in distances up to 300 m in a 4-core MCF. The performance of the wireless standard multiple-input multiple-output (MIMO) processing algorithms included in WLAN signals applied to the RoF transmission in MCF optical systems is also evaluated. The impact on the quality of the signal from one of the cores in the MIMO processing is investigated and compared with the results achieved with single-input single-output (SISO) transmission in each core. We measured the error vector magnitude (EVM) and the OFDM data burst information of the received WLAN signals after RoF transmission for different distributed-antenna systems with uni- and bi-directional MCF communication. Finally, we compare the received EVM of a single-antenna system (SISO arrangement) with WLAN systems using two antennas (2×2 MIMO) and four antennas (4×4 MIMO).

The application of digital signal processing techniques to a teleoperator radar system

NASA Technical Reports Server (NTRS)

Pujol, A.

1982-01-01

A digital signal processing system was studied for the determination of the spectral frequency distribution of echo signals from a teleoperator radar system. The system consisted of a sample and hold circuit, an analog to digital converter, a digital filter, and a Fast Fourier Transform. The system is interfaced to a 16 bit microprocessor. The microprocessor is programmed to control the complete digital signal processing. The digital filtering and Fast Fourier Transform functions are implemented by a S2815 digital filter/utility peripheral chip and a S2814A Fast Fourier Transform chip. The S2815 initially simulates a low-pass Butterworth filter with later expansion to complete filter circuit (bandpass and highpass) synthesizing.

[Research and realization of signal processing algorithms based on FPGA in digital ophthalmic ultrasonography imaging].

PubMed

Fang, Simin; Zhou, Sheng; Wang, Xiaochun; Ye, Qingsheng; Tian, Ling; Ji, Jianjun; Wang, Yanqun

2015-01-01

To design and improve signal processing algorithms of ophthalmic ultrasonography based on FPGA. Achieved three signal processing modules: full parallel distributed dynamic filter, digital quadrature demodulation, logarithmic compression, using Verilog HDL hardware language in Quartus II. Compared to the original system, the hardware cost is reduced, the whole image shows clearer and more information of the deep eyeball contained in the image, the depth of detection increases from 5 cm to 6 cm. The new algorithms meet the design requirements and achieve the system's optimization that they can effectively improve the image quality of existing equipment.

Estimating Transmitted-Signal Phase Variations for Uplink Array Antennas

NASA Technical Reports Server (NTRS)

Paal, Leslie; Mukai, Ryan; Vilntrotter, Victor; Cornish, Timothy; Lee, Dennis

2009-01-01

A method of estimating phase drifts of microwave signals distributed to, and transmitted by, antennas in an array involves the use of the signals themselves as phase references. The method was conceived as part of the solution of the problem of maintaining precise phase calibration required for proper operation of an array of Deep Space Network (DSN) antennas on Earth used for communicating with distant spacecraft at frequencies between 7 and 8 GHz. The method could also be applied to purely terrestrial phased-array radar and other radio antenna array systems. In the DSN application, the electrical lengths (effective signal-propagation path lengths) of the various branches of the system for distributing the transmitted signals to the antennas are not precisely known, and they vary with time. The variations are attributable mostly to thermal expansion and contraction of fiber-optic and electrical signal cables and to a variety of causes associated with aging of signal-handling components. The variations are large enough to introduce large phase drifts at the signal frequency. It is necessary to measure and correct for these phase drifts in order to maintain phase calibration of the antennas. A prior method of measuring phase drifts involves the use of reference-frequency signals separate from the transmitted signals. A major impediment to accurate measurement of phase drifts over time by the prior method is the fact that although DSN reference-frequency sources separate from the transmitting signal sources are stable and accurate enough for most DSN purposes, they are not stable enough for use in maintaining phase calibrations, as required, to within a few degrees over times as long as days or possibly even weeks. By eliminating reliance on the reference-frequency subsystem, the present method overcomes this impediment. In a DSN array to which the present method applies (see figure), the microwave signals to be transmitted are generated by exciters in a signal-processing center, then distributed to the antennas via optical fibers. At each antenna, the signals are used to drive a microwave power-amplifier train, the output of which is coupled to the antenna for transmission. A small fraction of the power-amplifier-train output is sent back to the signal-processing center along another optical fiber that is part of the same fiber-optic cable used to distribute the transmitted signal to the antenna. In the signal-processing center, the signal thus returned from each antenna is detected and its phase is compared with the phase of the signal sampled directly from the corresponding exciter. It is known, from other measurements, that the signal-propagation path length from the power-amplifier-train output port to the phase center of each antenna is sufficiently stable and, hence, that sampling the signal at the power-amplifier-train output port suffices for the purpose of characterizing the phase drift of the transmitted signal at the phase center of the antenna

Power Aware Signal Processing Environment (PASPE) for PAC/C

DTIC Science & Technology

2003-02-01

vs. FFT Size For our implementation , the Annapolis FFT core was radix-256, and therefore the smallest PN code length that could be processed was the...PN-64. A C- code version of correlate was compared to the FPGA 61 implementation . The results in Figure 68 show that for a PN-1024, the...12a. DISTRIBUTION / AVAILABILITY STATEMENT APPROVED FOR PUBLIC RELEASE; DISTRIBUTION UNLIMITED. 12b. DISTRIBUTION CODE 13. ABSTRACT (Maximum

Frequency-wavenumber processing for infrasound distributed arrays.

PubMed

Costley, R Daniel; Frazier, W Garth; Dillion, Kevin; Picucci, Jennifer R; Williams, Jay E; McKenna, Mihan H

2013-10-01

The work described herein discusses the application of a frequency-wavenumber signal processing technique to signals from rectangular infrasound arrays for detection and estimation of the direction of travel of infrasound. Arrays of 100 sensors were arranged in square configurations with sensor spacing of 2 m. Wind noise data were collected at one site. Synthetic infrasound signals were superposed on top of the wind noise to determine the accuracy and sensitivity of the technique with respect to signal-to-noise ratio. The technique was then applied to an impulsive event recorded at a different site. Preliminary results demonstrated the feasibility of this approach.

Applying simulation model to uniform field space charge distribution measurements by the PEA method

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

Liu, Y.; Salama, M.M.A.

1996-12-31

Signals measured under uniform fields by the Pulsed Electroacoustic (PEA) method have been processed by the deconvolution procedure to obtain space charge distributions since 1988. To simplify data processing, a direct method has been proposed recently in which the deconvolution is eliminated. However, the surface charge cannot be represented well by the method because the surface charge has a bandwidth being from zero to infinity. The bandwidth of the charge distribution must be much narrower than the bandwidths of the PEA system transfer function in order to apply the direct method properly. When surface charges can not be distinguished frommore » space charge distributions, the accuracy and the resolution of the obtained space charge distributions decrease. To overcome this difficulty a simulation model is therefore proposed. This paper shows their attempts to apply the simulation model to obtain space charge distributions under plane-plane electrode configurations. Due to the page limitation for the paper, the charge distribution originated by the simulation model is compared to that obtained by the direct method with a set of simulated signals.« less

Hardware design and implementation of fast DOA estimation method based on multicore DSP

NASA Astrophysics Data System (ADS)

Guo, Rui; Zhao, Yingxiao; Zhang, Yue; Lin, Qianqiang; Chen, Zengping

2016-10-01

In this paper, we present a high-speed real-time signal processing hardware platform based on multicore digital signal processor (DSP). The real-time signal processing platform shows several excellent characteristics including high performance computing, low power consumption, large-capacity data storage and high speed data transmission, which make it able to meet the constraint of real-time direction of arrival (DOA) estimation. To reduce the high computational complexity of DOA estimation algorithm, a novel real-valued MUSIC estimator is used. The algorithm is decomposed into several independent steps and the time consumption of each step is counted. Based on the statistics of the time consumption, we present a new parallel processing strategy to distribute the task of DOA estimation to different cores of the real-time signal processing hardware platform. Experimental results demonstrate that the high processing capability of the signal processing platform meets the constraint of real-time direction of arrival (DOA) estimation.

Self spectrum window method in wigner-ville distribution.

PubMed

Liu, Zhongguo; Liu, Changchun; Liu, Boqiang; Lv, Yangsheng; Lei, Yinsheng; Yu, Mengsun

2005-01-01

Wigner-Ville distribution (WVD) is an important type of time-frequency analysis in biomedical signal processing. The cross-term interference in WVD has a disadvantageous influence on its application. In this research, the Self Spectrum Window (SSW) method was put forward to suppress the cross-term interference, based on the fact that the cross-term and auto-WVD- terms in integral kernel function are orthogonal. With the Self Spectrum Window (SSW) algorithm, a real auto-WVD function was used as a template to cross-correlate with the integral kernel function, and the Short Time Fourier Transform (STFT) spectrum of the signal was used as window function to process the WVD in time-frequency plane. The SSW method was confirmed by computer simulation with good analysis results. Satisfactory time- frequency distribution was obtained.

Separation and reconstruction of high pressure water-jet reflective sound signal based on ICA

NASA Astrophysics Data System (ADS)

Yang, Hongtao; Sun, Yuling; Li, Meng; Zhang, Dongsu; Wu, Tianfeng

2011-12-01

The impact of high pressure water-jet on the different materials target will produce different reflective mixed sound. In order to reconstruct the reflective sound signals distribution on the linear detecting line accurately and to separate the environment noise effectively, the mixed sound signals acquired by linear mike array were processed by ICA. The basic principle of ICA and algorithm of FASTICA were described in detail. The emulation experiment was designed. The environment noise signal was simulated by using band-limited white noise and the reflective sound signal was simulated by using pulse signal. The reflective sound signal attenuation produced by the different distance transmission was simulated by weighting the sound signal with different contingencies. The mixed sound signals acquired by linear mike array were synthesized by using the above simulated signals and were whitened and separated by ICA. The final results verified that the environment noise separation and the reconstruction of the detecting-line sound distribution can be realized effectively.

Modeling Geodetic Processes with Levy α-Stable Distribution and FARIMA

NASA Astrophysics Data System (ADS)

Montillet, Jean-Philippe; Yu, Kegen

2015-04-01

Over the last years the scientific community has been using the auto regressive moving average (ARMA) model in the modeling of the noise in global positioning system (GPS) time series (daily solution). This work starts with the investigation of the limit of the ARMA model which is widely used in signal processing when the measurement noise is white. Since a typical GPS time series consists of geophysical signals (e.g., seasonal signal) and stochastic processes (e.g., coloured and white noise), the ARMA model may be inappropriate. Therefore, the application of the fractional auto-regressive integrated moving average (FARIMA) model is investigated. The simulation results using simulated time series as well as real GPS time series from a few selected stations around Australia show that the FARIMA model fits the time series better than other models when the coloured noise is larger than the white noise. The second fold of this work focuses on fitting the GPS time series with the family of Levy α-stable distributions. Using this distribution, a hypothesis test is developed to eliminate effectively coarse outliers from GPS time series, achieving better performance than using the rule of thumb of n standard deviations (with n chosen empirically).

[An Extraction and Recognition Method of the Distributed Optical Fiber Vibration Signal Based on EMD-AWPP and HOSA-SVM Algorithm].

PubMed

Zhang, Yanjun; Liu, Wen-zhe; Fu, Xing-hu; Bi, Wei-hong

2016-02-01

Given that the traditional signal processing methods can not effectively distinguish the different vibration intrusion signal, a feature extraction and recognition method of the vibration information is proposed based on EMD-AWPP and HOSA-SVM, using for high precision signal recognition of distributed fiber optic intrusion detection system. When dealing with different types of vibration, the method firstly utilizes the adaptive wavelet processing algorithm based on empirical mode decomposition effect to reduce the abnormal value influence of sensing signal and improve the accuracy of signal feature extraction. Not only the low frequency part of the signal is decomposed, but also the high frequency part the details of the signal disposed better by time-frequency localization process. Secondly, it uses the bispectrum and bicoherence spectrum to accurately extract the feature vector which contains different types of intrusion vibration. Finally, based on the BPNN reference model, the recognition parameters of SVM after the implementation of the particle swarm optimization can distinguish signals of different intrusion vibration, which endows the identification model stronger adaptive and self-learning ability. It overcomes the shortcomings, such as easy to fall into local optimum. The simulation experiment results showed that this new method can effectively extract the feature vector of sensing information, eliminate the influence of random noise and reduce the effects of outliers for different types of invasion source. The predicted category identifies with the output category and the accurate rate of vibration identification can reach above 95%. So it is better than BPNN recognition algorithm and improves the accuracy of the information analysis effectively.

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.

Exploiting Virtual Synchrony in Distributed Systems

DTIC Science & Technology

1987-02-01

for distributed systems yield the best performance relative to the level of synchronization guaranteed by the primitive . A pro- grammer could then... synchronization facility. Semaphores Replicated binary and general semaphores . Monitors Monitor lock, condition variables and signals. Deadlock detection...We describe applications of a new software abstraction called the virtually synchronous process group. Such a group consists of a set of processes

Investigation of the photon statistics of parametric fluorescence in a traveling-wave parametric amplifier by means of self-homodyne tomography.

PubMed

Vasilyev, M; Choi, S K; Kumar, P; D'Ariano, G M

1998-09-01

Photon-number distributions for parametric fluorescence from a nondegenerate optical parametric amplifier are measured with a novel self-homodyne technique. These distributions exhibit the thermal-state character predicted by theory. However, a difference between the fluorescence gain and the signal gain of the parametric amplifier is observed. We attribute this difference to a change in the signal-beam profile during the traveling-wave pulsed amplification process.

Wavelet-Based Signal Processing for Monitoring Discomfort and Fatigue

DTIC Science & Technology

2008-06-01

Wigner - Ville distribution ( WVD ), the short-time Fourier transform (STFT) or spectrogram, the Choi-Williams distribution (CWD), the smoothed pseudo Wigner ...has the advantage of being computationally less expensive than other standard techniques, such as the Wigner - Ville distribution ( WVD ), the spectrogram...slopes derived from the spectrogram and the smoothed pseudo Wigner - Ville distribution . Furthermore, slopes derived from the filter bank

All-digital radar architecture

NASA Astrophysics Data System (ADS)

Molchanov, Pavlo A.

2014-10-01

All digital radar architecture requires exclude mechanical scan system. The phase antenna array is necessarily large because the array elements must be co-located with very precise dimensions and will need high accuracy phase processing system for aggregate and distribute T/R modules data to/from antenna elements. Even phase array cannot provide wide field of view. New nature inspired all digital radar architecture proposed. The fly's eye consists of multiple angularly spaced sensors giving the fly simultaneously thee wide-area visual coverage it needs to detect and avoid the threats around him. Fly eye radar antenna array consist multiple directional antennas loose distributed along perimeter of ground vehicle or aircraft and coupled with receiving/transmitting front end modules connected by digital interface to central processor. Non-steering antenna array allows creating all-digital radar with extreme flexible architecture. Fly eye radar architecture provides wide possibility of digital modulation and different waveform generation. Simultaneous correlation and integration of thousands signals per second from each point of surveillance area allows not only detecting of low level signals ((low profile targets), but help to recognize and classify signals (targets) by using diversity signals, polarization modulation and intelligent processing. Proposed all digital radar architecture with distributed directional antenna array can provide a 3D space vector to the jammer by verification direction of arrival for signals sources and as result jam/spoof protection not only for radar systems, but for communication systems and any navigation constellation system, for both encrypted or unencrypted signals, for not limited number or close positioned jammers.

Joint Estimation of Time-Frequency Signature and DOA Based on STFD for Multicomponent Chirp Signals

PubMed Central

Zhao, Ziyue; Liu, Congfeng

2014-01-01

In the study of the joint estimation of time-frequency signature and direction of arrival (DOA) for multicomponent chirp signals, an estimation method based on spatial time-frequency distributions (STFDs) is proposed in this paper. Firstly, array signal model for multicomponent chirp signals is presented and then array processing is applied in time-frequency analysis to mitigate cross-terms. According to the results of the array processing, Hough transform is performed and the estimation of time-frequency signature is obtained. Subsequently, subspace method for DOA estimation based on STFD matrix is achieved. Simulation results demonstrate the validity of the proposed method. PMID:27382610

Joint Estimation of Time-Frequency Signature and DOA Based on STFD for Multicomponent Chirp Signals.

PubMed

Zhao, Ziyue; Liu, Congfeng

2014-01-01

In the study of the joint estimation of time-frequency signature and direction of arrival (DOA) for multicomponent chirp signals, an estimation method based on spatial time-frequency distributions (STFDs) is proposed in this paper. Firstly, array signal model for multicomponent chirp signals is presented and then array processing is applied in time-frequency analysis to mitigate cross-terms. According to the results of the array processing, Hough transform is performed and the estimation of time-frequency signature is obtained. Subsequently, subspace method for DOA estimation based on STFD matrix is achieved. Simulation results demonstrate the validity of the proposed method.

Neural networks for continuous online learning and control.

PubMed

Choy, Min Chee; Srinivasan, Dipti; Cheu, Ruey Long

2006-11-01

This paper proposes a new hybrid neural network (NN) model that employs a multistage online learning process to solve the distributed control problem with an infinite horizon. Various techniques such as reinforcement learning and evolutionary algorithm are used to design the multistage online learning process. For this paper, the infinite horizon distributed control problem is implemented in the form of real-time distributed traffic signal control for intersections in a large-scale traffic network. The hybrid neural network model is used to design each of the local traffic signal controllers at the respective intersections. As the state of the traffic network changes due to random fluctuation of traffic volumes, the NN-based local controllers will need to adapt to the changing dynamics in order to provide effective traffic signal control and to prevent the traffic network from becoming overcongested. Such a problem is especially challenging if the local controllers are used for an infinite horizon problem where online learning has to take place continuously once the controllers are implemented into the traffic network. A comprehensive simulation model of a section of the Central Business District (CBD) of Singapore has been developed using PARAMICS microscopic simulation program. As the complexity of the simulation increases, results show that the hybrid NN model provides significant improvement in traffic conditions when evaluated against an existing traffic signal control algorithm as well as a new, continuously updated simultaneous perturbation stochastic approximation-based neural network (SPSA-NN). Using the hybrid NN model, the total mean delay of each vehicle has been reduced by 78% and the total mean stoppage time of each vehicle has been reduced by 84% compared to the existing traffic signal control algorithm. This shows the efficacy of the hybrid NN model in solving large-scale traffic signal control problem in a distributed manner. Also, it indicates the possibility of using the hybrid NN model for other applications that are similar in nature as the infinite horizon distributed control problem.

Layover and shadow detection based on distributed spaceborne single-baseline InSAR

NASA Astrophysics Data System (ADS)

Huanxin, Zou; Bin, Cai; Changzhou, Fan; Yun, Ren

2014-03-01

Distributed spaceborne single-baseline InSAR is an effective technique to get high quality Digital Elevation Model. Layover and Shadow are ubiquitous phenomenon in SAR images because of geometric relation of SAR imaging. In the signal processing of single-baseline InSAR, the phase singularity of Layover and Shadow leads to the phase difficult to filtering and unwrapping. This paper analyzed the geometric and signal model of the Layover and Shadow fields. Based on the interferometric signal autocorrelation matrix, the paper proposed the signal number estimation method based on information theoretic criteria, to distinguish Layover and Shadow from normal InSAR fields. The effectiveness and practicability of the method proposed in the paper are validated in the simulation experiments and theoretical analysis.

Novel auto-correction method in a fiber-optic distributed-temperature sensor using reflected anti-Stokes Raman scattering.

PubMed

Hwang, Dusun; Yoon, Dong-Jin; Kwon, Il-Bum; Seo, Dae-Cheol; Chung, Youngjoo

2010-05-10

A novel method for auto-correction of fiber optic distributed temperature sensor using anti-Stokes Raman back-scattering and its reflected signal is presented. This method processes two parts of measured signal. One part is the normal back scattered anti-Stokes signal and the other part is the reflected signal which eliminate not only the effect of local losses due to the micro-bending or damages on fiber but also the differential attenuation. Because the beams of the same wavelength are used to cancel out the local variance in transmission medium there is no differential attenuation inherently. The auto correction concept was verified by the bending experiment on different bending points. (c) 2010 Optical Society of America.

Fiber-distributed Ultra-wideband noise radar with steerable power spectrum and colorless base station.

PubMed

Zheng, Jianyu; Wang, Hui; Fu, Jianbin; Wei, Li; Pan, Shilong; Wang, Lixian; Liu, Jianguo; Zhu, Ninghua

2014-03-10

A fiber-distributed Ultra-wideband (UWB) noise radar was achieved, which consists of a chaotic UWB noise source based on optoelectronic oscillator (OEO), a fiber-distributed transmission link, a colorless base station (BS), and a cross-correlation processing module. Due to a polarization modulation based microwave photonic filter and an electrical UWB pass-band filter embedded in the feedback loop of the OEO, the power spectrum of chaotic UWB signal could be shaped and notch-filtered to avoid the spectrum-overlay-induced interference to the narrow band signals. Meanwhile, the wavelength-reusing could be implemented in the BS by means of the distributed polarization modulation-to-intensity modulation conversion. The experimental comparison for range finding was carried out as the chaotic UWB signal was notch-filtered at 5.2 GHz and 7.8 GHz or not. Measured results indicate that space resolution with cm-level could be realized after 3-km fiber transmission thanks to the excellent self-correlation property of the UWB noise signal provided by the OEO. The performance deterioration of the radar raised by the energy loss of the notch-filtered noise signal was negligible.

Evaluation of Ultrasonic Fiber Structure Extraction Technique Using Autopsy Specimens of Liver

NASA Astrophysics Data System (ADS)

Yamaguchi, Tadashi; Hirai, Kazuki; Yamada, Hiroyuki; Ebara, Masaaki; Hachiya, Hiroyuki

2005-06-01

It is very important to diagnose liver cirrhosis noninvasively and correctly. In our previous studies, we proposed a processing technique to detect changes in liver tissue in vivo. In this paper, we propose the evaluation of the relationship between liver disease and echo information using autopsy specimens of a human liver in vitro. It is possible to verify the function of a processing parameter clearly and to compare the processing result and the actual human liver tissue structure by in vitro experiment. In the results of our processing technique, information that did not obey a Rayleigh distribution from the echo signal of the autopsy liver specimens was extracted depending on changes in a particular processing parameter. The fiber tissue structure of the same specimen was extracted from a number of histological images of stained tissue. We constructed 3D structures using the information extracted from the echo signal and the fiber structure of the stained tissue and compared the two. By comparing the 3D structures, it is possible to evaluate the relationship between the information that does not obey a Rayleigh distribution of the echo signal and the fibrosis structure.

Adaptive Fourier decomposition based ECG denoising.

PubMed

Wang, Ze; Wan, Feng; Wong, Chi Man; Zhang, Liming

2016-10-01

A novel ECG denoising method is proposed based on the adaptive Fourier decomposition (AFD). The AFD decomposes a signal according to its energy distribution, thereby making this algorithm suitable for separating pure ECG signal and noise with overlapping frequency ranges but different energy distributions. A stop criterion for the iterative decomposition process in the AFD is calculated on the basis of the estimated signal-to-noise ratio (SNR) of the noisy signal. The proposed AFD-based method is validated by the synthetic ECG signal using an ECG model and also real ECG signals from the MIT-BIH Arrhythmia Database both with additive Gaussian white noise. Simulation results of the proposed method show better performance on the denoising and the QRS detection in comparing with major ECG denoising schemes based on the wavelet transform, the Stockwell transform, the empirical mode decomposition, and the ensemble empirical mode decomposition. Copyright © 2016 Elsevier Ltd. All rights reserved.

Radar signal transmission and switching over optical networks

NASA Astrophysics Data System (ADS)

Esmail, Maged A.; Ragheb, Amr; Seleem, Hussein; Fathallah, Habib; Alshebeili, Saleh

2018-03-01

In this paper, we experimentally demonstrate a radar signal distribution over optical networks. The use of fiber enables us to distribute radar signals to distant sites with a low power loss. Moreover, fiber networks can reduce the radar system cost, by sharing precise and expensive radar signal generation and processing equipment. In order to overcome the bandwidth challenges in electrical switches, a semiconductor optical amplifier (SOA) is used as an all-optical device for wavelength conversion to the desired port (or channel) of a wavelength division multiplexing (WDM) network. Moreover, the effect of chromatic dispersion in double sideband (DSB) signals is combated by generating optical single sideband (OSSB) signals. The optimal values of the SOA device parameters required to generate an OSSB with a high sideband suppression ratio (SSR) are determined. We considered various parameters such as injection current, pump power, and probe power. In addition, the effect of signal wavelength conversion and transmission over fiber are studied in terms of signal dynamic range.

Bragg-cell receiver study

NASA Technical Reports Server (NTRS)

Wilson, Lonnie A.

1987-01-01

Bragg-cell receivers are employed in specialized Electronic Warfare (EW) applications for the measurement of frequency. Bragg-cell receiver characteristics are fully characterized for simple RF emitter signals. This receiver is early in its development cycle when compared to the IFM receiver. Functional mathematical models are derived and presented in this report for the Bragg-cell receiver. Theoretical analysis is presented and digital computer signal processing results are presented for the Bragg-cell receiver. Probability density function analysis are performed for output frequency. Probability density function distributions are observed to depart from assumed distributions for wideband and complex RF signals. This analysis is significant for high resolution and fine grain EW Bragg-cell receiver systems.

3-D readout-electronics packaging for high-bandwidth massively paralleled imager

DOEpatents

Kwiatkowski, Kris; Lyke, James

2007-12-18

Dense, massively parallel signal processing electronics are co-packaged behind associated sensor pixels. Microchips containing a linear or bilinear arrangement of photo-sensors, together with associated complex electronics, are integrated into a simple 3-D structure (a "mirror cube"). An array of photo-sensitive cells are disposed on a stacked CMOS chip's surface at a 45.degree. angle from light reflecting mirror surfaces formed on a neighboring CMOS chip surface. Image processing electronics are held within the stacked CMOS chip layers. Electrical connections couple each of said stacked CMOS chip layers and a distribution grid, the connections for distributing power and signals to components associated with each stacked CSMO chip layer.

Fault-Tolerant Signal Processing Architectures with Distributed Error Control.

DTIC Science & Technology

1985-01-01

Zm, Revisited," Information and Control, Vol. 37, pp. 100-104, 1978. 13. J. Wakerly , Error Detecting Codes. SeIf-Checkino Circuits and Applications ...However, the newer results concerning applications of real codes are still in the publication process. Hence, two very detailed appendices are included to...significant entities to be protected. While the distributed finite field approach afforded adequate protection, its applicability was restricted and

Distributed Fusion in Sensor Networks with Information Genealogy

DTIC Science & Technology

2011-06-28

image processing [2], acoustic and speech recognition [3], multitarget tracking [4], distributed fusion [5], and Bayesian inference [6-7]. For...Adaptation for Distant-Talking Speech Recognition." in Proc Acoustics. Speech , and Signal Processing, 2004 |4| Y Bar-Shalom and T 1-. Fortmann...used in speech recognition and other classification applications [8]. But their use in underwater mine classification is limited. In this paper, we

The Not-So-Global Blood Oxygen Level-Dependent Signal.

PubMed

Billings, Jacob; Keilholz, Shella

2018-04-01

Global signal regression is a controversial processing step for resting-state functional magnetic resonance imaging, partly because the source of the global blood oxygen level-dependent (BOLD) signal remains unclear. On the one hand, nuisance factors such as motion can readily introduce coherent BOLD changes across the whole brain. On the other hand, the global signal has been linked to neural activity and vigilance levels, suggesting that it contains important neurophysiological information and should not be discarded. Any widespread pattern of coordinated activity is likely to contribute appreciably to the global signal. Such patterns may include large-scale quasiperiodic spatiotemporal patterns, known also to be tied to performance on vigilance tasks. This uncertainty surrounding the separability of the global BOLD signal from concurrent neurological processes motivated an examination of the global BOLD signal's spatial distribution. The results clarify that although the global signal collects information from all tissue classes, a diverse subset of the BOLD signal's independent components contribute the most to the global signal. Further, the timing of each network's contribution to the global signal is not consistent across volunteers, confirming the independence of a constituent process that comprises the global signal.

Laser Calibration of an Impact Disdrometer

NASA Technical Reports Server (NTRS)

Lane, John E.; Kasparis, Takis; Metzger, Philip T.; Jones, W. Linwood

2014-01-01

A practical approach to developing an operational low-cost disdrometer hinges on implementing an effective in situ adaptive calibration strategy. This calibration strategy lowers the cost of the device and provides a method to guarantee continued automatic calibration. In previous work, a collocated tipping bucket rain gauge was utilized to provide a calibration signal to the disdrometer's digital signal processing software. Rainfall rate is proportional to the 11/3 moment of the drop size distribution (a 7/2 moment can also be assumed, depending on the choice of terminal velocity relationship). In the previous case, the disdrometer calibration was characterized and weighted to the 11/3 moment of the drop size distribution (DSD). Optical extinction by rainfall is proportional to the 2nd moment of the DSD. Using visible laser light as a means to focus and generate an auxiliary calibration signal, the adaptive calibration processing is significantly improved.

Free-space microwave-power transmission

NASA Technical Reports Server (NTRS)

Brown, W. C.

1976-01-01

Laboratory-scale wireless transmission of microwave power approaches fifty-four percent efficiency. DC is converted to a 2.45-GHz signal and is transmitted through horn antenna array; microwave signal is received at rectenna and is simultaneously collected and rectified back to dc at receiving sites; dc is then processed for wired distribution.

Signal Processing Applications Of Wigner-Ville Analysis

NASA Astrophysics Data System (ADS)

Whitehouse, H. J.; Boashash, B.

1986-04-01

The Wigner-Ville distribution (WVD), a form of time-frequency analysis, is shown to be useful in the analysis of a variety of non-stationary signals both deterministic and stochastic. The properties of the WVD are reviewed and alternative methods of calculating the WVD are discussed. Applications are presented.

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.

Wavelet analysis to decompose a vibration simulation signal to improve pre-distribution testing of packaging

NASA Astrophysics Data System (ADS)

Griffiths, K. R.; Hicks, B. J.; Keogh, P. S.; Shires, D.

2016-08-01

In general, vehicle vibration is non-stationary and has a non-Gaussian probability distribution; yet existing testing methods for packaging design employ Gaussian distributions to represent vibration induced by road profiles. This frequently results in over-testing and/or over-design of the packaging to meet a specification and correspondingly leads to wasteful packaging and product waste, which represent 15bn per year in the USA and €3bn per year in the EU. The purpose of the paper is to enable a measured non-stationary acceleration signal to be replaced by a constructed signal that includes as far as possible any non-stationary characteristics from the original signal. The constructed signal consists of a concatenation of decomposed shorter duration signals, each having its own kurtosis level. Wavelet analysis is used for the decomposition process into inner and outlier signal components. The constructed signal has a similar PSD to the original signal, without incurring excessive acceleration levels. This allows an improved and more representative simulated input signal to be generated that can be used on the current generation of shaker tables. The wavelet decomposition method is also demonstrated experimentally through two correlation studies. It is shown that significant improvements over current international standards for packaging testing are achievable; hence the potential for more efficient packaging system design is possible.

Neutron Detector Signal Processing to Calculate the Effective Neutron Multiplication Factor of Subcritical Assemblies

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

Talamo, Alberto; Gohar, Yousry

2016-06-01

This report describes different methodologies to calculate the effective neutron multiplication factor of subcritical assemblies by processing the neutron detector signals using MATLAB scripts. The subcritical assembly can be driven either by a spontaneous fission neutron source (e.g. californium) or by a neutron source generated from the interactions of accelerated particles with target materials. In the latter case, when the particle accelerator operates in a pulsed mode, the signals are typically stored into two files. One file contains the time when neutron reactions occur and the other contains the times when the neutron pulses start. In both files, the timemore » is given by an integer representing the number of time bins since the start of the counting. These signal files are used to construct the neutron count distribution from a single neutron pulse. The built-in functions of MATLAB are used to calculate the effective neutron multiplication factor through the application of the prompt decay fitting or the area method to the neutron count distribution. If the subcritical assembly is driven by a spontaneous fission neutron source, then the effective multiplication factor can be evaluated either using the prompt neutron decay constant obtained from Rossi or Feynman distributions or the Modified Source Multiplication (MSM) method.« less

Distributed control network for optogenetic experiments

NASA Astrophysics Data System (ADS)

Kasprowicz, G.; Juszczyk, B.; Mankiewicz, L.

2014-11-01

Nowadays optogenetic experiments are constructed to examine social behavioural relations in groups of animals. A novel concept of implantable device with distributed control network and advanced positioning capabilities is proposed. It is based on wireless energy transfer technology, micro-power radio interface and advanced signal processing.

Body size distributions signal a regime shift in a lake ecosystem

EPA Science Inventory

Communities of organisms, from mammals to microorganisms, have discontinuous distributions of body size. This pattern of size structuring is a conservative trait of community organization and is a product of processes that occur at multiple spatial and temporal scales. In this st...

Research on distributed optical fiber sensing data processing method based on LabVIEW

NASA Astrophysics Data System (ADS)

Li, Zhonghu; Yang, Meifang; Wang, Luling; Wang, Jinming; Yan, Junhong; Zuo, Jing

2018-01-01

The pipeline leak detection and leak location problem have gotten extensive attention in the industry. In this paper, the distributed optical fiber sensing system is designed based on the heat supply pipeline. The data processing method of distributed optical fiber sensing based on LabVIEW is studied emphatically. The hardware system includes laser, sensing optical fiber, wavelength division multiplexer, photoelectric detector, data acquisition card and computer etc. The software system is developed using LabVIEW. The software system adopts wavelet denoising method to deal with the temperature information, which improved the SNR. By extracting the characteristic value of the fiber temperature information, the system can realize the functions of temperature measurement, leak location and measurement signal storage and inquiry etc. Compared with traditional negative pressure wave method or acoustic signal method, the distributed optical fiber temperature measuring system can measure several temperatures in one measurement and locate the leak point accurately. It has a broad application prospect.

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

DTIC Science & Technology

1992-10-30

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

Nonlinear Real-Time Optical Signal Processing.

DTIC Science & Technology

1988-07-01

Principal Investigator B. K. Jenkins Signal and Image Processing Institute University of Southern California Mail Code 0272 Los Angeles, California...ADDRESS (09% SteW. Mnd ZIP Code ) 10. SOURC OF FUNONG NUMBERS Bldg. 410, Bolling AFB PROGAM CT TASK WORK UNIT Washington, D.C. 20332 EEETP.aso o 11...TAB Unmnnncced Justification By Distribution/ I O’ Availablility Codes I - ’_ ji and/or 2 I Summary During the period 1 July 1987 - 30 June 1988, the

Signal Processing in Reverberation- A Summary of Performance Capability

DTIC Science & Technology

1972-08-30

34 LkP+52-DOGLB. UNCLASSIFIED N, TM No. TC- 173-72 LC INAVAL UNDERWATER SYSTEMS CENTER Technical Memorandum SIGNAL PROCESSING IN REVERBERATION- A...SUMMARY OF PERFORMANCE CAPABILITY Date: 30 August 1972 Prepared by: -- v i Alert H. Nuttall Office of the Director of Science and Technology 2TICELECTEI...Nuffall Office of the Director of Science and Technology Approved for public release; distribution unlimited UNCLASSIFIED TM No. TC- I7P-72 NAVAL

Seismic signal time-frequency analysis based on multi-directional window using greedy strategy

NASA Astrophysics Data System (ADS)

Chen, Yingpin; Peng, Zhenming; Cheng, Zhuyuan; Tian, Lin

2017-08-01

Wigner-Ville distribution (WVD) is an important time-frequency analysis technology with a high energy distribution in seismic signal processing. However, it is interfered by many cross terms. To suppress the cross terms of the WVD and keep the concentration of its high energy distribution, an adaptive multi-directional filtering window in the ambiguity domain is proposed. This begins with the relationship of the Cohen distribution and the Gabor transform combining the greedy strategy and the rotational invariance property of the fractional Fourier transform in order to propose the multi-directional window, which extends the one-dimensional, one directional, optimal window function of the optimal fractional Gabor transform (OFrGT) to a two-dimensional, multi-directional window in the ambiguity domain. In this way, the multi-directional window matches the main auto terms of the WVD more precisely. Using the greedy strategy, the proposed window takes into account the optimal and other suboptimal directions, which also solves the problem of the OFrGT, called the local concentration phenomenon, when encountering a multi-component signal. Experiments on different types of both the signal models and the real seismic signals reveal that the proposed window can overcome the drawbacks of the WVD and the OFrGT mentioned above. Finally, the proposed method is applied to a seismic signal's spectral decomposition. The results show that the proposed method can explore the space distribution of a reservoir more precisely.

Dynamic Singularity Spectrum Distribution of Sea Clutter

NASA Astrophysics Data System (ADS)

Xiong, Gang; Yu, Wenxian; Zhang, Shuning

2015-12-01

The fractal and multifractal theory have provided new approaches for radar signal processing and target-detecting under the background of ocean. However, the related research mainly focuses on fractal dimension or multifractal spectrum (MFS) of sea clutter. In this paper, a new dynamic singularity analysis method of sea clutter using MFS distribution is developed, based on moving detrending analysis (DMA-MFSD). Theoretically, we introduce the time information by using cyclic auto-correlation of sea clutter. For transient correlation series, the instantaneous singularity spectrum based on multifractal detrending moving analysis (MF-DMA) algorithm is calculated, and the dynamic singularity spectrum distribution of sea clutter is acquired. In addition, we analyze the time-varying singularity exponent ranges and maximum position function in DMA-MFSD of sea clutter. For the real sea clutter data, we analyze the dynamic singularity spectrum distribution of real sea clutter in level III sea state, and conclude that the radar sea clutter has the non-stationary and time-varying scale characteristic and represents the time-varying singularity spectrum distribution based on the proposed DMA-MFSD method. The DMA-MFSD will also provide reference for nonlinear dynamics and multifractal signal processing.

Robust signal recovery using the prolate spherical wave functions and maximum correntropy criterion

NASA Astrophysics Data System (ADS)

Zou, Cuiming; Kou, Kit Ian

2018-05-01

Signal recovery is one of the most important problem in signal processing. This paper proposes a novel signal recovery method based on prolate spherical wave functions (PSWFs). PSWFs are a kind of special functions, which have been proved having good performance in signal recovery. However, the existing PSWFs based recovery methods used the mean square error (MSE) criterion, which depends on the Gaussianity assumption of the noise distributions. For the non-Gaussian noises, such as impulsive noise or outliers, the MSE criterion is sensitive, which may lead to large reconstruction error. Unlike the existing PSWFs based recovery methods, our proposed PSWFs based recovery method employs the maximum correntropy criterion (MCC), which is independent of the noise distribution. The proposed method can reduce the impact of the large and non-Gaussian noises. The experimental results on synthetic signals with various types of noises show that the proposed MCC based signal recovery method has better robust property against various noises compared to other existing methods.

A Robust Distributed Multipoint Fiber Optic Gas Sensor System Based on AGC Amplifier Structure.

PubMed

Zhu, Cunguang; Wang, Rende; Tao, Xuechen; Wang, Guangwei; Wang, Pengpeng

2016-07-28

A harsh environment-oriented distributed multipoint fiber optic gas sensor system realized by automatic gain control (AGC) technology is proposed. To improve the photoelectric signal reliability, the electronic variable gain can be modified in real time by an AGC closed-loop feedback structure to compensate for optical transmission loss which is caused by the fiber bend loss or other reasons. The deviation of the system based on AGC structure is below 4.02% when photoelectric signal decays due to fiber bending loss for bending radius of 5 mm, which is 20 times lower than the ordinary differential system. In addition, the AGC circuit with the same electric parameters can keep the baseline intensity of signals in different channels of the distributed multipoint sensor system at the same level. This avoids repetitive calibrations and streamlines the installation process.

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.

Radar modulation classification using time-frequency representation and nonlinear regression

NASA Astrophysics Data System (ADS)

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

1999-09-01

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

Advancing Underwater Acoustic Communication for Autonomous Distributed Networks via Sparse Channel Sensing, Coding, and Navigation Support

DTIC Science & Technology

2014-09-30

underwater acoustic communication technologies for autonomous distributed underwater networks , through innovative signal processing, coding, and...4. TITLE AND SUBTITLE Advancing Underwater Acoustic Communication for Autonomous Distributed Networks via Sparse Channel Sensing, Coding, and...coding: 3) OFDM modulated dynamic coded cooperation in underwater acoustic channels; 3 Localization, Networking , and Testbed: 4) On-demand

Investigation of signal models and methods for evaluating structures of processing telecommunication information exchange systems under acoustic noise conditions

NASA Astrophysics Data System (ADS)

Kropotov, Y. A.; Belov, A. A.; Proskuryakov, A. Y.; Kolpakov, A. A.

2018-05-01

The paper considers models and methods for estimating signals during the transmission of information messages in telecommunication systems of audio exchange. One-dimensional probability distribution functions that can be used to isolate useful signals, and acoustic noise interference are presented. An approach to the estimation of the correlation and spectral functions of the parameters of acoustic signals is proposed, based on the parametric representation of acoustic signals and the components of the noise components. The paper suggests an approach to improving the efficiency of interference cancellation and highlighting the necessary information when processing signals from telecommunications systems. In this case, the suppression of acoustic noise is based on the methods of adaptive filtering and adaptive compensation. The work also describes the models of echo signals and the structure of subscriber devices in operational command telecommunications systems.

Software system for data management and distributed processing of multichannel biomedical signals.

PubMed

Franaszczuk, P J; Jouny, C C

2004-01-01

The presented software is designed for efficient utilization of cluster of PC computers for signal analysis of multichannel physiological data. The system consists of three main components: 1) a library of input and output procedures, 2) a database storing additional information about location in a storage system, 3) a user interface for selecting data for analysis, choosing programs for analysis, and distributing computing and output data on cluster nodes. The system allows for processing multichannel time series data in multiple binary formats. The description of data format, channels and time of recording are included in separate text files. Definition and selection of multiple channel montages is possible. Epochs for analysis can be selected both manually and automatically. Implementation of a new signal processing procedures is possible with a minimal programming overhead for the input/output processing and user interface. The number of nodes in cluster used for computations and amount of storage can be changed with no major modification to software. Current implementations include the time-frequency analysis of multiday, multichannel recordings of intracranial EEG of epileptic patients as well as evoked response analyses of repeated cognitive tasks.

GEOSTAR-II: A Prototype Water Vapor Imager/Sounder for the Path Mission

NASA Technical Reports Server (NTRS)

Gaier, Todd; Lambrigtsen, Bjorn; Kangaslahti, Pekka; Lim, Boon; Tanner, Alan; Harding, Dennis; Owen, Heather; Soria, Mary; ODwyer, Ian; Ruf, Christopher;

A distributed code for color in natural scenes derived from center-surround filtered cone signals

PubMed Central

Kellner, Christian J.; Wachtler, Thomas

2013-01-01

In the retina of trichromatic primates, chromatic information is encoded in an opponent fashion and transmitted to the lateral geniculate nucleus (LGN) and visual cortex via parallel pathways. Chromatic selectivities of neurons in the LGN form two separate clusters, corresponding to two classes of cone opponency. In the visual cortex, however, the chromatic selectivities are more distributed, which is in accordance with a population code for color. Previous studies of cone signals in natural scenes typically found opponent codes with chromatic selectivities corresponding to two directions in color space. Here we investigated how the non-linear spatio-chromatic filtering in the retina influences the encoding of color signals. Cone signals were derived from hyper-spectral images of natural scenes and preprocessed by center-surround filtering and rectification, resulting in parallel ON and OFF channels. Independent Component Analysis (ICA) on these signals yielded a highly sparse code with basis functions that showed spatio-chromatic selectivities. In contrast to previous analyses of linear transformations of cone signals, chromatic selectivities were not restricted to two main chromatic axes, but were more continuously distributed in color space, similar to the population code of color in the early visual cortex. Our results indicate that spatio-chromatic processing in the retina leads to a more distributed and more efficient code for natural scenes. PMID:24098289

Distribution of Software Changes for Battlefield Computer Systems: A lingering Problem

DTIC Science & Technology

1983-06-03

Defense, 10 June 1963), pp. 1-4. 3 Ibid. 4Automatic Data Processing Systems, Book - 1 Introduction (U.S. Army Signal School, Fort Monmouth, New Jersey, 15...January 1960) , passim. 5Automatic Data Processing Systems, Book - 2 Army Use of ADPS (U.S. Army Signal School, Fort Monmouth, New Jersey, 15 October...execute an application or utility program. It controls how the computer functions during a given operation. Utility programs are merely general use

[Evoked Potential Blind Extraction Based on Fractional Lower Order Spatial Time-Frequency Matrix].

PubMed

Long, Junbo; Wang, Haibin; Zha, Daifeng

2015-04-01

The impulsive electroencephalograph (EEG) noises in evoked potential (EP) signals is very strong, usually with a heavy tail and infinite variance characteristics like the acceleration noise impact, hypoxia and etc., as shown in other special tests. The noises can be described by a stable distribution model. In this paper, Wigner-Ville distribution (WVD) and pseudo Wigner-Ville distribution (PWVD) time-frequency distribution based on the fractional lower order moment are presented to be improved. We got fractional lower order WVD (FLO-WVD) and fractional lower order PWVD (FLO-PWVD) time-frequency distribution which could be suitable for a stable distribution process. We also proposed the fractional lower order spatial time-frequency distribution matrix (FLO-STFM) concept. Therefore, combining with time-frequency underdetermined blind source separation (TF-UBSS), we proposed a new fractional lower order spatial time-frequency underdetermined blind source separation (FLO-TF-UBSS) which can work in a stable distribution environment. We used the FLO-TF-UBSS algorithm to extract EPs. Simulations showed that the proposed method could effectively extract EPs in EEG noises, and the separated EPs and EEG signals based on FLO-TF-UBSS were almost the same as the original signal, but blind separation based on TF-UBSS had certain deviation. The correlation coefficient of the FLO-TF-UBSS algorithm was higher than the TF-UBSS algorithm when generalized signal-to-noise ratio (GSNR) changed from 10 dB to 30 dB and a varied from 1. 06 to 1. 94, and was approximately e- qual to 1. Hence, the proposed FLO-TF-UBSS method might be better than the TF-UBSS algorithm based on second order for extracting EP signal under an EEG noise environment.

Off-Grid Direction of Arrival Estimation Based on Joint Spatial Sparsity for Distributed Sparse Linear Arrays

PubMed Central

Liang, Yujie; Ying, Rendong; Lu, Zhenqi; Liu, Peilin

2014-01-01

In the design phase of sensor arrays during array signal processing, the estimation performance and system cost are largely determined by array aperture size. In this article, we address the problem of joint direction-of-arrival (DOA) estimation with distributed sparse linear arrays (SLAs) and propose an off-grid synchronous approach based on distributed compressed sensing to obtain larger array aperture. We focus on the complex source distribution in the practical applications and classify the sources into common and innovation parts according to whether a signal of source can impinge on all the SLAs or a specific one. For each SLA, we construct a corresponding virtual uniform linear array (ULA) to create the relationship of random linear map between the signals respectively observed by these two arrays. The signal ensembles including the common/innovation sources for different SLAs are abstracted as a joint spatial sparsity model. And we use the minimization of concatenated atomic norm via semidefinite programming to solve the problem of joint DOA estimation. Joint calculation of the signals observed by all the SLAs exploits their redundancy caused by the common sources and decreases the requirement of array size. The numerical results illustrate the advantages of the proposed approach. PMID:25420150

Quantum Electronic Solids

DTIC Science & Technology

2012-03-07

signal processing with smaller sizes and unique properties Nanoelectronics: NTs, graphene, diamond, SiC for sensing, logic & memory storage 3...synthesized i-n graphene heterojunctions 19 DISTRIBUTION A: Approved for public release; distribution is unlimited. Electrical Properties of...boundaries in polycrystalline samples Polycrystalline graphene can have similar (as much as 90%) electrical properties (conductance and mobility

lop-DWI: A Novel Scheme for Pre-Processing of Diffusion-Weighted Images in the Gradient Direction Domain.

PubMed

Sepehrband, Farshid; Choupan, Jeiran; Caruyer, Emmanuel; Kurniawan, Nyoman D; Gal, Yaniv; Tieng, Quang M; McMahon, Katie L; Vegh, Viktor; Reutens, David C; Yang, Zhengyi

2014-01-01

We describe and evaluate a pre-processing method based on a periodic spiral sampling of diffusion-gradient directions for high angular resolution diffusion magnetic resonance imaging. Our pre-processing method incorporates prior knowledge about the acquired diffusion-weighted signal, facilitating noise reduction. Periodic spiral sampling of gradient direction encodings results in an acquired signal in each voxel that is pseudo-periodic with characteristics that allow separation of low-frequency signal from high frequency noise. Consequently, it enhances local reconstruction of the orientation distribution function used to define fiber tracks in the brain. Denoising with periodic spiral sampling was tested using synthetic data and in vivo human brain images. The level of improvement in signal-to-noise ratio and in the accuracy of local reconstruction of fiber tracks was significantly improved using our method.

Smart signal processing for an evolving electric grid

NASA Astrophysics Data System (ADS)

Silva, Leandro Rodrigues Manso; Duque, Calos Augusto; Ribeiro, Paulo F.

2015-12-01

Electric grids are interconnected complex systems consisting of generation, transmission, distribution, and active loads, recently called prosumers as they produce and consume electric energy. Additionally, these encompass a vast array of equipment such as machines, power transformers, capacitor banks, power electronic devices, motors, etc. that are continuously evolving in their demand characteristics. Given these conditions, signal processing is becoming an essential assessment tool to enable the engineer and researcher to understand, plan, design, and operate the complex and smart electronic grid of the future. This paper focuses on recent developments associated with signal processing applied to power system analysis in terms of characterization and diagnostics. The following techniques are reviewed and their characteristics and applications discussed: active power system monitoring, sparse representation of power system signal, real-time resampling, and time-frequency (i.e., wavelets) applied to power fluctuations.

Cardiac Monitor

NASA Technical Reports Server (NTRS)

1996-01-01

Under contract to Johnson Space Center, the University of Minnesota developed the concept of impedance cardiography as an alternative to thermodilution to access astronaut heart function in flight. NASA then contracted Space Labs, Inc. to construct miniature space units based on this technology. Several companies then launched their own impedance cardiography, including Renaissance Technologies, which manufactures the IQ System. The IQ System is 5 to 17 times cheaper than thermodilution, and features the signal processing technology called TFD (Time Frequency Distribution). TFD provides three- dimensional distribution of the blood circulation force signals, allowing visualization of changes in power, frequency and time.

Randomized Hough transform filter for echo extraction in DLR

NASA Astrophysics Data System (ADS)

Liu, Tong; Chen, Hao; Shen, Ming; Gao, Pengqi; Zhao, You

2016-11-01

The signal-to-noise ratio (SNR) of debris laser ranging (DLR) data is extremely low, and the valid returns in the DLR range residuals are distributed on a curve in a long observation time. Therefore, it is hard to extract the signals from noise in the Observed-minus-Calculated (O-C) residuals with low SNR. In order to autonomously extract the valid returns, we propose a new algorithm based on randomized Hough transform (RHT). We firstly pre-process the data using histogram method to find the zonal area that contains all the possible signals to reduce large amount of noise. Then the data is processed with RHT algorithm to find the curve that the signal points are distributed on. A new parameter update strategy is introduced in the RHT to get the best parameters. We also analyze the values of the parameters in the algorithm. We test our algorithm on the 10 Hz repetition rate DLR data from Yunnan Observatory and 100 Hz repetition rate DLR data from Graz SLR station. For 10 Hz DLR data with relative larger and similar range gate, we can process it in real time and extract all the signals autonomously with a few false readings. For 100 Hz DLR data with longer observation time, we autonomously post-process DLR data of 0.9%, 2.7%, 8% and 33% return rate with high reliability. The extracted points contain almost all signals and a low percentage of noise. Additional noise is added to 10 Hz DLR data to get lower return rate data. The valid returns can also be well extracted for DLR data with 0.18% and 0.1% return rate.

Lung Parenchymal Signal Intensity in MRI: A Technical Review with Educational Aspirations Regarding Reversible Versus Irreversible Transverse Relaxation Effects in Common Pulse Sequences.

PubMed

Mulkern, Robert; Haker, Steven; Mamata, Hatsuho; Lee, Edward; Mitsouras, Dimitrios; Oshio, Koichi; Balasubramanian, Mukund; Hatabu, Hiroto

2014-03-01

Lung parenchyma is challenging to image with proton MRI. The large air space results in ~l/5th as many signal-generating protons compared to other organs. Air/tissue magnetic susceptibility differences lead to strong magnetic field gradients throughout the lungs and to broad frequency distributions, much broader than within other organs. Such distributions have been the subject of experimental and theoretical analyses which may reveal aspects of lung microarchitecture useful for diagnosis. Their most immediate relevance to current imaging practice is to cause rapid signal decays, commonly discussed in terms of short T 2 * values of 1 ms or lower at typical imaging field strengths. Herein we provide a brief review of previous studies describing and interpreting proton lung spectra. We then link these broad frequency distributions to rapid signal decays, though not necessarily the exponential decays generally used to define T 2 * values. We examine how these decays influence observed signal intensities and spatial mapping features associated with the most prominent torso imaging sequences, including spoiled gradient and spin echo sequences. Effects of imperfect refocusing pulses on the multiple echo signal decays in single shot fast spin echo (SSFSE) sequences and effects of broad frequency distributions on balanced steady state free precession (bSSFP) sequence signal intensities are also provided. The theoretical analyses are based on the concept of explicitly separating the effects of reversible and irreversible transverse relaxation processes, thus providing a somewhat novel and more general framework from which to estimate lung signal intensity behavior in modern imaging practice.

Lung Parenchymal Signal Intensity in MRI: A Technical Review with Educational Aspirations Regarding Reversible Versus Irreversible Transverse Relaxation Effects in Common Pulse Sequences

PubMed Central

MULKERN, ROBERT; HAKER, STEVEN; MAMATA, HATSUHO; LEE, EDWARD; MITSOURAS, DIMITRIOS; OSHIO, KOICHI; BALASUBRAMANIAN, MUKUND; HATABU, HIROTO

2014-01-01

Lung parenchyma is challenging to image with proton MRI. The large air space results in ~l/5th as many signal-generating protons compared to other organs. Air/tissue magnetic susceptibility differences lead to strong magnetic field gradients throughout the lungs and to broad frequency distributions, much broader than within other organs. Such distributions have been the subject of experimental and theoretical analyses which may reveal aspects of lung microarchitecture useful for diagnosis. Their most immediate relevance to current imaging practice is to cause rapid signal decays, commonly discussed in terms of short T2* values of 1 ms or lower at typical imaging field strengths. Herein we provide a brief review of previous studies describing and interpreting proton lung spectra. We then link these broad frequency distributions to rapid signal decays, though not necessarily the exponential decays generally used to define T2* values. We examine how these decays influence observed signal intensities and spatial mapping features associated with the most prominent torso imaging sequences, including spoiled gradient and spin echo sequences. Effects of imperfect refocusing pulses on the multiple echo signal decays in single shot fast spin echo (SSFSE) sequences and effects of broad frequency distributions on balanced steady state free precession (bSSFP) sequence signal intensities are also provided. The theoretical analyses are based on the concept of explicitly separating the effects of reversible and irreversible transverse relaxation processes, thus providing a somewhat novel and more general framework from which to estimate lung signal intensity behavior in modern imaging practice. PMID:25228852

Preface to the special issue on "Integrated Microwave Photonic Signal Processing"

NASA Astrophysics Data System (ADS)

Azaña, José; Yao, Jianping

2016-08-01

As Guest Editors, we are pleased to introduce this special issue on ;Integrated Microwave Photonic Signal Processing; published by the Elsevier journal Optics Communications. Microwave photonics is a field of growing importance from both scientific and practical application perspectives. The field of microwave photonics is devoted to the study, development and application of optics-based techniques and technologies aimed to the generation, processing, control, characterization and/or distribution of microwave signals, including signals well into the millimeter-wave frequency range. The use of photonic technologies for these microwave applications translates into a number of key advantages, such as the possibility of dealing with high-frequency, wide bandwidth signals with minimal losses and reduced electromagnetic interferences, and the potential for enhanced reconfigurability. The central purpose of this special issue is to provide an overview of the state of the art of generation, processing and characterization technologies for high-frequency microwave signals. It is now widely accepted that the practical success of microwave photonics at a large scale will essentially depend on the realization of high-performance microwave-photonic signal-processing engines in compact and integrated formats, preferably on a chip. Thus, the focus of the issue is on techniques implemented using integrated photonic technologies, with the goal of providing an update of the most recent advances toward realization of this vision.

Probabilistic n/γ discrimination with robustness against outliers for use in neutron profile monitors

NASA Astrophysics Data System (ADS)

Uchida, Y.; Takada, E.; Fujisaki, A.; Kikuchi, T.; Ogawa, K.; Isobe, M.

2017-08-01

A method to stochastically discriminate neutron and γ-ray signals measured with a stilbene organic scintillator is proposed. Each pulse signal was stochastically categorized into two groups: neutron and γ-ray. In previous work, the Expectation Maximization (EM) algorithm was used with the assumption that the measured data followed a Gaussian mixture distribution. It was shown that probabilistic discrimination between these groups is possible. Moreover, by setting the initial parameters for the Gaussian mixture distribution with a k-means algorithm, the possibility of automatic discrimination was demonstrated. In this study, the Student's t-mixture distribution was used as a probabilistic distribution with the EM algorithm to improve the robustness against the effect of outliers caused by pileup of the signals. To validate the proposed method, the figures of merit (FOMs) were compared for the EM algorithm assuming a t-mixture distribution and a Gaussian mixture distribution. The t-mixture distribution resulted in an improvement of the FOMs compared with the Gaussian mixture distribution. The proposed data processing technique is a promising tool not only for neutron and γ-ray discrimination in fusion experiments but also in other fields, for example, homeland security, cancer therapy with high energy particles, nuclear reactor decommissioning, pattern recognition, and so on.

Time-varying higher order spectra

NASA Astrophysics Data System (ADS)

Boashash, Boualem; O'Shea, Peter

1991-12-01

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

Acoustic Source Localization via Time Difference of Arrival Estimation for Distributed Sensor Networks Using Tera-Scale Optical Core Devices

DOE PAGES

Imam, Neena; Barhen, Jacob

2009-01-01

For real-time acoustic source localization applications, one of the primary challenges is the considerable growth in computational complexity associated with the emergence of ever larger, active or passive, distributed sensor networks. These sensors rely heavily on battery-operated system components to achieve highly functional automation in signal and information processing. In order to keep communication requirements minimal, it is desirable to perform as much processing on the receiver platforms as possible. However, the complexity of the calculations needed to achieve accurate source localization increases dramatically with the size of sensor arrays, resulting in substantial growth of computational requirements that cannot bemore » readily met with standard hardware. One option to meet this challenge builds upon the emergence of digital optical-core devices. The objective of this work was to explore the implementation of key building block algorithms used in underwater source localization on the optical-core digital processing platform recently introduced by Lenslet Inc. This demonstration of considerably faster signal processing capability should be of substantial significance to the design and innovation of future generations of distributed sensor networks.« less

Implication of high dynamic range and wide color gamut content distribution

NASA Astrophysics Data System (ADS)

Lu, Taoran; Pu, Fangjun; Yin, Peng; Chen, Tao; Husak, Walt

2015-09-01

High Dynamic Range (HDR) and Wider Color Gamut (WCG) content represents a greater range of luminance levels and a more complete reproduction of colors found in real-world scenes. The current video distribution environments deliver Standard Dynamic Range (SDR) signal. Therefore, there might be some significant implication on today's end-to-end ecosystem from content creation to distribution and finally to consumption. For SDR content, the common practice is to apply compression on Y'CbCr 4:2:0 using gamma transfer function and non-constant luminance 4:2:0 chroma subsampling. For HDR and WCG content, it is desirable to examine if such signal format still works well for compression, and it is interesting to know if the overall system performance can be further improved by exploring different signal formats and processing workflows. In this paper, we will provide some of our insight into those problems.

See-through Detection and 3D Reconstruction Using Terahertz Leaky-Wave Radar Based on Sparse Signal Processing

NASA Astrophysics Data System (ADS)

Murata, Koji; Murano, Kosuke; Watanabe, Issei; Kasamatsu, Akifumi; Tanaka, Toshiyuki; Monnai, Yasuaki

2018-02-01

We experimentally demonstrate see-through detection and 3D reconstruction using terahertz leaky-wave radar based on sparse signal processing. The application of terahertz waves to radar has received increasing attention in recent years for its potential to high-resolution and see-through detection. Among others, the implementation using a leaky-wave antenna is promising for compact system integration with beam steering capability based on frequency sweep. However, the use of a leaky-wave antenna poses a challenge on signal processing. Since a leaky-wave antenna combines the entire signal captured by each part of the aperture into a single output, the conventional array signal processing assuming access to a respective antenna element is not applicable. In this paper, we apply an iterative recovery algorithm "CoSaMP" to signals acquired with terahertz leaky-wave radar for clutter mitigation and aperture synthesis. We firstly demonstrate see-through detection of target location even when the radar is covered with an opaque screen, and therefore, the radar signal is disturbed by clutter. Furthermore, leveraging the robustness of the algorithm against noise, we also demonstrate 3D reconstruction of distributed targets by synthesizing signals collected from different orientations. The proposed approach will contribute to the smart implementation of terahertz leaky-wave radar.

WAMS measurements pre-processing for detecting low-frequency oscillations in power systems

NASA Astrophysics Data System (ADS)

Kovalenko, P. Y.

2017-07-01

Processing the data received from measurement systems implies the situation when one or more registered values stand apart from the sample collection. These values are referred to as “outliers”. The processing results may be influenced significantly by the presence of those in the data sample under consideration. In order to ensure the accuracy of low-frequency oscillations detection in power systems the corresponding algorithm has been developed for the outliers detection and elimination. The algorithm is based on the concept of the irregular component of measurement signal. This component comprises measurement errors and is assumed to be Gauss-distributed random. The median filtering is employed to detect the values lying outside the range of the normally distributed measurement error on the basis of a 3σ criterion. The algorithm has been validated involving simulated signals and WAMS data as well.

Humic Substances: Determining Potential Molecular Regulatory Processes in Plants

PubMed Central

Shah, Zahid Hussain; Rehman, Hafiz M.; Akhtar, Tasneem; Alsamadany, Hameed; Hamooh, Bahget T.; Mujtaba, Tahir; Daur, Ihsanullah; Al Zahrani, Yahya; Alzahrani, Hind A. S.; Ali, Shawkat; Yang, Seung H.; Chung, Gyuhwa

2018-01-01

Humic substances (HSs) have considerable effects on soil fertility and crop productivity owing to their unique physiochemical and biochemical properties, and play a vital role in establishing biotic and abiotic interactions within the plant rhizosphere. A comprehensive understanding of the mode of action and tissue distribution of HS is, however, required, as this knowledge could be useful for devising advanced rhizospheric management practices. These substances trigger various molecular processes in plant cells, and can strengthen the plant’s tolerance to various kinds of abiotic stresses. HS manifest their effects in cells through genetic, post-transcriptional, and post-translational modifications of signaling entities that trigger different molecular, biochemical, and physiological processes. Understanding of such fundamental mechanisms will provide a better perspective for defining the cues and signaling crosstalk of HS that mediate various metabolic and hormonal networks operating in plant systems. Various regulatory activities and distribution strategies of HS have been discussed in this review. PMID:29593751

Detecting blast-induced infrasound in wind noise.

PubMed

Howard, Wheeler B; Dillion, Kevin L; Shields, F Douglas

2010-03-01

Current efforts seek to monitor and investigate such naturally occurring events as volcanic eruptions, hurricanes, bolides entering the atmosphere, earthquakes, and tsunamis by the infrasound they generate. Often, detection of the infrasound signal is limited by the masking effect of wind noise. This paper describes the use of a distributed array to detect infrasound signals from four atmospheric detonations at White Sands Missile Range in New Mexico, USA in 2006. Three of the blasts occurred during times of low wind noise and were easily observed with array processing techniques. One blast was obscured by high wind conditions. The results of signal processing are presented that allowed localization of the blast-induced signals in the presence of wind noise in the array response.

A Distributed Compressive Sensing Scheme for Event Capture in Wireless Visual Sensor Networks

NASA Astrophysics Data System (ADS)

Hou, Meng; Xu, Sen; Wu, Weiling; Lin, Fei

2018-01-01

Image signals which acquired by wireless visual sensor network can be used for specific event capture. This event capture is realized by image processing at the sink node. A distributed compressive sensing scheme is used for the transmission of these image signals from the camera nodes to the sink node. A measurement and joint reconstruction algorithm for these image signals are proposed in this paper. Make advantage of spatial correlation between images within a sensing area, the cluster head node which as the image decoder can accurately co-reconstruct these image signals. The subjective visual quality and the reconstruction error rate are used for the evaluation of reconstructed image quality. Simulation results show that the joint reconstruction algorithm achieves higher image quality at the same image compressive rate than the independent reconstruction algorithm.

Nuclear test ban treaty verification: Improving test ban monitoring with empirical and model-based signal processing

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

Harris, David B.; Gibbons, Steven J.; Rodgers, Arthur J.

In this approach, small scale-length medium perturbations not modeled in the tomographic inversion might be described as random fields, characterized by particular distribution functions (e.g., normal with specified spatial covariance). Conceivably, random field parameters (scatterer density or scale length) might themselves be the targets of tomographic inversions of the scattered wave field. As a result, such augmented models may provide processing gain through the use of probabilistic signal sub spaces rather than deterministic waveforms.

Nuclear test ban treaty verification: Improving test ban monitoring with empirical and model-based signal processing

DOE PAGES

Harris, David B.; Gibbons, Steven J.; Rodgers, Arthur J.; ...

2012-05-01

In this approach, small scale-length medium perturbations not modeled in the tomographic inversion might be described as random fields, characterized by particular distribution functions (e.g., normal with specified spatial covariance). Conceivably, random field parameters (scatterer density or scale length) might themselves be the targets of tomographic inversions of the scattered wave field. As a result, such augmented models may provide processing gain through the use of probabilistic signal sub spaces rather than deterministic waveforms.

Control of Networked Traffic Flow Distribution - A Stochastic Distribution System Perspective

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

Wang, Hong; Aziz, H M Abdul; Young, Stan

Networked traffic flow is a common scenario for urban transportation, where the distribution of vehicle queues either at controlled intersections or highway segments reflect the smoothness of the traffic flow in the network. At signalized intersections, the traffic queues are controlled by traffic signal control settings and effective traffic lights control would realize both smooth traffic flow and minimize fuel consumption. Funded by the Energy Efficient Mobility Systems (EEMS) program of the Vehicle Technologies Office of the US Department of Energy, we performed a preliminary investigation on the modelling and control framework in context of urban network of signalized intersections.more » In specific, we developed a recursive input-output traffic queueing models. The queue formation can be modeled as a stochastic process where the number of vehicles entering each intersection is a random number. Further, we proposed a preliminary B-Spline stochastic model for a one-way single-lane corridor traffic system based on theory of stochastic distribution control.. It has been shown that the developed stochastic model would provide the optimal probability density function (PDF) of the traffic queueing length as a dynamic function of the traffic signal setting parameters. Based upon such a stochastic distribution model, we have proposed a preliminary closed loop framework on stochastic distribution control for the traffic queueing system to make the traffic queueing length PDF follow a target PDF that potentially realizes the smooth traffic flow distribution in a concerned corridor.« less

pySPACE—a signal processing and classification environment in Python

PubMed Central

Krell, Mario M.; Straube, Sirko; Seeland, Anett; Wöhrle, Hendrik; Teiwes, Johannes; Metzen, Jan H.; Kirchner, Elsa A.; Kirchner, Frank

2013-01-01

In neuroscience large amounts of data are recorded to provide insights into cerebral information processing and function. The successful extraction of the relevant signals becomes more and more challenging due to increasing complexities in acquisition techniques and questions addressed. Here, automated signal processing and machine learning tools can help to process the data, e.g., to separate signal and noise. With the presented software pySPACE (http://pyspace.github.io/pyspace), signal processing algorithms can be compared and applied automatically on time series data, either with the aim of finding a suitable preprocessing, or of training supervised algorithms to classify the data. pySPACE originally has been built to process multi-sensor windowed time series data, like event-related potentials from the electroencephalogram (EEG). The software provides automated data handling, distributed processing, modular build-up of signal processing chains and tools for visualization and performance evaluation. Included in the software are various algorithms like temporal and spatial filters, feature generation and selection, classification algorithms, and evaluation schemes. Further, interfaces to other signal processing tools are provided and, since pySPACE is a modular framework, it can be extended with new algorithms according to individual needs. In the presented work, the structural hierarchies are described. It is illustrated how users and developers can interface the software and execute offline and online modes. Configuration of pySPACE is realized with the YAML format, so that programming skills are not mandatory for usage. The concept of pySPACE is to have one comprehensive tool that can be used to perform complete signal processing and classification tasks. It further allows to define own algorithms, or to integrate and use already existing libraries. PMID:24399965

pySPACE-a signal processing and classification environment in Python.

PubMed

Krell, Mario M; Straube, Sirko; Seeland, Anett; Wöhrle, Hendrik; Teiwes, Johannes; Metzen, Jan H; Kirchner, Elsa A; Kirchner, Frank

2013-01-01

In neuroscience large amounts of data are recorded to provide insights into cerebral information processing and function. The successful extraction of the relevant signals becomes more and more challenging due to increasing complexities in acquisition techniques and questions addressed. Here, automated signal processing and machine learning tools can help to process the data, e.g., to separate signal and noise. With the presented software pySPACE (http://pyspace.github.io/pyspace), signal processing algorithms can be compared and applied automatically on time series data, either with the aim of finding a suitable preprocessing, or of training supervised algorithms to classify the data. pySPACE originally has been built to process multi-sensor windowed time series data, like event-related potentials from the electroencephalogram (EEG). The software provides automated data handling, distributed processing, modular build-up of signal processing chains and tools for visualization and performance evaluation. Included in the software are various algorithms like temporal and spatial filters, feature generation and selection, classification algorithms, and evaluation schemes. Further, interfaces to other signal processing tools are provided and, since pySPACE is a modular framework, it can be extended with new algorithms according to individual needs. In the presented work, the structural hierarchies are described. It is illustrated how users and developers can interface the software and execute offline and online modes. Configuration of pySPACE is realized with the YAML format, so that programming skills are not mandatory for usage. The concept of pySPACE is to have one comprehensive tool that can be used to perform complete signal processing and classification tasks. It further allows to define own algorithms, or to integrate and use already existing libraries.

An Overview Of Wideband Signal Analysis Techniques

NASA Astrophysics Data System (ADS)

Speiser, Jeffrey M.; Whitehouse, Harper J.

1989-11-01

This paper provides a unifying perspective for several narowband and wideband signal processing techniques. It considers narrowband ambiguity functions and Wigner-Ville distibutions, together with the wideband ambiguity function and several proposed approaches to a wideband version of the Wigner-Ville distribution (WVD). A unifying perspective is provided by the methodology of unitary representations and ray representations of transformation groups.

Improved Target Detection in Urban Structures Using Distributed Sensing and Fast Data Acquisition Techniques

DTIC Science & Technology

2013-04-01

Trans. Signal Process., vol. 57, no. 6, pp. 2275-2284, 2009. [83] A. Gurbuz, J. IVIcClellan, and W. Scott, "Compressive sensing for subsurface ... imaging using ground penetrating radar," Signal Pracess., vol. 89, no. 10, pp. 1959 -1972, 2009. [84] A. Gurbuz, J. McClellan, and W. Scott, "A

Typical effects of laser dazzling CCD camera

NASA Astrophysics Data System (ADS)

Zhang, Zhen; Zhang, Jianmin; Shao, Bibo; Cheng, Deyan; Ye, Xisheng; Feng, Guobin

2015-05-01

In this article, an overview of laser dazzling effect to buried channel CCD camera is given. The CCDs are sorted into staring and scanning types. The former includes the frame transfer and interline transfer types. The latter includes linear and time delay integration types. All CCDs must perform four primary tasks in generating an image, which are called charge generation, charge collection, charge transfer and charge measurement. In camera, the lenses are needed to input the optical signal to the CCD sensors, in which the techniques for erasing stray light are used. And the electron circuits are needed to process the output signal of CCD, in which many electronic techniques are used. The dazzling effects are the conjunct result of light distribution distortion and charge distribution distortion, which respectively derive from the lens and the sensor. Strictly speaking, in lens, the light distribution is not distorted. In general, the lens are so well designed and fabricated that its stray light can be neglected. But the laser is of much enough intensity to make its stray light obvious. In CCD image sensors, laser can induce a so large electrons generation. Charges transfer inefficiency and charges blooming will cause the distortion of the charge distribution. Commonly, the largest signal outputted from CCD sensor is restricted by capability of the collection well of CCD, and can't go beyond the dynamic range for the subsequent electron circuits maintaining normal work. So the signal is not distorted in the post-processing circuits. But some techniques in the circuit can make some dazzling effects present different phenomenon in final image.

A robust nonlinear filter for image restoration.

PubMed

Koivunen, V

1995-01-01

A class of nonlinear regression filters based on robust estimation theory is introduced. The goal of the filtering is to recover a high-quality image from degraded observations. Models for desired image structures and contaminating processes are employed, but deviations from strict assumptions are allowed since the assumptions on signal and noise are typically only approximately true. The robustness of filters is usually addressed only in a distributional sense, i.e., the actual error distribution deviates from the nominal one. In this paper, the robustness is considered in a broad sense since the outliers may also be due to inappropriate signal model, or there may be more than one statistical population present in the processing window, causing biased estimates. Two filtering algorithms minimizing a least trimmed squares criterion are provided. The design of the filters is simple since no scale parameters or context-dependent threshold values are required. Experimental results using both real and simulated data are presented. The filters effectively attenuate both impulsive and nonimpulsive noise while recovering the signal structure and preserving interesting details.

Stability evaluation of short-circuiting gas metal arc welding based on ensemble empirical mode decomposition

NASA Astrophysics Data System (ADS)

Huang, Yong; Wang, Kehong; Zhou, Zhilan; Zhou, Xiaoxiao; Fang, Jimi

2017-03-01

The arc of gas metal arc welding (GMAW) contains abundant information about its stability and droplet transition, which can be effectively characterized by extracting the arc electrical signals. In this study, ensemble empirical mode decomposition (EEMD) was used to evaluate the stability of electrical current signals. The welding electrical signals were first decomposed by EEMD, and then transformed to a Hilbert-Huang spectrum and a marginal spectrum. The marginal spectrum is an approximate distribution of amplitude with frequency of signals, and can be described by a marginal index. Analysis of various welding process parameters showed that the marginal index of current signals increased when the welding process was more stable, and vice versa. Thus EEMD combined with the marginal index can effectively uncover the stability and droplet transition of GMAW.

Double Fourier analysis for Emotion Identification in Voiced Speech

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

OPTICAL INFORMATION PROCESSING: Modulation—spectral analysis of an image transmitted across a distorting medium

NASA Astrophysics Data System (ADS)

Zubov, Vladimir A.; Mironova, T. V.

1998-05-01

The task of simultaneous determination of the structure and characteristics of a two-dimensional amplitude—phase signal and a two-dimensional complex transfer or instrumental function is considered. The solution is based on determination of four independent intensity distributions of spectral representations of the signal Isr(ωx, ωy) subjected to the action of the transfer function, of the signal Ismr(ωx, ωy which) has experienced additional modulation applied in a certain manner and the action of the transfer function, of the signal Isrn(ωx, ωy) representing the signal Isr(ωx, ωy) with certain additional modulation at the output, and of the signal Ismrn(ωx, ωy) which is the signal Ismr(ωx, ωy) with certain additional modulation at the output. These intensity distributions make it possible to calculate the amplitude and phase components of the image being analysed and of the transfer function. Additional modulations should in some way ensure visualisation of the phase information. A specific type of additional spatial modulation, in the form of linear amplitude, is discussed.

Incorporating reversible and irreversible transverse relaxation effects into Steady State Free Precession (SSFP) signal intensity expressions for fMRI considerations.

PubMed

Mulkern, Robert V; Balasubramanian, Mukund; Orbach, Darren B; Mitsouras, Dimitrios; Haker, Steven J

2013-04-01

Among the multiple sequences available for functional magnetic resonance imaging (fMRI), the Steady State Free Precession (SSFP) sequence offers the highest signal-to-noise ratio (SNR) per unit time as well as distortion free images not feasible with the more commonly employed single-shot echo planar imaging (EPI) approaches. Signal changes occurring with activation in SSFP sequences reflect underlying changes in both irreversible and reversible transverse relaxation processes. The latter are characterized by changes in the central frequencies and widths of the inherent frequency distribution present within a voxel. In this work, the well-known frequency response of the SSFP signal intensity is generalized to include the widths and central frequencies of some common frequency distributions on SSFP signal intensities. The approach, using a previously unnoted series expansion, allows for a separation of reversible from irreversible transverse relaxation effects on SSFP signal intensity changes. The formalism described here should prove useful for identifying and modeling mechanisms associated with SSFP signal changes accompanying neural activation. Copyright © 2013 Elsevier Inc. All rights reserved.

Spin-Off Successes of SETI Research at Berkeley

NASA Astrophysics Data System (ADS)

Douglas, K. A.; Anderson, D. P.; Bankay, R.; Chen, H.; Cobb, J.; Korpela, E. J.; Lebofsky, M.; Parsons, A.; von Korff, J.; Werthimer, D.

2009-12-01

Our group contributes to the Search for Extra-Terrestrial Intelligence (SETI) by developing and using world-class signal processing computers to analyze data collected on the Arecibo telescope. Although no patterned signal of extra-terrestrial origin has yet been detected, and the immediate prospects for making such a detection are highly uncertain, the SETI@home project has nonetheless proven the value of pursuing such research through its impact on the fields of distributed computing, real-time signal processing, and radio astronomy. The SETI@home project has spun off the Center for Astronomy Signal Processing and Electronics Research (CASPER) and the Berkeley Open Infrastructure for Networked Computing (BOINC), both of which are responsible for catalyzing a smorgasbord of new research in scientific disciplines in countries around the world. Futhermore, the data collected and archived for the SETI@home project is proving valuable in data-mining experiments for mapping neutral galatic hydrogen and for detecting black-hole evaporation.

Algorithms and Results of Eye Tissues Differentiation Based on RF Ultrasound

PubMed Central

Jurkonis, R.; Janušauskas, A.; Marozas, V.; Jegelevičius, D.; Daukantas, S.; Patašius, M.; Paunksnis, A.; Lukoševičius, A.

2012-01-01

Algorithms and software were developed for analysis of B-scan ultrasonic signals acquired from commercial diagnostic ultrasound system. The algorithms process raw ultrasonic signals in backscattered spectrum domain, which is obtained using two time-frequency methods: short-time Fourier and Hilbert-Huang transformations. The signals from selected regions of eye tissues are characterized by parameters: B-scan envelope amplitude, approximated spectral slope, approximated spectral intercept, mean instantaneous frequency, mean instantaneous bandwidth, and parameters of Nakagami distribution characterizing Hilbert-Huang transformation output. The backscattered ultrasound signal parameters characterizing intraocular and orbit tissues were processed by decision tree data mining algorithm. The pilot trial proved that applied methods are able to correctly classify signals from corpus vitreum blood, extraocular muscle, and orbit tissues. In 26 cases of ocular tissues classification, one error occurred, when tissues were classified into classes of corpus vitreum blood, extraocular muscle, and orbit tissue. In this pilot classification parameters of spectral intercept and Nakagami parameter for instantaneous frequencies distribution of the 1st intrinsic mode function were found specific for corpus vitreum blood, orbit and extraocular muscle tissues. We conclude that ultrasound data should be further collected in clinical database to establish background for decision support system for ocular tissue noninvasive differentiation. PMID:22654643

Neural Networks Applied to Signal Processing

DTIC Science & Technology

1989-09-01

Distributed Processing, The MIT Press, Cambridge, MA, 1988. 3. Marvin Minsky and Seymour Papert, Perceptrons, The MIT Press, Cambridge, MA, 1969. 4...signum function, the linear function, and the sigmoid function. Initial research conducted in the 1950’s and 1960’s by Rosenblat, Minsky and others used

Squeezed-state quantum key distribution with a Rindler observer

NASA Astrophysics Data System (ADS)

Zhou, Jian; Shi, Ronghua; Guo, Ying

2018-03-01

Lengthening the maximum transmission distance of quantum key distribution plays a vital role in quantum information processing. In this paper, we propose a directional squeezed-state protocol with signals detected by a Rindler observer in the relativistic quantum field framework. We derive an analytical solution to the transmission problem of squeezed states from the inertial sender to the accelerated receiver. The variance of the involved signal mode is closer to optimality than that of the coherent-state-based protocol. Simulation results show that the proposed protocol has better performance than the coherent-state counterpart especially in terms of the maximal transmission distance.

Storage filters upland suspended sediment signals delivered from watersheds

USGS Publications Warehouse

Pizzuto, James E.; Keeler, Jeremy; Skalak, Katherine; Karwan, Diana

2017-01-01

Climate change, tectonics, and humans create long- and short-term temporal variations in the supply of suspended sediment to rivers. These signals, generated in upland erosional areas, are filtered by alluvial storage before reaching the basin outlet. We quantified this filter using a random walk model driven by sediment budget data, a power-law distributed probability density function (PDF) to determine how long sediment remains stored, and a constant downstream drift velocity during transport of 157 km/yr. For 25 km of transport, few particles are stored, and the median travel time is 0.2 yr. For 1000 km of transport, nearly all particles are stored, and the median travel time is 2.5 m.y. Both travel-time distributions are power laws. The 1000 km travel-time distribution was then used to filter sinusoidal input signals with periods of 10 yr and 104 yr. The 10 yr signal is delayed by 12.5 times its input period, damped by a factor of 380, and is output as a power law. The 104 yr signal is delayed by 0.15 times its input period, damped by a factor of 3, and the output signal retains its sinusoidal input form (but with a power-law “tail”). Delivery time scales for these two signals are controlled by storage; in-channel transport time is insignificant, and low-frequency signals are transmitted with greater fidelity than high-frequency signals. These signal modifications are essential to consider when evaluating watershed restoration schemes designed to control sediment loading, and where source-area geomorphic processes are inferred from the geologic record.

Simulation of energy spectrum of GEM detector from an x-ray quantum

NASA Astrophysics Data System (ADS)

Malinowski, K.; Chernyshova, M.; Czarski, T.; Kowalska-Strzęciwilk, E.; Linczuk, P.; Wojeński, A.; Krawczyk, R.; Gąska, M.

2018-01-01

This paper presents the results of the energy resolution simulation for the triple GEM-based detector for x-ray quantum of 5.9 keV . Photons of this energy are emitted by 55Fe source, which is a standard calibration marker for this type of detectors. The calculations were made in Garfield++ in two stages. In the first stage, the distribution of the amount of primary electrons generated in the drift volume by the x-ray quantum was simulated using the Heed program. Secondly, the primary electrons of the resulting quantitative distribution were treated as a source of electron avalanches propagated through the whole volume of the triple GEM-based detector. The distribution of the obtained signals created a spectrum corresponding to the peak at 5.9 keV, which allowed us to determine the theoretical energy resolution of the detector. Its knowledge allows observing and improving the eventual experimental deterioration of the energy resolution, inevitably accompanying processes of registration and processing of the signals.

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.

Characterization of the Ionospheric Scintillations at High Latitude using GPS Signal

NASA Astrophysics Data System (ADS)

Mezaoui, H.; Hamza, A. M.; Jayachandran, P. T.

2013-12-01

Transionospheric radio signals experience both amplitude and phase variations as a result of propagation through a turbulent ionosphere; this phenomenon is known as ionospheric scintillations. As a result of these fluctuations, Global Positioning System (GPS) receivers lose track of signals and consequently induce position and navigational errors. Therefore, there is a need to study these scintillations and their causes in order to not only resolve the navigational problem but in addition develop analytical and numerical radio propagation models. In order to quantify and qualify these scintillations, we analyze the probability distribution functions (PDFs) of L1 GPS signals at 50 Hz sampling rate using the Canadian High arctic Ionospheric Network (CHAIN) measurements. The raw GPS signal is detrended using a wavelet-based technique and the detrended amplitude and phase of the signal are used to construct probability distribution functions (PDFs) of the scintillating signal. The resulting PDFs are non-Gaussian. From the PDF functional fits, the moments are estimated. The results reveal a general non-trivial parabolic relationship between the normalized fourth and third moments for both the phase and amplitude of the signal. The calculated higher-order moments of the amplitude and phase distribution functions will help quantify some of the scintillation characteristics and in the process provide a base for forecasting, i.e. develop a scintillation climatology model. This statistical analysis, including power spectra, along with a numerical simulation will constitute the backbone of a high latitude scintillation model.

Stabilization of Phase of a Sinusoidal Signal Transmitted Over Optical Fiber

NASA Technical Reports Server (NTRS)

DAddario, Larry R.; Trink, Joseph T.

2010-01-01

In the process of connecting widely distributed antennas into a coherent array, it is necessary to synchronize the timing of signals at the various locations. This can be accomplished by distributing a common reference signal from a central source, usually over optical fiber. A high-frequency (RF or microwave) tone is a good choice for the reference. One difficulty is that the effective length of the optical fiber changes with temperature and mechanical stress, leading to phase instability in the received tone. This innovation provides a new way to stabilize the phase of the received tone, in spite of variations in the electrical length of the fiber. Stabilization is accomplished by two-way transmission in which part of the received signal is returned to the transmitting end over an identical fiber. The returned signal is detected and used to close an electrical servo loop whose effect is to keep constant the phase of the tone at the receiving end.

Coherent Frequency Reference System for the NASA Deep Space Network

NASA Technical Reports Server (NTRS)

Tucker, Blake C.; Lauf, John E.; Hamell, Robert L.; Gonzaler, Jorge, Jr.; Diener, William A.; Tjoelker, Robert L.

2010-01-01

The NASA Deep Space Network (DSN) requires state-of-the-art frequency references that are derived and distributed from very stable atomic frequency standards. A new Frequency Reference System (FRS) and Frequency Reference Distribution System (FRD) have been developed, which together replace the previous Coherent Reference Generator System (CRG). The FRS and FRD each provide new capabilities that significantly improve operability and reliability. The FRS allows for selection and switching between frequency standards, a flywheel capability (to avoid interruptions when switching frequency standards), and a frequency synthesis system (to generate standardized 5-, 10-, and 100-MHz reference signals). The FRS is powered by redundant, specially filtered, and sustainable power systems and includes a monitor and control capability for station operations to interact and control the frequency-standard selection process. The FRD receives the standardized 5-, 10-, and 100-MHz reference signals and distributes signals to distribution amplifiers in a fan out fashion to dozens of DSN users that require the highly stable reference signals. The FRD is also powered by redundant, specially filtered, and sustainable power systems. The new DSN Frequency Distribution System, which consists of the FRS and FRD systems described here, is central to all operational activities of the NASA DSN. The frequency generation and distribution system provides ultra-stable, coherent, and very low phase-noise references at 5, l0, and 100 MHz to between 60 and 100 separate users at each Deep Space Communications Complex.

Signal Processing in Periodically Forced Gradient Frequency Neural Networks

PubMed Central

Kim, Ji Chul; Large, Edward W.

2015-01-01

Oscillatory instability at the Hopf bifurcation is a dynamical phenomenon that has been suggested to characterize active non-linear processes observed in the auditory system. Networks of oscillators poised near Hopf bifurcation points and tuned to tonotopically distributed frequencies have been used as models of auditory processing at various levels, but systematic investigation of the dynamical properties of such oscillatory networks is still lacking. Here we provide a dynamical systems analysis of a canonical model for gradient frequency neural networks driven by a periodic signal. We use linear stability analysis to identify various driven behaviors of canonical oscillators for all possible ranges of model and forcing parameters. The analysis shows that canonical oscillators exhibit qualitatively different sets of driven states and transitions for different regimes of model parameters. We classify the parameter regimes into four main categories based on their distinct signal processing capabilities. This analysis will lead to deeper understanding of the diverse behaviors of neural systems under periodic forcing and can inform the design of oscillatory network models of auditory signal processing. PMID:26733858

Detecting determinism with improved sensitivity in time series: rank-based nonlinear predictability score.

PubMed

Naro, Daniel; Rummel, Christian; Schindler, Kaspar; Andrzejak, Ralph G

2014-09-01

The rank-based nonlinear predictability score was recently introduced as a test for determinism in point processes. We here adapt this measure to time series sampled from time-continuous flows. We use noisy Lorenz signals to compare this approach against a classical amplitude-based nonlinear prediction error. Both measures show an almost identical robustness against Gaussian white noise. In contrast, when the amplitude distribution of the noise has a narrower central peak and heavier tails than the normal distribution, the rank-based nonlinear predictability score outperforms the amplitude-based nonlinear prediction error. For this type of noise, the nonlinear predictability score has a higher sensitivity for deterministic structure in noisy signals. It also yields a higher statistical power in a surrogate test of the null hypothesis of linear stochastic correlated signals. We show the high relevance of this improved performance in an application to electroencephalographic (EEG) recordings from epilepsy patients. Here the nonlinear predictability score again appears of higher sensitivity to nonrandomness. Importantly, it yields an improved contrast between signals recorded from brain areas where the first ictal EEG signal changes were detected (focal EEG signals) versus signals recorded from brain areas that were not involved at seizure onset (nonfocal EEG signals).

Detecting determinism with improved sensitivity in time series: Rank-based nonlinear predictability score

NASA Astrophysics Data System (ADS)

Naro, Daniel; Rummel, Christian; Schindler, Kaspar; Andrzejak, Ralph G.

2014-09-01

The rank-based nonlinear predictability score was recently introduced as a test for determinism in point processes. We here adapt this measure to time series sampled from time-continuous flows. We use noisy Lorenz signals to compare this approach against a classical amplitude-based nonlinear prediction error. Both measures show an almost identical robustness against Gaussian white noise. In contrast, when the amplitude distribution of the noise has a narrower central peak and heavier tails than the normal distribution, the rank-based nonlinear predictability score outperforms the amplitude-based nonlinear prediction error. For this type of noise, the nonlinear predictability score has a higher sensitivity for deterministic structure in noisy signals. It also yields a higher statistical power in a surrogate test of the null hypothesis of linear stochastic correlated signals. We show the high relevance of this improved performance in an application to electroencephalographic (EEG) recordings from epilepsy patients. Here the nonlinear predictability score again appears of higher sensitivity to nonrandomness. Importantly, it yields an improved contrast between signals recorded from brain areas where the first ictal EEG signal changes were detected (focal EEG signals) versus signals recorded from brain areas that were not involved at seizure onset (nonfocal EEG signals).

Distributed Computing for Signal Processing: Modeling of Asynchronous Parallel Computation.

DTIC Science & Technology

1986-03-01

the proposed approaches 16, 16, 40 . 451. The conclusion most often reached is that the best scheme to use in a particular design depends highly upon...76. 40 . Siegel, H. J., McMillen. R. J., and Mueller. P. T.. Jr. A survey of interconnection methods for reconligurable parallel processing systems...addressing meehaanm distributed in the network area rimonication% tit reach gigabit./second speeds je g.. PoCoS83 .’ i.V--i the lirO! lk i nitronment is

Integrated Sensing and Processing (ISP) Phase II: Demonstration and Evaluation for Distributed Sensor Netowrks and Missile Seeker Systems

DTIC Science & Technology

2007-02-28

Shah, D. Waagen, H. Schmitt, S. Bellofiore, A. Spanias, and D. Cochran, 32nd International Conference on Acoustics, Speech , and Signal Processing...Information Exploitation Office kNN k-Nearest Neighbor LEAN Laplacian Eigenmap Adaptive Neighbor LIP Linear Integer Programming ISP

Studies of acoustic emission from point and extended sources

NASA Technical Reports Server (NTRS)

Sachse, W.; Kim, K. Y.; Chen, C. P.

1986-01-01

The use of simulated and controlled acoustic emission signals forms the basis of a powerful tool for the detailed study of various deformation and wave interaction processes in materials. The results of experiments and signal analyses of acoustic emission resulting from point sources such as various types of indentation-produced cracks in brittle materials and the growth of fatigue cracks in 7075-T6 aluminum panels are discussed. Recent work dealing with the modeling and subsequent signal processing of an extended source of emission in a material is reviewed. Results of the forward problem and the inverse problem are presented with the example of a source distributed through the interior of a specimen.

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.

Photonics for microwave systems and ultra-wideband signal processing

NASA Astrophysics Data System (ADS)

Ng, W.

2016-08-01

The advantages of using the broadband and low-loss distribution attributes of photonics to enhance the signal processing and sensing capabilities of microwave systems are well known. In this paper, we review the progress made in the topical areas of true-time-delay beamsteering, photonic-assisted analog-to-digital conversion, RF-photonic filtering and link performances. We also provide an outlook on the emerging field of integrated microwave photonics (MWP) that promise to reduce the cost of MWP subsystems and components, while providing significantly improved form-factors for system insertion.

Distributed optical signal processing for microwave photonics subsystems.

PubMed

Chew, Suen Xin; Nguyen, Linh; Yi, Xiaoke; Song, Shijie; Li, Liwei; Bian, Pengju; Minasian, Robert

2016-03-07

We propose and experimentally demonstrate a novel and practical microwave photonic system that is capable of executing cascaded signal processing functions comprising a microwave photonic bandpass filter and a phase shifter, while providing separate and independent control for each function. The experimental results demonstrate a single bandpass microwave photonic filter with a 3-dB bandwidth of 15 MHz and an out-of-band ratio of over 40 dB, together with a simultaneous RF phase tuning control of 0-215° with less than ± 3 dB filter shape variance.

Statistical analysis of CCSN/SS7 traffic data from working CCS subnetworks

NASA Astrophysics Data System (ADS)

Duffy, Diane E.; McIntosh, Allen A.; Rosenstein, Mark; Willinger, Walter

1994-04-01

In this paper, we report on an ongoing statistical analysis of actual CCSN traffic data. The data consist of approximately 170 million signaling messages collected from a variety of different working CCS subnetworks. The key findings from our analysis concern: (1) the characteristics of both the telephone call arrival process and the signaling message arrival process; (2) the tail behavior of the call holding time distribution; and (3) the observed performance of the CCSN with respect to a variety of performance and reliability measurements.

Estimating random errors due to shot noise in backscatter lidar observations.

PubMed

Liu, Zhaoyan; Hunt, William; Vaughan, Mark; Hostetler, Chris; McGill, Matthew; Powell, Kathleen; Winker, David; Hu, Yongxiang

2006-06-20

We discuss the estimation of random errors due to shot noise in backscatter lidar observations that use either photomultiplier tube (PMT) or avalanche photodiode (APD) detectors. The statistical characteristics of photodetection are reviewed, and photon count distributions of solar background signals and laser backscatter signals are examined using airborne lidar observations at 532 nm using a photon-counting mode APD. Both distributions appear to be Poisson, indicating that the arrival at the photodetector of photons for these signals is a Poisson stochastic process. For Poisson- distributed signals, a proportional, one-to-one relationship is known to exist between the mean of a distribution and its variance. Although the multiplied photocurrent no longer follows a strict Poisson distribution in analog-mode APD and PMT detectors, the proportionality still exists between the mean and the variance of the multiplied photocurrent. We make use of this relationship by introducing the noise scale factor (NSF), which quantifies the constant of proportionality that exists between the root mean square of the random noise in a measurement and the square root of the mean signal. Using the NSF to estimate random errors in lidar measurements due to shot noise provides a significant advantage over the conventional error estimation techniques, in that with the NSF, uncertainties can be reliably calculated from or for a single data sample. Methods for evaluating the NSF are presented. Algorithms to compute the NSF are developed for the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations lidar and tested using data from the Lidar In-space Technology Experiment.

Estimating Random Errors Due to Shot Noise in Backscatter Lidar Observations

NASA Technical Reports Server (NTRS)

Liu, Zhaoyan; Hunt, William; Vaughan, Mark A.; Hostetler, Chris A.; McGill, Matthew J.; Powell, Kathy; Winker, David M.; Hu, Yongxiang

2006-01-01

In this paper, we discuss the estimation of random errors due to shot noise in backscatter lidar observations that use either photomultiplier tube (PMT) or avalanche photodiode (APD) detectors. The statistical characteristics of photodetection are reviewed, and photon count distributions of solar background signals and laser backscatter signals are examined using airborne lidar observations at 532 nm using a photon-counting mode APD. Both distributions appear to be Poisson, indicating that the arrival at the photodetector of photons for these signals is a Poisson stochastic process. For Poisson-distributed signals, a proportional, one-to-one relationship is known to exist between the mean of a distribution and its variance. Although the multiplied photocurrent no longer follows a strict Poisson distribution in analog-mode APD and PMT detectors, the proportionality still exists between the mean and the variance of the multiplied photocurrent. We make use of this relationship by introducing the noise scale factor (NSF), which quantifies the constant of proportionality that exists between the root-mean-square of the random noise in a measurement and the square root of the mean signal. Using the NSF to estimate random errors in lidar measurements due to shot noise provides a significant advantage over the conventional error estimation techniques, in that with the NSF uncertainties can be reliably calculated from/for a single data sample. Methods for evaluating the NSF are presented. Algorithms to compute the NSF are developed for the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) lidar and tested using data from the Lidar In-space Technology Experiment (LITE). OCIS Codes:

Internal curvature signal and noise in low- and high-level vision

PubMed Central

Grabowecky, Marcia; Kim, Yee Joon; Suzuki, Satoru

2011-01-01

How does internal processing contribute to visual pattern perception? By modeling visual search performance, we estimated internal signal and noise relevant to perception of curvature, a basic feature important for encoding of three-dimensional surfaces and objects. We used isolated, sparse, crowded, and face contexts to determine how internal curvature signal and noise depended on image crowding, lateral feature interactions, and level of pattern processing. Observers reported the curvature of a briefly flashed segment, which was presented alone (without lateral interaction) or among multiple straight segments (with lateral interaction). Each segment was presented with no context (engaging low-to-intermediate-level curvature processing), embedded within a face context as the mouth (engaging high-level face processing), or embedded within an inverted-scrambled-face context as a control for crowding. Using a simple, biologically plausible model of curvature perception, we estimated internal curvature signal and noise as the mean and standard deviation, respectively, of the Gaussian-distributed population activity of local curvature-tuned channels that best simulated behavioral curvature responses. Internal noise was increased by crowding but not by face context (irrespective of lateral interactions), suggesting prevention of noise accumulation in high-level pattern processing. In contrast, internal curvature signal was unaffected by crowding but modulated by lateral interactions. Lateral interactions (with straight segments) increased curvature signal when no contextual elements were added, but equivalent interactions reduced curvature signal when each segment was presented within a face. These opposing effects of lateral interactions are consistent with the phenomena of local-feature contrast in low-level processing and global-feature averaging in high-level processing. PMID:21209356

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

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

PubMed Central

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

2017-01-01

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

A Phonocardiographic-Based Fiber-Optic Sensor and Adaptive Filtering System for Noninvasive Continuous Fetal Heart Rate Monitoring.

PubMed

Martinek, Radek; Nedoma, Jan; Fajkus, Marcel; Kahankova, Radana; Konecny, Jaromir; Janku, Petr; Kepak, Stanislav; Bilik, Petr; Nazeran, Homer

2017-04-18

This paper focuses on the design, realization, and verification of a novel phonocardiographic- based fiber-optic sensor and adaptive signal processing system for noninvasive continuous fetal heart rate (fHR) monitoring. Our proposed system utilizes two Mach-Zehnder interferometeric sensors. Based on the analysis of real measurement data, we developed a simplified dynamic model for the generation and distribution of heart sounds throughout the human body. Building on this signal model, we then designed, implemented, and verified our adaptive signal processing system by implementing two stochastic gradient-based algorithms: the Least Mean Square Algorithm (LMS), and the Normalized Least Mean Square (NLMS) Algorithm. With this system we were able to extract the fHR information from high quality fetal phonocardiograms (fPCGs), filtered from abdominal maternal phonocardiograms (mPCGs) by performing fPCG signal peak detection. Common signal processing methods such as linear filtering, signal subtraction, and others could not be used for this purpose as fPCG and mPCG signals share overlapping frequency spectra. The performance of the adaptive system was evaluated by using both qualitative (gynecological studies) and quantitative measures such as: Signal-to-Noise Ratio-SNR, Root Mean Square Error-RMSE, Sensitivity-S+, and Positive Predictive Value-PPV.

A Phonocardiographic-Based Fiber-Optic Sensor and Adaptive Filtering System for Noninvasive Continuous Fetal Heart Rate Monitoring

PubMed Central

Martinek, Radek; Nedoma, Jan; Fajkus, Marcel; Kahankova, Radana; Konecny, Jaromir; Janku, Petr; Kepak, Stanislav; Bilik, Petr; Nazeran, Homer

2017-01-01

This paper focuses on the design, realization, and verification of a novel phonocardiographic- based fiber-optic sensor and adaptive signal processing system for noninvasive continuous fetal heart rate (fHR) monitoring. Our proposed system utilizes two Mach-Zehnder interferometeric sensors. Based on the analysis of real measurement data, we developed a simplified dynamic model for the generation and distribution of heart sounds throughout the human body. Building on this signal model, we then designed, implemented, and verified our adaptive signal processing system by implementing two stochastic gradient-based algorithms: the Least Mean Square Algorithm (LMS), and the Normalized Least Mean Square (NLMS) Algorithm. With this system we were able to extract the fHR information from high quality fetal phonocardiograms (fPCGs), filtered from abdominal maternal phonocardiograms (mPCGs) by performing fPCG signal peak detection. Common signal processing methods such as linear filtering, signal subtraction, and others could not be used for this purpose as fPCG and mPCG signals share overlapping frequency spectra. The performance of the adaptive system was evaluated by using both qualitative (gynecological studies) and quantitative measures such as: Signal-to-Noise Ratio—SNR, Root Mean Square Error—RMSE, Sensitivity—S+, and Positive Predictive Value—PPV. PMID:28420215

A concept for non-invasive temperature measurement during injection moulding processes

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

Hopmann, Christian; Spekowius, Marcel, E-mail: spekowius@ikv.rwth-aachen.de; Wipperfürth, Jens

2016-03-09

Current models of the injection moulding process insufficiently consider the thermal interactions between melt, solidified material and the mould. A detailed description requires a deep understanding of the underlying processes and a precise observation of the temperature. Because todays measurement concepts do not allow a non-invasive analysis it is necessary to find new measurement techniques for temperature measurements during the manufacturing process. In this work we present the idea of a set up for a tomographic ultrasound measurement of the temperature field inside a plastics melt. The goal is to identify a concept that can be installed on a specializedmore » mould for the injection moulding process. The challenges are discussed and the design of a prototype is shown. Special attention is given to the spatial arrangement of the sensors. Besides the design of a measurement set up a reconstruction strategy for the ultrasound signals is required. We present an approach in which an image processing algorithm can be used to calculate a temperature distribution from the ultrasound scans. We discuss a reconstruction strategy in which the ultrasound signals are converted into a spartial temperature distribution by using pvT curves that are obtained by dilatometer measurements.« less

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

NASA Astrophysics Data System (ADS)

Boashash, Boualem

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

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

NASA Astrophysics Data System (ADS)

Boashash, Boualem

1988-02-01

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

Energy-efficient hierarchical processing in the network of wireless intelligent sensors (WISE)

NASA Astrophysics Data System (ADS)

Raskovic, Dejan

Sensor network nodes have benefited from technological advances in the field of wireless communication, processing, and power sources. However, the processing power of microcontrollers is often not sufficient to perform sophisticated processing, while the power requirements of digital signal processing boards or handheld computers are usually too demanding for prolonged system use. We are matching the intrinsic hierarchical nature of many digital signal-processing applications with the natural hierarchy in distributed wireless networks, and building the hierarchical system of wireless intelligent sensors. Our goal is to build a system that will exploit the hierarchical organization to optimize the power consumption and extend battery life for the given time and memory constraints, while providing real-time processing of sensor signals. In addition, we are designing our system to be able to adapt to the current state of the environment, by dynamically changing the algorithm through procedure replacement. This dissertation presents the analysis of hierarchical environment and methods for energy profiling used to evaluate different system design strategies, and to optimize time-effective and energy-efficient processing.

Signal processing for molecular and cellular biological physics: an emerging field.

PubMed

Little, Max A; Jones, Nick S

2013-02-13

Recent advances in our ability to watch the molecular and cellular processes of life in action--such as atomic force microscopy, optical tweezers and Forster fluorescence resonance energy transfer--raise challenges for digital signal processing (DSP) of the resulting experimental data. This article explores the unique properties of such biophysical time series that set them apart from other signals, such as the prevalence of abrupt jumps and steps, multi-modal distributions and autocorrelated noise. It exposes the problems with classical linear DSP algorithms applied to this kind of data, and describes new nonlinear and non-Gaussian algorithms that are able to extract information that is of direct relevance to biological physicists. It is argued that these new methods applied in this context typify the nascent field of biophysical DSP. Practical experimental examples are supplied.

Signal processing for molecular and cellular biological physics: an emerging field

PubMed Central

Little, Max A.; Jones, Nick S.

2013-01-01

Recent advances in our ability to watch the molecular and cellular processes of life in action—such as atomic force microscopy, optical tweezers and Forster fluorescence resonance energy transfer—raise challenges for digital signal processing (DSP) of the resulting experimental data. This article explores the unique properties of such biophysical time series that set them apart from other signals, such as the prevalence of abrupt jumps and steps, multi-modal distributions and autocorrelated noise. It exposes the problems with classical linear DSP algorithms applied to this kind of data, and describes new nonlinear and non-Gaussian algorithms that are able to extract information that is of direct relevance to biological physicists. It is argued that these new methods applied in this context typify the nascent field of biophysical DSP. Practical experimental examples are supplied. PMID:23277603

The Miniaturization of the AFIT Random Noise Radar

DTIC Science & Technology

2013-03-01

RANDOM NOISE RADAR I. Introduction Recent advances in technology and signal processing techniques have opened thedoor to using an ultra-wide band random...AIR FORCE INSTITUTE OF TECHNOLOGY Wright-Patterson Air Force Base, Ohio DISTRIBUTION STATEMENT A. APPROVED FOR PUBLIC RELEASE; DISTRIBUTION UNLIMITED...and Computer Engineering Graduate School of Engineering and Management Air Force Institute of Technology Air University Air Education and Training

A cost-effective line-based light-balancing technique using adaptive processing.

PubMed

Hsia, Shih-Chang; Chen, Ming-Huei; Chen, Yu-Min

2006-09-01

The camera imaging system has been widely used; however, the displaying image appears to have an unequal light distribution. This paper presents novel light-balancing techniques to compensate uneven illumination based on adaptive signal processing. For text image processing, first, we estimate the background level and then process each pixel with nonuniform gain. This algorithm can balance the light distribution while keeping a high contrast in the image. For graph image processing, the adaptive section control using piecewise nonlinear gain is proposed to equalize the histogram. Simulations show that the performance of light balance is better than the other methods. Moreover, we employ line-based processing to efficiently reduce the memory requirement and the computational cost to make it applicable in real-time systems.

Phosphotyrosine-mediated LAT assembly on membranes drives kinetic bifurcation in recruitment dynamics of the Ras activator SOS

DOE PAGES

Huang, William Y. C.; Yan, Qingrong; Lin, Wan-Chen; ...

2016-07-01

The assembly of cell surface receptors with downstream signaling molecules is a commonly occurring theme in multiple signaling systems. However, little is known about how these assemblies modulate reaction kinetics and the ultimate propagation of signals. Here, we reconstitute phosphotyrosine-mediated assembly of extended linker for the activation of T cells (LAT):growth factor receptor-bound protein 2 (Grb2):Son of Sevenless (SOS) networks, derived from the T-cell receptor signaling system, on supported membranes. Single-molecule dwell time distributions reveal two, well-differentiated kinetic species for both Grb2 and SOS on the LAT assemblies. The majority fraction of membrane-recruited Grb2 and SOS both exhibit fast kineticsmore » and single exponential dwell time distributions, with average dwell times of hundreds of milliseconds. The minor fraction exhibits much slower kinetics, extending the dwell times to tens of seconds. Considering this result in the context of the multistep process by which the Ras GEF (guanine nucleotide exchange factor) activity of SOS is activated indicates that kinetic stabilization from the LAT assembly may be important. This kinetic proofreading effect would additionally serve as a stochastic noise filter by reducing the relative probability of spontaneous SOS activation in the absence of receptor triggering. In conclusion, the generality of receptor-mediated assembly suggests that such effects may play a role in multiple receptor proximal signaling processes.« less

Phosphotyrosine-mediated LAT assembly on membranes drives kinetic bifurcation in recruitment dynamics of the Ras activator SOS

PubMed Central

Huang, William Y. C.; Yan, Qingrong; Lin, Wan-Chen; Chung, Jean K.; Hansen, Scott D.; Christensen, Sune M.; Tu, Hsiung-Lin; Kuriyan, John; Groves, Jay T.

2016-01-01

The assembly of cell surface receptors with downstream signaling molecules is a commonly occurring theme in multiple signaling systems. However, little is known about how these assemblies modulate reaction kinetics and the ultimate propagation of signals. Here, we reconstitute phosphotyrosine-mediated assembly of extended linker for the activation of T cells (LAT):growth factor receptor-bound protein 2 (Grb2):Son of Sevenless (SOS) networks, derived from the T-cell receptor signaling system, on supported membranes. Single-molecule dwell time distributions reveal two, well-differentiated kinetic species for both Grb2 and SOS on the LAT assemblies. The majority fraction of membrane-recruited Grb2 and SOS both exhibit fast kinetics and single exponential dwell time distributions, with average dwell times of hundreds of milliseconds. The minor fraction exhibits much slower kinetics, extending the dwell times to tens of seconds. Considering this result in the context of the multistep process by which the Ras GEF (guanine nucleotide exchange factor) activity of SOS is activated indicates that kinetic stabilization from the LAT assembly may be important. This kinetic proofreading effect would additionally serve as a stochastic noise filter by reducing the relative probability of spontaneous SOS activation in the absence of receptor triggering. The generality of receptor-mediated assembly suggests that such effects may play a role in multiple receptor proximal signaling processes. PMID:27370798

Phosphotyrosine-mediated LAT assembly on membranes drives kinetic bifurcation in recruitment dynamics of the Ras activator SOS.

PubMed

Huang, William Y C; Yan, Qingrong; Lin, Wan-Chen; Chung, Jean K; Hansen, Scott D; Christensen, Sune M; Tu, Hsiung-Lin; Kuriyan, John; Groves, Jay T

2016-07-19

The assembly of cell surface receptors with downstream signaling molecules is a commonly occurring theme in multiple signaling systems. However, little is known about how these assemblies modulate reaction kinetics and the ultimate propagation of signals. Here, we reconstitute phosphotyrosine-mediated assembly of extended linker for the activation of T cells (LAT):growth factor receptor-bound protein 2 (Grb2):Son of Sevenless (SOS) networks, derived from the T-cell receptor signaling system, on supported membranes. Single-molecule dwell time distributions reveal two, well-differentiated kinetic species for both Grb2 and SOS on the LAT assemblies. The majority fraction of membrane-recruited Grb2 and SOS both exhibit fast kinetics and single exponential dwell time distributions, with average dwell times of hundreds of milliseconds. The minor fraction exhibits much slower kinetics, extending the dwell times to tens of seconds. Considering this result in the context of the multistep process by which the Ras GEF (guanine nucleotide exchange factor) activity of SOS is activated indicates that kinetic stabilization from the LAT assembly may be important. This kinetic proofreading effect would additionally serve as a stochastic noise filter by reducing the relative probability of spontaneous SOS activation in the absence of receptor triggering. The generality of receptor-mediated assembly suggests that such effects may play a role in multiple receptor proximal signaling processes.

Distributed Environment Control Using Wireless Sensor/Actuator Networks for Lighting Applications

PubMed Central

Nakamura, Masayuki; Sakurai, Atsushi; Nakamura, Jiro

2009-01-01

We propose a decentralized algorithm to calculate the control signals for lights in wireless sensor/actuator networks. This algorithm uses an appropriate step size in the iterative process used for quickly computing the control signals. We demonstrate the accuracy and efficiency of this approach compared with the penalty method by using Mote-based mesh sensor networks. The estimation error of the new approach is one-eighth as large as that of the penalty method with one-fifth of its computation time. In addition, we describe our sensor/actuator node for distributed lighting control based on the decentralized algorithm and demonstrate its practical efficacy. PMID:22291525

Detection of weak signals in memory thermal baths.

PubMed

Jiménez-Aquino, J I; Velasco, R M; Romero-Bastida, M

2014-11-01

The nonlinear relaxation time and the statistics of the first passage time distribution in connection with the quasideterministic approach are used to detect weak signals in the decay process of the unstable state of a Brownian particle embedded in memory thermal baths. The study is performed in the overdamped approximation of a generalized Langevin equation characterized by an exponential decay in the friction memory kernel. A detection criterion for each time scale is studied: The first one is referred to as the receiver output, which is given as a function of the nonlinear relaxation time, and the second one is related to the statistics of the first passage time distribution.

GLOBECOM '87 - Global Telecommunications Conference, Tokyo, Japan, Nov. 15-18, 1987, Conference Record. Volumes 1, 2, & 3

NASA Astrophysics Data System (ADS)

The present conference on global telecommunications discusses topics in the fields of Integrated Services Digital Network (ISDN) technology field trial planning and results to date, motion video coding, ISDN networking, future network communications security, flexible and intelligent voice/data networks, Asian and Pacific lightwave and radio systems, subscriber radio systems, the performance of distributed systems, signal processing theory, satellite communications modulation and coding, and terminals for the handicapped. Also discussed are knowledge-based technologies for communications systems, future satellite transmissions, high quality image services, novel digital signal processors, broadband network access interface, traffic engineering for ISDN design and planning, telecommunications software, coherent optical communications, multimedia terminal systems, advanced speed coding, portable and mobile radio communications, multi-Gbit/second lightwave transmission systems, enhanced capability digital terminals, communications network reliability, advanced antimultipath fading techniques, undersea lightwave transmission, image coding, modulation and synchronization, adaptive signal processing, integrated optical devices, VLSI technologies for ISDN, field performance of packet switching, CSMA protocols, optical transport system architectures for broadband ISDN, mobile satellite communications, indoor wireless communication, echo cancellation in communications, and distributed network algorithms.

[Multi-channel in vivo recording techniques: signal processing of action potentials and local field potentials].

PubMed

Xu, Jia-Min; Wang, Ce-Qun; Lin, Long-Nian

2014-06-25

Multi-channel in vivo recording techniques are used to record ensemble neuronal activity and local field potentials (LFP) simultaneously. One of the key points for the technique is how to process these two sets of recorded neural signals properly so that data accuracy can be assured. We intend to introduce data processing approaches for action potentials and LFP based on the original data collected through multi-channel recording system. Action potential signals are high-frequency signals, hence high sampling rate of 40 kHz is normally chosen for recording. Based on waveforms of extracellularly recorded action potentials, tetrode technology combining principal component analysis can be used to discriminate neuronal spiking signals from differently spatially distributed neurons, in order to obtain accurate single neuron spiking activity. LFPs are low-frequency signals (lower than 300 Hz), hence the sampling rate of 1 kHz is used for LFPs. Digital filtering is required for LFP analysis to isolate different frequency oscillations including theta oscillation (4-12 Hz), which is dominant in active exploration and rapid-eye-movement (REM) sleep, gamma oscillation (30-80 Hz), which is accompanied by theta oscillation during cognitive processing, and high frequency ripple oscillation (100-250 Hz) in awake immobility and slow wave sleep (SWS) state in rodent hippocampus. For the obtained signals, common data post-processing methods include inter-spike interval analysis, spike auto-correlation analysis, spike cross-correlation analysis, power spectral density analysis, and spectrogram analysis.

Deterring watermark collusion attacks using signal processing techniques

NASA Astrophysics Data System (ADS)

Lemma, Aweke N.; van der Veen, Michiel

2007-02-01

Collusion attack is a malicious watermark removal attack in which the hacker has access to multiple copies of the same content with different watermarks and tries to remove the watermark using averaging. In the literature, several solutions to collusion attacks have been reported. The main stream solutions aim at designing watermark codes that are inherently resistant to collusion attacks. The other approaches propose signal processing based solutions that aim at modifying the watermarked signals in such a way that averaging multiple copies of the content leads to a significant degradation of the content quality. In this paper, we present signal processing based technique that may be deployed for deterring collusion attacks. We formulate the problem in the context of electronic music distribution where the content is generally available in the compressed domain. Thus, we first extend the collusion resistance principles to bit stream signals and secondly present experimental based analysis to estimate a bound on the maximum number of modified versions of a content that satisfy good perceptibility requirement on one hand and destructive averaging property on the other hand.

Differential distribution of adenosine receptors in rat cochlea.

PubMed

Vlajkovic, Srdjan M; Abi, Shukri; Wang, Carol J H; Housley, Gary D; Thorne, Peter R

2007-06-01

Adenosine is a constitutive cell metabolite that can be released from cells via specific bi-directional transporters and is an end-point for nucleotide hydrolysis. In the extracellular space, adenosine becomes a signalling molecule for P1 (adenosine) receptors that modulate physiological responses in a wide range of mammalian tissues. Whereas adenosine signalling has been implicated in the regulation of cochlear blood flow and in cochlear protection from oxidative damage, the potential roles for adenosine signalling in the modulation of sound transduction and auditory neurotransmission have not been established. We have characterised the expression and distribution of adenosine receptors in the rat cochlea. mRNA transcripts for all four subtypes of adenosine receptors (A(1), A(2A), A(2B) and A(3)) were detected in dissected cochlear tissue by using reverse transcription/polymerase chain reaction analysis. The protein distribution for the A(1), A(2A) and A(3) receptor subtypes was identified by immunoperoxidase histochemistry and confocal immunofluorescence labelling. These receptors were differentially expressed in the organ of Corti, spiral ganglion neurones, lateral wall tissues and cochlear blood vessels. The distribution of adenosine receptors in sensory and neural tissues and in the vasculature coincided with other elements of purinergic signalling (P2X and P2Y receptors, ectonucleotidases), consistent with the integrative regulation of many physiological processes in the cochlea by extracellular nucleotides and nucleosides. Our study provides a framework for further investigation of adenosine signalling in the inner ear, including putative roles in oxidative stress responses.

Body size distributions signal a regime shift in a lake ...

EPA Pesticide Factsheets

Communities of organisms, from mammals to microorganisms, have discontinuous distributions of body size. This pattern of size structuring is a conservative trait of community organization and is a product of processes that occur at multiple spatial and temporal scales. In this study, we assessed whether body size patterns serve as an indicator of a threshold between alternative regimes. Over the past 7000 years, the biological communities of Foy Lake (Montana,USA) have undergone a major regime shift owing to climate change. We used a palaeoecological record of diatom communities to estimate diatom sizes, and then analysed the discontinuous distribution of organism sizes over time. We used Bayesian classification and regression tree models to determine that all time intervals exhibited aggregations of sizes separated by gaps in the distribution and found a significant change in diatom body size distributions approximately 150 years before the identified ecosystem regime shift. We suggest that discontinuity analysis is a useful addition to the suite of tools for the detection of early warning signals of regime shifts. Communities of organisms from mammals to microorganisms have discontinuous distributions of body size. This pattern of size structuring is a conservative trait of community organization and is a product of processes that occur at discrete spatial and temporal scales within ecosystems. Here, a paleoecological record of diatom community change is use

In-line mixing states monitoring of suspensions using ultrasonic reflection technique.

PubMed

Zhan, Xiaobin; Yang, Yili; Liang, Jian; Zou, Dajun; Zhang, Jiaqi; Feng, Luyi; Shi, Tielin; Li, Xiwen

2016-02-01

Based on the measurement of echo signal changes caused by different concentration distributions in the mixing process, a simple ultrasonic reflection technique is proposed for in-line monitoring of the mixing states of suspensions in an agitated tank in this study. The relation between the echo signals and the concentration of suspensions is studied, and the mixing process of suspensions is tracked by in-line measurement of ultrasonic echo signals using two ultrasonic sensors. Through the analysis of echo signals over time, the mixing states of suspensions are obtained, and the homogeneity of suspensions is quantified. With the proposed technique, the effects of impeller diameter and agitation speed on the mixing process are studied, and the optimal agitation speed and the minimum mixing time to achieve the maximum homogeneity are acquired under different operating conditions and design parameters. The proposed technique is stable and feasible and shows great potential for in-line monitoring of mixing states of suspensions. Copyright © 2015 Elsevier B.V. All rights reserved.

A biological inspired fuzzy adaptive window median filter (FAWMF) for enhancing DNA signal processing.

PubMed

Ahmad, Muneer; Jung, Low Tan; Bhuiyan, Al-Amin

2017-10-01

Digital signal processing techniques commonly employ fixed length window filters to process the signal contents. DNA signals differ in characteristics from common digital signals since they carry nucleotides as contents. The nucleotides own genetic code context and fuzzy behaviors due to their special structure and order in DNA strand. Employing conventional fixed length window filters for DNA signal processing produce spectral leakage and hence results in signal noise. A biological context aware adaptive window filter is required to process the DNA signals. This paper introduces a biological inspired fuzzy adaptive window median filter (FAWMF) which computes the fuzzy membership strength of nucleotides in each slide of window and filters nucleotides based on median filtering with a combination of s-shaped and z-shaped filters. Since coding regions cause 3-base periodicity by an unbalanced nucleotides' distribution producing a relatively high bias for nucleotides' usage, such fundamental characteristic of nucleotides has been exploited in FAWMF to suppress the signal noise. Along with adaptive response of FAWMF, a strong correlation between median nucleotides and the Π shaped filter was observed which produced enhanced discrimination between coding and non-coding regions contrary to fixed length conventional window filters. The proposed FAWMF attains a significant enhancement in coding regions identification i.e. 40% to 125% as compared to other conventional window filters tested over more than 250 benchmarked and randomly taken DNA datasets of different organisms. This study proves that conventional fixed length window filters applied to DNA signals do not achieve significant results since the nucleotides carry genetic code context. The proposed FAWMF algorithm is adaptive and outperforms significantly to process DNA signal contents. The algorithm applied to variety of DNA datasets produced noteworthy discrimination between coding and non-coding regions contrary to fixed window length conventional filters. Copyright © 2017 Elsevier B.V. All rights reserved.

Body size distributions signal a regime shift in a lake ecosystem

USGS Publications Warehouse

Spanbauer, Trisha; Allen, Craig R.; Angeler, David G.; Eason, Tarsha; Fritz, Sherilyn C.; Garmestani, Ahjond S.; Nash, Kirsty L.; Stone, Jeffery R.; Stow, Craig A.; Sundstrom, Shana M.

2016-01-01

Communities of organisms, from mammals to microorganisms, have discontinuous distributions of body size. This pattern of size structuring is a conservative trait of community organization and is a product of processes that occur at multiple spatial and temporal scales. In this study, we assessed whether body size patterns serve as an indicator of a threshold between alternative regimes. Over the past 7000 years, the biological communities of Foy Lake (Montana, USA) have undergone a major regime shift owing to climate change. We used a palaeoecological record of diatom communities to estimate diatom sizes, and then analysed the discontinuous distribution of organism sizes over time. We used Bayesian classification and regression tree models to determine that all time intervals exhibited aggregations of sizes separated by gaps in the distribution and found a significant change in diatom body size distributions approximately 150 years before the identified ecosystem regime shift. We suggest that discontinuity analysis is a useful addition to the suite of tools for the detection of early warning signals of regime shifts.

Investigation of Doppler spectra of laser radiation scattered inside hand skin during occlusion test

NASA Astrophysics Data System (ADS)

Kozlov, I. O.; Zherebtsov, E. A.; Zherebtsova, A. I.; Dremin, V. V.; Dunaev, A. V.

2017-11-01

Laser Doppler flowmetry (LDF) is a method widely used in diagnosis of microcirculation diseases. It is well known that information about frequency distribution of Doppler spectrum of the laser radiation scattered by moving red blood cells (RBC) usually disappears after signal processing procedure. Photocurrent’s spectrum distribution contains valuable diagnostic information about velocity distribution of the RBC. In this research it is proposed to compute the indexes of microcirculation in the sub-ranges of the Doppler spectrum as well as investigate the frequency distribution of the computed indexes.

Photonic Materials and Devices for RF (mmW) Sensing and Imaging

DTIC Science & Technology

2012-12-31

wave encoding thereby eliminating the need for bulky LO distribution cables. Also, optical processing techniques can be utilized to provide simple... optical powers, can be close to unity and low -noise photodetectors make the detection of exceedingly low power millimeter-waves practical. In... optically -filtering the modulated signal to pass only a single sideband and detecting the resultant optical signal with a low -noise photodetector we have

Distributed processing for features improvement in real-time portable medical devices.

PubMed

Mercado, Erwin John Saavedra

2008-01-01

Portable biomedical devices are being developed and incorporated in daily life. Nevertheless, their standalone capacity is diminished due to the lack of processing power required to face such duties as for example, signal artifacts robustness in EKG monitor devices. The following paper presents a multiprocessor architecture made from simple microcontrollers to provide an increase in processing performance, power consumption efficiency and lower cost.

Visual perception and imagery: a new molecular hypothesis.

PubMed

Bókkon, I

2009-05-01

Here, we put forward a redox molecular hypothesis about the natural biophysical substrate of visual perception and visual imagery. This hypothesis is based on the redox and bioluminescent processes of neuronal cells in retinotopically organized cytochrome oxidase-rich visual areas. Our hypothesis is in line with the functional roles of reactive oxygen and nitrogen species in living cells that are not part of haphazard process, but rather a very strict mechanism used in signaling pathways. We point out that there is a direct relationship between neuronal activity and the biophoton emission process in the brain. Electrical and biochemical processes in the brain represent sensory information from the external world. During encoding or retrieval of information, electrical signals of neurons can be converted into synchronized biophoton signals by bioluminescent radical and non-radical processes. Therefore, information in the brain appears not only as an electrical (chemical) signal but also as a regulated biophoton (weak optical) signal inside neurons. During visual perception, the topological distribution of photon stimuli on the retina is represented by electrical neuronal activity in retinotopically organized visual areas. These retinotopic electrical signals in visual neurons can be converted into synchronized biophoton signals by radical and non-radical processes in retinotopically organized mitochondria-rich areas. As a result, regulated bioluminescent biophotons can create intrinsic pictures (depictive representation) in retinotopically organized cytochrome oxidase-rich visual areas during visual imagery and visual perception. The long-term visual memory is interpreted as epigenetic information regulated by free radicals and redox processes. This hypothesis does not claim to solve the secret of consciousness, but proposes that the evolution of higher levels of complexity made the intrinsic picture representation of the external visual world possible by regulated redox and bioluminescent reactions in the visual system during visual perception and visual imagery.

Distributed digital signal processors for multi-body flexible structures

NASA Technical Reports Server (NTRS)

Lee, Gordon K. F.

1992-01-01

Multi-body flexible structures, such as those currently under investigation in spacecraft design, are large scale (high-order) dimensional systems. Controlling and filtering such structures is a computationally complex problem. This is particularly important when many sensors and actuators are located along the structure and need to be processed in real time. This report summarizes research activity focused on solving the signal processing (that is, information processing) issues of multi-body structures. A distributed architecture is developed in which single loop processors are employed for local filtering and control. By implementing such a philosophy with an embedded controller configuration, a supervising controller may be used to process global data and make global decisions as the local devices are processing local information. A hardware testbed, a position controller system for a servo motor, is employed to illustrate the capabilities of the embedded controller structure. Several filtering and control structures which can be modeled as rational functions can be implemented on the system developed in this research effort. Thus the results of the study provide a support tool for many Control/Structure Interaction (CSI) NASA testbeds such as the Evolutionary model and the nine-bay truss structure.

Fractal dimension and nonlinear dynamical processes

NASA Astrophysics Data System (ADS)

McCarty, Robert C.; Lindley, John P.

1993-11-01

Mandelbrot, Falconer and others have demonstrated the existence of dimensionally invariant geometrical properties of non-linear dynamical processes known as fractals. Barnsley defines fractal geometry as an extension of classical geometry. Such an extension, however, is not mathematically trivial Of specific interest to those engaged in signal processing is the potential use of fractal geometry to facilitate the analysis of non-linear signal processes often referred to as non-linear time series. Fractal geometry has been used in the modeling of non- linear time series represented by radar signals in the presence of ground clutter or interference generated by spatially distributed reflections around the target or a radar system. It was recognized by Mandelbrot that the fractal geometries represented by man-made objects had different dimensions than the geometries of the familiar objects that abound in nature such as leaves, clouds, ferns, trees, etc. The invariant dimensional property of non-linear processes suggests that in the case of acoustic signals (active or passive) generated within a dispersive medium such as the ocean environment, there exists much rich structure that will aid in the detection and classification of various objects, man-made or natural, within the medium.

Radioastronomic signal processing cores for the SKA radio telescope

NASA Astrophysics Data System (ADS)

Comorett, G.; Chiarucc, S.; Belli, C.

Modern radio telescopes require the processing of wideband signals, with sample rates from tens of MHz to tens of GHz, and are composed from hundreds up to a million of individual antennas. Digital signal processing of these signals include digital receivers (the digital equivalent of the heterodyne receiver), beamformers, channelizers, spectrometers. FPGAs present the advantage of providing a relatively low power consumption, relative to GPUs or dedicated computers, a wide signal data path, and high interconnectivity. Efficient algorithms have been developed for these applications. Here we will review some of the signal processing cores developed for the SKA telescope. The LFAA beamformer/channelizer architecture is based on an oversampling channelizer, where the channelizer output sampling rate and channel spacing can be set independently. This is useful where an overlap between adjacent channels is required to provide an uniform spectral coverage. The architecture allows for an efficient and distributed channelization scheme, with a final resolution corresponding to a million of spectral channels, minimum leakage and high out-of-band rejection. An optimized filter design procedure is used to provide an equiripple response with a very large number of spectral channels. A wideband digital receiver has been designed in order to select the processed bandwidth of the SKA Mid receiver. The receiver extracts a 2.5 MHz bandwidth form a 14 GHz input bandwidth. The design allows for non-integer ratios between the input and output sampling rates, with a resource usage comparable to that of a conventional decimating digital receiver. Finally, some considerations on quantization of radioastronomic signals are presented. Due to the stochastic nature of the signal, quantization using few data bits is possible. Good accuracies and dynamic range are possible even with 2-3 bits, but the nonlinearity in the correlation process must be corrected in post-processing. With at least 6 bits it is possible to have a very linear response of the instrument, with nonlinear terms below 80 dB, providing the signal amplitude is kept within bounds.

Estimation of the Scatterer Distribution of the Cirrhotic Liver using Ultrasonic Image

NASA Astrophysics Data System (ADS)

Yamaguchi, Tadashi; Hachiya, Hiroyuki

1998-05-01

In the B-mode image of the liver obtained by an ultrasonic imaging system, the speckled pattern changes with the progression of the disease such as liver cirrhosis.In this paper we present the statistical characteristics of the echo envelope of the liver, and the technique to extract information of the scatterer distribution from the normal and cirrhotic liver images using constant false alarm rate (CFAR) processing.We analyze the relationship between the extracted scatterer distribution and the stage of liver cirrhosis. The ratio of the area in which the amplitude of the processing signal is more than the threshold to the entire processed image area is related quantitatively to the stage of liver cirrhosis.It is found that the proposed technique is valid for the quantitative diagnosis of liver cirrhosis.

Spatiotemporal transcriptome provides insights into early fruit development of tomato (Solanum lycopersicum).

PubMed

Zhang, Shuaibin; Xu, Meng; Qiu, Zhengkun; Wang, Ketao; Du, Yongchen; Gu, Lianfeng; Cui, Xia

2016-03-18

Early fruit development is crucial for crop production in tomato. After fertilization, the ovary undergoes cell division and cell expansion before maturation. Although the roles of regulatory signals such as hormone and carbohydrate during early fruit development have been studied, the spatial distribution and the sequential initiation of these regulatory signals still need to be explored. Using the tomato cultivar 'Moneymaker', we analyzed the transcriptome of the ovule and the ovary wall/pericarp dissected from four different stages of the early developing fruits by stereoscope. These datasets give us the whole picture about the spatial and temporal signal distribution in early development of ovule and pericarp. Our results indicate that the hormone signal was initiated in both ovule and pericarp after fertilization. After that, different signals were activated in ovule and pericarp due to their distinct developmental processes. Our study provides spatiotemporal regulatory landscape of gene expression with sequential information which was not studied by previous work and further strengthens the comprehension of the regulatory and metabolic events controlling early fruit development.

Multi-Scale Morphological Analysis of Conductance Signals in Vertical Upward Gas-Liquid Two-Phase Flow

NASA Astrophysics Data System (ADS)

Lian, Enyang; Ren, Yingyu; Han, Yunfeng; Liu, Weixin; Jin, Ningde; Zhao, Junying

2016-11-01

The multi-scale analysis is an important method for detecting nonlinear systems. In this study, we carry out experiments and measure the fluctuation signals from a rotating electric field conductance sensor with eight electrodes. We first use a recurrence plot to recognise flow patterns in vertical upward gas-liquid two-phase pipe flow from measured signals. Then we apply a multi-scale morphological analysis based on the first-order difference scatter plot to investigate the signals captured from the vertical upward gas-liquid two-phase flow loop test. We find that the invariant scaling exponent extracted from the multi-scale first-order difference scatter plot with the bisector of the second-fourth quadrant as the reference line is sensitive to the inhomogeneous distribution characteristics of the flow structure, and the variation trend of the exponent is helpful to understand the process of breakup and coalescence of the gas phase. In addition, we explore the dynamic mechanism influencing the inhomogeneous distribution of the gas phase in terms of adaptive optimal kernel time-frequency representation. The research indicates that the system energy is a factor influencing the distribution of the gas phase and the multi-scale morphological analysis based on the first-order difference scatter plot is an effective method for indicating the inhomogeneous distribution of the gas phase in gas-liquid two-phase flow.

Regulation of EGFR signal transduction by analogue-to-digital conversion in endosomes

PubMed Central

Villaseñor, Roberto; Nonaka, Hidenori; Del Conte-Zerial, Perla; Kalaidzidis, Yannis; Zerial, Marino

2015-01-01

An outstanding question is how receptor tyrosine kinases (RTKs) determine different cell-fate decisions despite sharing the same signalling cascades. Here, we uncovered an unexpected mechanism of RTK trafficking in this process. By quantitative high-resolution FRET microscopy, we found that phosphorylated epidermal growth factor receptor (p-EGFR) is not randomly distributed but packaged at constant mean amounts in endosomes. Cells respond to higher EGF concentrations by increasing the number of endosomes but keeping the mean p-EGFR content per endosome almost constant. By mathematical modelling, we found that this mechanism confers both robustness and regulation to signalling output. Different growth factors caused specific changes in endosome number and size in various cell systems and changing the distribution of p-EGFR between endosomes was sufficient to reprogram cell-fate decision upon EGF stimulation. We propose that the packaging of p-RTKs in endosomes is a general mechanism to ensure the fidelity and specificity of the signalling response. DOI: http://dx.doi.org/10.7554/eLife.06156.001 PMID:25650738

Optical Processing of Speckle Images with Bacteriorhodopsin for Pattern Recognition

NASA Technical Reports Server (NTRS)

Downie, John D.; Tucker, Deanne (Technical Monitor)

1994-01-01

Logarithmic processing of images with multiplicative noise characteristics can be utilized to transform the image into one with an additive noise distribution. This simplifies subsequent image processing steps for applications such as image restoration or correlation for pattern recognition. One particularly common form of multiplicative noise is speckle, for which the logarithmic operation not only produces additive noise, but also makes it of constant variance (signal-independent). We examine the optical transmission properties of some bacteriorhodopsin films here and find them well suited to implement such a pointwise logarithmic transformation optically in a parallel fashion. We present experimental results of the optical conversion of speckle images into transformed images with additive, signal-independent noise statistics using the real-time photochromic properties of bacteriorhodopsin. We provide an example of improved correlation performance in terms of correlation peak signal-to-noise for such a transformed speckle image.

Analysis of the reflection of a micro drop fiber sensor

NASA Astrophysics Data System (ADS)

Sun, Weimin; Liu, Qiang; Zhao, Lei; Li, Yingjuan; Yuan, Libo

2005-01-01

Micro drop fiber sensors are effective tools for measuring characters of liquids. These types of sensors are wildly used in biotechnology, beverage and food markets. For a fiber micro drop sensor, the signal of the output light is wavy with two peaks, normally. Carefully analyzing the wavy process can identify the liquid components. Understanding the reason of forming this wavy signal is important to design a suitable sensing head and to choose a suitable signal-processing method. The dripping process of a type of liquids is relative to the characters of the liquid and the shape of the sensing head. The quasi-Gauss model of the light field from the input-fiber end is used to analyse the distribution of the light field in the liquid drop. In addition, considering the characters of the liquid to be measured, the dripping process of the optical signal from the output-fiber end can be expected. The reflection surface of the micro drop varies as serials of spheres with different radiuses and global centers. The intensity of the reflection light changes with the shape of the surface. The varying process of the intensity relates to the tense, refractive index, transmission et al. To support the analyse above, an experimental system is established. In the system, LED is chosen as the light source and the PIN transform the light signal to the electrical signal, which is collected by a data acquisition card. An on-line testing system is made to check the theory discussed above.

Llamas: Large-area microphone arrays and sensing systems

NASA Astrophysics Data System (ADS)

Sanz-Robinson, Josue

Large-area electronics (LAE) provides a platform to build sensing systems, based on distributing large numbers of densely spaced sensors over a physically-expansive space. Due to their flexible, "wallpaper-like" form factor, these systems can be seamlessly deployed in everyday spaces. They go beyond just supplying sensor readings, but rather they aim to transform the wealth of data from these sensors into actionable inferences about our physical environment. This requires vertically integrated systems that span the entirety of the signal processing chain, including transducers and devices, circuits, and signal processing algorithms. To this end we develop hybrid LAE / CMOS systems, which exploit the complementary strengths of LAE, enabling spatially distributed sensors, and CMOS ICs, providing computational capacity for signal processing. To explore the development of hybrid sensing systems, based on vertical integration across the signal processing chain, we focus on two main drivers: (1) thin-film diodes, and (2) microphone arrays for blind source separation: 1) Thin-film diodes are a key building block for many applications, such as RFID tags or power transfer over non-contact inductive links, which require rectifiers for AC-to-DC conversion. We developed hybrid amorphous / nanocrystalline silicon diodes, which are fabricated at low temperatures (<200 °C) to be compatible with processing on plastic, and have high current densities (5 A/cm2 at 1 V) and high frequency operation (cutoff frequency of 110 MHz). 2) We designed a system for separating the voices of multiple simultaneous speakers, which can ultimately be fed to a voice-command recognition engine for controlling electronic systems. On a device level, we developed flexible PVDF microphones, which were used to create a large-area microphone array. On a circuit level we developed localized a-Si TFT amplifiers, and a custom CMOS IC, for system control, sensor readout and digitization. On a signal processing level we developed an algorithm for blind source separation in a real, reverberant room, based on beamforming and binary masking. It requires no knowledge about the location of the speakers or microphones. Instead, it uses cluster analysis techniques to determine the time delays for beamforming; thus, adapting to the unique acoustic environment of the room.

Future electro-optical sensors and processing in urban operations

NASA Astrophysics Data System (ADS)

Grönwall, Christina; Schwering, Piet B.; Rantakokko, Jouni; Benoist, Koen W.; Kemp, Rob A. W.; Steinvall, Ove; Letalick, Dietmar; Björkert, Stefan

2013-10-01

In the electro-optical sensors and processing in urban operations (ESUO) study we pave the way for the European Defence Agency (EDA) group of Electro-Optics experts (IAP03) for a common understanding of the optimal distribution of processing functions between the different platforms. Combinations of local, distributed and centralized processing are proposed. In this way one can match processing functionality to the required power, and available communication systems data rates, to obtain the desired reaction times. In the study, three priority scenarios were defined. For these scenarios, present-day and future sensors and signal processing technologies were studied. The priority scenarios were camp protection, patrol and house search. A method for analyzing information quality in single and multi-sensor systems has been applied. A method for estimating reaction times for transmission of data through the chain of command has been proposed and used. These methods are documented and can be used to modify scenarios, or be applied to other scenarios. Present day data processing is organized mainly locally. Very limited exchange of information with other platforms is present; this is performed mainly at a high information level. Main issues that arose from the analysis of present-day systems and methodology are the slow reaction time due to the limited field of view of present-day sensors and the lack of robust automated processing. Efficient handover schemes between wide and narrow field of view sensors may however reduce the delay times. The main effort in the study was in forecasting the signal processing of EO-sensors in the next ten to twenty years. Distributed processing is proposed between hand-held and vehicle based sensors. This can be accompanied by cloud processing on board several vehicles. Additionally, to perform sensor fusion on sensor data originating from different platforms, and making full use of UAV imagery, a combination of distributed and centralized processing is essential. There is a central role for sensor fusion of heterogeneous sensors in future processing. The changes that occur in the urban operations of the future due to the application of these new technologies will be the improved quality of information, with shorter reaction time, and with lower operator load.

Temperature variability is integrated by a spatially embedded decision-making center to break dormancy in Arabidopsis seeds.

PubMed

Topham, Alexander T; Taylor, Rachel E; Yan, Dawei; Nambara, Eiji; Johnston, Iain G; Bassel, George W

2017-06-20

Plants perceive and integrate information from the environment to time critical transitions in their life cycle. Some mechanisms underlying this quantitative signal processing have been described, whereas others await discovery. Seeds have evolved a mechanism to integrate environmental information by regulating the abundance of the antagonistically acting hormones abscisic acid (ABA) and gibberellin (GA). Here, we show that hormone metabolic interactions and their feedbacks are sufficient to create a bistable developmental fate switch in Arabidopsis seeds. A digital single-cell atlas mapping the distribution of hormone metabolic and response components revealed their enrichment within the embryonic radicle, identifying the presence of a decision-making center within dormant seeds. The responses to both GA and ABA were found to occur within distinct cell types, suggesting cross-talk occurs at the level of hormone transport between these signaling centers. We describe theoretically, and demonstrate experimentally, that this spatial separation within the decision-making center is required to process variable temperature inputs from the environment to promote the breaking of dormancy. In contrast to other noise-filtering systems, including human neurons, the functional role of this spatial embedding is to leverage variability in temperature to transduce a fate-switching signal within this biological system. Fluctuating inputs therefore act as an instructive signal for seeds, enhancing the accuracy with which plants are established in ecosystems, and distributed computation within the radicle underlies this signal integration mechanism.

Temperature variability is integrated by a spatially embedded decision-making center to break dormancy in Arabidopsis seeds

PubMed Central

Topham, Alexander T.; Taylor, Rachel E.; Yan, Dawei; Nambara, Eiji; Johnston, Iain G.

2017-01-01

Plants perceive and integrate information from the environment to time critical transitions in their life cycle. Some mechanisms underlying this quantitative signal processing have been described, whereas others await discovery. Seeds have evolved a mechanism to integrate environmental information by regulating the abundance of the antagonistically acting hormones abscisic acid (ABA) and gibberellin (GA). Here, we show that hormone metabolic interactions and their feedbacks are sufficient to create a bistable developmental fate switch in Arabidopsis seeds. A digital single-cell atlas mapping the distribution of hormone metabolic and response components revealed their enrichment within the embryonic radicle, identifying the presence of a decision-making center within dormant seeds. The responses to both GA and ABA were found to occur within distinct cell types, suggesting cross-talk occurs at the level of hormone transport between these signaling centers. We describe theoretically, and demonstrate experimentally, that this spatial separation within the decision-making center is required to process variable temperature inputs from the environment to promote the breaking of dormancy. In contrast to other noise-filtering systems, including human neurons, the functional role of this spatial embedding is to leverage variability in temperature to transduce a fate-switching signal within this biological system. Fluctuating inputs therefore act as an instructive signal for seeds, enhancing the accuracy with which plants are established in ecosystems, and distributed computation within the radicle underlies this signal integration mechanism. PMID:28584126

Complete fourier direct magnetic resonance imaging (CFD-MRI) for diffusion MRI

PubMed Central

Özcan, Alpay

2013-01-01

The foundation for an accurate and unifying Fourier-based theory of diffusion weighted magnetic resonance imaging (DW–MRI) is constructed by carefully re-examining the first principles of DW–MRI signal formation and deriving its mathematical model from scratch. The derivations are specifically obtained for DW–MRI signal by including all of its elements (e.g., imaging gradients) using complex values. Particle methods are utilized in contrast to conventional partial differential equations approach. The signal is shown to be the Fourier transform of the joint distribution of number of the magnetic moments (at a given location at the initial time) and magnetic moment displacement integrals. In effect, the k-space is augmented by three more dimensions, corresponding to the frequency variables dual to displacement integral vectors. The joint distribution function is recovered by applying the Fourier transform to the complete high-dimensional data set. In the process, to obtain a physically meaningful real valued distribution function, phase corrections are applied for the re-establishment of Hermitian symmetry in the signal. Consequently, the method is fully unconstrained and directly presents the distribution of displacement integrals without any assumptions such as symmetry or Markovian property. The joint distribution function is visualized with isosurfaces, which describe the displacement integrals, overlaid on the distribution map of the number of magnetic moments with low mobility. The model provides an accurate description of the molecular motion measurements via DW–MRI. The improvement of the characterization of tissue microstructure leads to a better localization, detection and assessment of biological properties such as white matter integrity. The results are demonstrated on the experimental data obtained from an ex vivo baboon brain. PMID:23596401

The effect of signal variability on the histograms of anthropomorphic channel outputs: factors resulting in non-normally distributed data

NASA Astrophysics Data System (ADS)

Elshahaby, Fatma E. A.; Ghaly, Michael; Jha, Abhinav K.; Frey, Eric C.

2015-03-01

Model Observers are widely used in medical imaging for the optimization and evaluation of instrumentation, acquisition parameters and image reconstruction and processing methods. The channelized Hotelling observer (CHO) is a commonly used model observer in nuclear medicine and has seen increasing use in other modalities. An anthropmorphic CHO consists of a set of channels that model some aspects of the human visual system and the Hotelling Observer, which is the optimal linear discriminant. The optimality of the CHO is based on the assumption that the channel outputs for data with and without the signal present have a multivariate normal distribution with equal class covariance matrices. The channel outputs result from the dot product of channel templates with input images and are thus the sum of a large number of random variables. The central limit theorem is thus often used to justify the assumption that the channel outputs are normally distributed. In this work, we aim to examine this assumption for realistically simulated nuclear medicine images when various types of signal variability are present.

Time difference of arrival estimation of microseismic signals based on alpha-stable distribution

NASA Astrophysics Data System (ADS)

Jia, Rui-Sheng; Gong, Yue; Peng, Yan-Jun; Sun, Hong-Mei; Zhang, Xing-Li; Lu, Xin-Ming

2018-05-01

Microseismic signals are generally considered to follow the Gauss distribution. A comparison of the dynamic characteristics of sample variance and the symmetry of microseismic signals with the signals which follow α-stable distribution reveals that the microseismic signals have obvious pulse characteristics and that the probability density curve of the microseismic signal is approximately symmetric. Thus, the hypothesis that microseismic signals follow the symmetric α-stable distribution is proposed. On the premise of this hypothesis, the characteristic exponent α of the microseismic signals is obtained by utilizing the fractional low-order statistics, and then a new method of time difference of arrival (TDOA) estimation of microseismic signals based on fractional low-order covariance (FLOC) is proposed. Upon applying this method to the TDOA estimation of Ricker wavelet simulation signals and real microseismic signals, experimental results show that the FLOC method, which is based on the assumption of the symmetric α-stable distribution, leads to enhanced spatial resolution of the TDOA estimation relative to the generalized cross correlation (GCC) method, which is based on the assumption of the Gaussian distribution.

Correction of complex nonlinear signal response from a pixel array detector

PubMed Central

van Driel, Tim Brandt; Herrmann, Sven; Carini, Gabriella; Nielsen, Martin Meedom; Lemke, Henrik Till

2015-01-01

The pulsed free-electron laser light sources represent a new challenge to photon area detectors due to the intrinsic spontaneous X-ray photon generation process that makes single-pulse detection necessary. Intensity fluctuations up to 100% between individual pulses lead to high linearity requirements in order to distinguish small signal changes. In real detectors, signal distortions as a function of the intensity distribution on the entire detector can occur. Here a robust method to correct this nonlinear response in an area detector is presented for the case of exposures to similar signals. The method is tested for the case of diffuse scattering from liquids where relevant sub-1% signal changes appear on the same order as artifacts induced by the detector electronics. PMID:25931072

Correction of complex nonlinear signal response from a pixel array detector.

PubMed

van Driel, Tim Brandt; Herrmann, Sven; Carini, Gabriella; Nielsen, Martin Meedom; Lemke, Henrik Till

2015-05-01

The pulsed free-electron laser light sources represent a new challenge to photon area detectors due to the intrinsic spontaneous X-ray photon generation process that makes single-pulse detection necessary. Intensity fluctuations up to 100% between individual pulses lead to high linearity requirements in order to distinguish small signal changes. In real detectors, signal distortions as a function of the intensity distribution on the entire detector can occur. Here a robust method to correct this nonlinear response in an area detector is presented for the case of exposures to similar signals. The method is tested for the case of diffuse scattering from liquids where relevant sub-1% signal changes appear on the same order as artifacts induced by the detector electronics.

Structural health monitoring of plates with surface features using guided ultrasonic waves

NASA Astrophysics Data System (ADS)

Fromme, P.

2009-03-01

Distributed array systems for guided ultrasonic waves offer an efficient way for the long-term monitoring of the structural integrity of large plate-like structures. The measurement concept involving baseline subtraction has been demonstrated under laboratory conditions. For the application to real technical structures it needs to be shown that the methodology works equally well in the presence of structural and surface features. Problems employing this structural health monitoring concept can occur due to the presence of additional changes in the signal reflected at undamaged parts of the structure. The influence of the signal processing parameters and transducer placement on the damage detection and localization accuracy is discussed. The use of permanently attached, distributed sensors for the A0 Lamb wave mode has been investigated. Results are presented using experimental data obtained from laboratory measurements and Finite Element simulated signals for a large steel plate with a welded stiffener.

Analysis and demonstration of vibration waveform reconstruction in distributed optical fiber vibration sensing system

NASA Astrophysics Data System (ADS)

Zhu, Hui; Shan, Xuekang; Sun, Xiaohan

2017-10-01

A method for reconstructing the vibration waveform from the optical time-domain backscattering pulses in the distributed optical fiber sensing system (DOFSS) is proposed, which allows for extracting and recovering the external vibration signal from the tested pulses by analog signal processing, so that can obtain vibration location and waveform simultaneously. We establish the response model of DOFSS to the external vibration and analyze the effects of system parameters on the operational performance. The main parts of the DOFSS are optimized, including delay fiber length and wavelength, to improve the sensitivity of the system. The experimental system is set up and the vibration amplitudes and reconstructed waveforms are fit well with the original driving signal. The experimental results demonstrate that the performance of vibration waveform reconstruction is good with SNR of 15 dB whenever the external vibrations with different intensities and frequencies exert on the sensing fiber.

Optimization of chlorine fluxing process for magnesium removal from molten aluminum

NASA Astrophysics Data System (ADS)

Fu, Qian

High-throughput and low operational cost are the keys to a successful industrial process. Much aluminum is now recycled in the form of used beverage cans and this aluminum is of alloys that contain high levels of magnesium. It is common practice to "demag" the metal by injecting chlorine that preferentially reacts with the magnesium. In the conventional chlorine fluxing processes, low reaction efficiency results in excessive reactive gas emissions. In this study, through an experimental investigation of the reaction kinetics involved in this process, a mathematical model is set up for the purpose of process optimization. A feedback controlled chlorine reduction process strategy is suggested for demagging the molten aluminum to the desired magnesium level without significant gas emissions. This strategy also needs the least modification of the existing process facility. The suggested process time will only be slightly longer than conventional methods and chlorine usage and emissions will be reduced. In order to achieve process optimization through novel designs in any fluxing process, a system is necessary for measuring the bubble distribution in liquid metals. An electro-resistivity probe described in the literature has low accuracy and its capability to measure bubble distribution has not yet been fully demonstrated. A capacitance bubble probe was designed for bubble measurements in molten metals. The probe signal was collected and processed digitally. Higher accuracy was obtained by higher discrimination against corrupted signals. A single-size bubble experiment in Belmont metal was designed to reveal the characteristic response of the capacitance probe. This characteristic response fits well with a theoretical model. It is suggested that using a properly designed deconvolution process, the actual bubble size distribution can be calculated. The capacitance probe was used to study some practical bubble generation devices. Preliminary results on bubble distribution generated by a porous plug in Belmont metal showed bubbles much bigger than those in a water model. Preliminary results in molten aluminum showed that the probe was applicable in this harsh environment. An interesting bubble coalescence phenomenon was also observed in both Belmont metal and molten aluminum.

Self-Defense Distributed Engagement Coordinator

DTIC Science & Technology

2016-02-01

its countermeasures. Whether a missile is defeated with an interceptor, undermined by a signal jammer, or diverted by a decoy, there is Self - Defense ...anti-ship threats and recommends actions to the personnel coordinating ship self - defense . This tool was recognized with a 2015 R&D 100 Award. a cost...reloading process, and may not be possible at all. The Self - Defense Distributed Engagement Coordinator (SDDEC) is designed to provide automated battle

Advancing Underwater Acoustic Communication for Autonomous Distributed Networks via Sparse Channel Sensing, Coding, and Navigation Support

DTIC Science & Technology

2013-09-30

underwater acoustic communication technologies for autonomous distributed underwater networks, through innovative signal processing, coding, and navigation...in real enviroments , an offshore testbed has been developed to conduct field experimetns. The testbed consists of four nodes and has been deployed...Leadership by the Connecticut Technology Council. Dr. Zhaohui Wang joined the faculty of the Department of Electrical and Computer Engineering at

Assessment of Muscle Fatigue from TF Distributions of SEMG Signals

DTIC Science & Technology

2008-06-01

Wigner - Ville distribution ( WVD ) holds the...techniques used to build a TF distribution of SEMG signals, namely spectrogram, Wigner - Ville , Choi- Williams and smoothed pseudo Wigner - Ville . SEMG signals...spectrogram but also other Cohen’s class TF distributions , such as the Choi-Williams distribution (CWD) and the smoothed pseudo Wigner - Ville distribution

On the use of distributed sensing in control of large flexible spacecraft

NASA Technical Reports Server (NTRS)

Montgomery, Raymond C.; Ghosh, Dave

1990-01-01

Distributed processing technology is being developed to process signals from distributed sensors using distributed computations. Thiw work presents a scheme for calculating the operators required to emulate a conventional Kalman filter and regulator using such a computer. The scheme makes use of conventional Kalman theory as applied to the control of large flexible structures. The required computation of the distributed operators given the conventional Kalman filter and regulator is explained. A straightforward application of this scheme may lead to nonsmooth operators whose convergence is not apparent. This is illustrated by application to the Mini-Mast, a large flexible truss at the Langley Research Center used for research in structural dynamics and control. Techniques for developing smooth operators are presented. These involve spatial filtering as well as adjusting the design constants in the Kalman theory. Results are presented that illustrate the degree of smoothness achieved.

Ghost image in enhanced self-heterodyne synthetic aperture imaging ladar

NASA Astrophysics Data System (ADS)

Zhang, Guo; Sun, Jianfeng; Zhou, Yu; Lu, Zhiyong; Li, Guangyuan; Xu, Mengmeng; Zhang, Bo; Lao, Chenzhe; He, Hongyu

2018-03-01

The enhanced self-heterodyne synthetic aperture imaging ladar (SAIL) self-heterodynes two polarization-orthogonal echo signals to eliminate the phase disturbance caused by atmospheric turbulence and mechanical trembling, uses heterodyne receiver instead of self-heterodyne receiver to improve signal-to-noise ratio. The principle and structure of the enhanced self-heterodyne SAIL are presented. The imaging process of enhanced self-heterodyne SAIL for distributed target is also analyzed. In enhanced self-heterodyne SAIL, the phases of two orthogonal-polarization beams are modulated by four cylindrical lenses in transmitter to improve resolutions in orthogonal direction and travel direction, which will generate ghost image. The generation process of ghost image in enhanced self-heterodyne SAIL is mathematically detailed, and a method of eliminating ghost image is also presented, which is significant for far-distance imaging. A number of experiments of enhanced self-heterodyne SAIL for distributed target are presented, these experimental results verify the theoretical analysis of enhanced self-heterodyne SAIL. The enhanced self-heterodyne SAIL has the capability to eliminate the influence from the atmospheric turbulence and mechanical trembling, has high advantage in detecting weak signals, and has promising application for far-distance ladar imaging.

SGR-like behaviour of the repeating FRB 121102

NASA Astrophysics Data System (ADS)

Wang, F. Y.; Yu, H.

2017-03-01

Fast radio bursts (FRBs) are millisecond-duration radio signals occurring at cosmological distances. However the physical model of FRBs is mystery, many models have been proposed. Here we study the frequency distributions of peak flux, fluence, duration and waiting time for the repeating FRB 121102. The cumulative distributions of peak flux, fluence and duration show power-law forms. The waiting time distribution also shows power-law distribution, and is consistent with a non-stationary Poisson process. These distributions are similar as those of soft gamma repeaters (SGRs). We also use the statistical results to test the proposed models for FRBs. These distributions are consistent with the predictions from avalanche models of slowly driven nonlinear dissipative systems.

Systems Imaging of the Immune Synapse.

PubMed

Ambler, Rachel; Ruan, Xiangtao; Murphy, Robert F; Wülfing, Christoph

2017-01-01

Three-dimensional live cell imaging of the interaction of T cells with antigen-presenting cells (APCs) visualizes the subcellular distributions of signaling intermediates during T cell activation at thousands of resolved positions within a cell. These information-rich maps of local protein concentrations are a valuable resource in understanding T cell signaling. Here, we describe a protocol for the efficient acquisition of such imaging data and their computational processing to create four-dimensional maps of local concentrations. This protocol allows quantitative analysis of T cell signaling as it occurs inside live cells with resolution in time and space across thousands of cells.

Steady state statistical correlations predict bistability in reaction motifs.

PubMed

Chakravarty, Suchana; Barik, Debashis

2017-03-28

Various cellular decision making processes are regulated by bistable switches that take graded input signals and convert them to binary all-or-none responses. Traditionally, a bistable switch generated by a positive feedback loop is characterized either by a hysteretic signal response curve with two distinct signaling thresholds or by characterizing the bimodality of the response distribution in the bistable region. To identify the intrinsic bistability of a feedback regulated network, here we propose that bistability can be determined by correlating higher order moments and cumulants (≥2) of the joint steady state distributions of two components connected in a positive feedback loop. We performed stochastic simulations of four feedback regulated models with intrinsic bistability and we show that for a bistable switch with variation of the signal dose, the steady state variance vs. covariance adopts a signatory cusp-shaped curve. Further, we find that the (n + 1)th order cross-cumulant vs. nth order cross-cumulant adopts a closed loop structure for at least n = 3. We also propose that our method is capable of identifying systems without intrinsic bistability even though the system may show bimodality in the marginal response distribution. The proposed method can be used to analyze single cell protein data measured at steady state from experiments such as flow cytometry.

True-Triaxial Experimental Study of the Evolutionary Features of the Acoustic Emissions and Sounds of Rockburst Processes

NASA Astrophysics Data System (ADS)

Su, Guoshao; Shi, Yanjiong; Feng, Xiating; Jiang, Jianqing; Zhang, Jie; Jiang, Quan

2018-02-01

Rockbursts are markedly characterized by the ejection of rock fragments from host rocks at certain speeds. The rockburst process is always accompanied by acoustic signals that include acoustic emissions (AE) and sounds. A deep insight into the evolutionary features of AE and sound signals is important to improve the accuracy of rockburst prediction. To investigate the evolutionary features of AE and sound signals, rockburst tests on granite rock specimens under true-triaxial loading conditions were performed using an improved rockburst testing system, and the AE and sounds during rockburst development were recorded and analyzed. The results show that the evolutionary features of the AE and sound signals were obvious and similar. On the eve of a rockburst, a `quiescent period' could be observed in both the evolutionary process of the AE hits and the sound waveform. Furthermore, the time-dependent fractal dimensions of the AE hits and sound amplitude both showed a tendency to continuously decrease on the eve of the rockbursts. In addition, on the eve of the rockbursts, the main frequency of the AE and sound signals both showed decreasing trends, and the frequency spectrum distributions were both characterized by low amplitudes, wide frequency bands and multiple peak shapes. Thus, the evolutionary features of sound signals on the eve of rockbursts, as well as that of AE signals, can be used as beneficial information for rockburst prediction.

Agile waveforms for joint SAR-GMTI processing

NASA Astrophysics Data System (ADS)

Jaroszewski, Steven; Corbeil, Allan; McMurray, Stephen; Majumder, Uttam; Bell, Mark R.; Corbeil, Jeffrey; Minardi, Michael

2016-05-01

Wideband radar waveforms that employ spread-spectrum techniques were investigated and experimentally tested. The waveforms combine bi-phase coding with a traditional LFM chirp and are applicable to joint SAR-GMTI processing. After de-spreading, the received signals can be processed to support simultaneous GMTI and high resolution SAR imaging missions by airborne radars. The spread spectrum coding techniques can provide nearly orthogonal waveforms and offer enhanced operations in some environments by distributing the transmitted energy over a large instantaneous bandwidth. The LFM component offers the desired Doppler tolerance. In this paper, the waveforms are formulated and a shift-register approach for de-spreading the received signals is described. Hardware loop-back testing has shown the feasibility of using these waveforms in experimental radar test bed.

The influence of laser pulse duration and energy on ICP-MS signal intensity, elemental fractionation, and particle size distribution in NIR fs-LA-ICP-MS

PubMed Central

Diwakar, Prasoon K.; Harilal, Sivanandan S.; LaHaye, Nicole L.; Hassanein, Ahmed; Kulkarni, Pramod

2015-01-01

Laser parameters, typically wavelength, pulse width, irradiance, repetition rate, and pulse energy, are critical parameters which influence the laser ablation process and thereby influence the LA-ICP-MS signal. In recent times, femtosecond laser ablation has gained popularity owing to the reduction in fractionation related issues and improved analytical performance which can provide matrix-independent sampling. The advantage offered by fs-LA is due to shorter pulse duration of the laser as compared to the phonon relaxation time and heat diffusion time. Hence the thermal effects are minimized in fs-LA. Recently, fs-LA-ICP-MS demonstrated improved analytical performance as compared to ns-LA-ICP-MS, but detailed mechanisms and processes are still not clearly understood. Improvement of fs-LA-ICP-MS over ns-LA-ICP-MS elucidates the importance of laser pulse duration and related effects on the ablation process. In this study, we have investigated the influence of laser pulse width (40 fs to 0.3 ns) and energy on LA-ICP-MS signal intensity and repeatability using a brass sample. Experiments were performed in single spot ablation mode as well as rastering ablation mode to monitor the Cu/Zn ratio. The recorded ICP-MS signal was correlated with total particle counts generated during laser ablation as well as particle size distribution. Our results show the importance of pulse width effects in the fs regime that becomes more pronounced when moving from femtosecond to picosecond and nanosecond regimes. PMID:26664120

Matched signal detection on graphs: Theory and application to brain imaging data classification.

PubMed

Hu, Chenhui; Sepulcre, Jorge; Johnson, Keith A; Fakhri, Georges E; Lu, Yue M; Li, Quanzheng

2016-01-15

Motivated by recent progress in signal processing on graphs, we have developed a matched signal detection (MSD) theory for signals with intrinsic structures described by weighted graphs. First, we regard graph Laplacian eigenvalues as frequencies of graph-signals and assume that the signal is in a subspace spanned by the first few graph Laplacian eigenvectors associated with lower eigenvalues. The conventional matched subspace detector can be applied to this case. Furthermore, we study signals that may not merely live in a subspace. Concretely, we consider signals with bounded variation on graphs and more general signals that are randomly drawn from a prior distribution. For bounded variation signals, the test is a weighted energy detector. For the random signals, the test statistic is the difference of signal variations on associated graphs, if a degenerate Gaussian distribution specified by the graph Laplacian is adopted. We evaluate the effectiveness of the MSD on graphs both with simulated and real data sets. Specifically, we apply MSD to the brain imaging data classification problem of Alzheimer's disease (AD) based on two independent data sets: 1) positron emission tomography data with Pittsburgh compound-B tracer of 30 AD and 40 normal control (NC) subjects, and 2) resting-state functional magnetic resonance imaging (R-fMRI) data of 30 early mild cognitive impairment and 20 NC subjects. Our results demonstrate that the MSD approach is able to outperform the traditional methods and help detect AD at an early stage, probably due to the success of exploiting the manifold structure of the data. Copyright © 2015. Published by Elsevier Inc.

Signal optimization in urban transport: A totally asymmetric simple exclusion process with traffic lights.

PubMed

Arita, Chikashi; Foulaadvand, M Ebrahim; Santen, Ludger

2017-03-01

We consider the exclusion process on a ring with time-dependent defective bonds at which the hopping rate periodically switches between zero and one. This system models main roads in city traffics, intersecting with perpendicular streets. We explore basic properties of the system, in particular dependence of the vehicular flow on the parameters of signalization as well as the system size and the car density. We investigate various types of the spatial distribution of the vehicular density, and show existence of a shock profile. We also measure waiting time behind traffic lights, and examine its relationship with the traffic flow.

Signal optimization in urban transport: A totally asymmetric simple exclusion process with traffic lights

NASA Astrophysics Data System (ADS)

Arita, Chikashi; Foulaadvand, M. Ebrahim; Santen, Ludger

2017-03-01

We consider the exclusion process on a ring with time-dependent defective bonds at which the hopping rate periodically switches between zero and one. This system models main roads in city traffics, intersecting with perpendicular streets. We explore basic properties of the system, in particular dependence of the vehicular flow on the parameters of signalization as well as the system size and the car density. We investigate various types of the spatial distribution of the vehicular density, and show existence of a shock profile. We also measure waiting time behind traffic lights, and examine its relationship with the traffic flow.

Bayesian estimation of self-similarity exponent

NASA Astrophysics Data System (ADS)

Makarava, Natallia; Benmehdi, Sabah; Holschneider, Matthias

2011-08-01

In this study we propose a Bayesian approach to the estimation of the Hurst exponent in terms of linear mixed models. Even for unevenly sampled signals and signals with gaps, our method is applicable. We test our method by using artificial fractional Brownian motion of different length and compare it with the detrended fluctuation analysis technique. The estimation of the Hurst exponent of a Rosenblatt process is shown as an example of an H-self-similar process with non-Gaussian dimensional distribution. Additionally, we perform an analysis with real data, the Dow-Jones Industrial Average closing values, and analyze its temporal variation of the Hurst exponent.

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

van Driel, Tim Brandt; Herrmann, Sven; Carini, Gabriella

The pulsed free-electron laser light sources represent a new challenge to photon area detectors due to the intrinsic spontaneous X-ray photon generation process that makes single-pulse detection necessary. Intensity fluctuations up to 100% between individual pulses lead to high linearity requirements in order to distinguish small signal changes. In real detectors, signal distortions as a function of the intensity distribution on the entire detector can occur. Here a robust method to correct this nonlinear response in an area detector is presented for the case of exposures to similar signals. The method is tested for the case of diffuse scattering frommore » liquids where relevant sub-1% signal changes appear on the same order as artifacts induced by the detector electronics.« less

Common Randomness Principles of Secrecy

ERIC Educational Resources Information Center

Tyagi, Himanshu

2013-01-01

This dissertation concerns the secure processing of distributed data by multiple terminals, using interactive public communication among themselves, in order to accomplish a given computational task. In the setting of a probabilistic multiterminal source model in which several terminals observe correlated random signals, we analyze secure…

Decision Processes in Discrimination: Fundamental Misrepresentations of Signal Detection Theory

NASA Technical Reports Server (NTRS)

Balakrishnan, J. D.

1998-01-01

In the first part of this article, I describe a new approach to studying decision making in discrimination tasks that does not depend on the technical assumptions of signal detection theory (e.g., normality of the encoding distributions). Applying these new distribution-free tests to data from three experiments, I show that base rate and payoff manipulations had substantial effects on the participants' encoding distributions but no effect on their decision rules, which were uniformly unbiased in equal and unequal base rate conditions and in symmetric and asymmetric payoff conditions. In the second part of the article, I show that this seemingly paradoxical result is readily explained by the sequential sampling models of discrimination. I then propose a new, "model-free" test for response bias that seems to more properly identify both the nature and direction of the biases induced by the classical bias manipulations.

A Theoretical Study and Numerical Simulation of a Quasi-Distributed Sensor Based on the Low-Finesse Fabry-Perot Interferometer: Frequency-Division Multiplexing

PubMed Central

Guillen Bonilla, José Trinidad; Guillen Bonilla, Alex; Rodríguez Betancourtt, Verónica M.; Guillen Bonilla, Héctor; Casillas Zamora, Antonio

2017-01-01

The application of the sensor optical fibers in the areas of scientific instrumentation and industrial instrumentation is very attractive due to its numerous advantages. In the industry of civil engineering for example, quasi-distributed sensors made with optical fiber are used for reliable strain and temperature measurements. Here, a quasi-distributed sensor in the frequency domain is discussed. The sensor consists of a series of low-finesse Fabry-Perot interferometers where each Fabry-Perot interferometer acts as a local sensor. Fabry-Perot interferometers are formed by pairs of identical low reflective Bragg gratings imprinted in a single mode fiber. All interferometer sensors have different cavity length, provoking frequency-domain multiplexing. The optical signal represents the superposition of all interference patterns which can be decomposed using the Fourier transform. The frequency spectrum was analyzed and sensor’s properties were defined. Following that, a quasi-distributed sensor was numerically simulated. Our sensor simulation considers sensor properties, signal processing, noise system, and instrumentation. The numerical results show the behavior of resolution vs. signal-to-noise ratio. From our results, the Fabry-Perot sensor has high resolution and low resolution. Both resolutions are conceivable because the Fourier Domain Phase Analysis (FDPA) algorithm elaborates two evaluations of Bragg wavelength shift. PMID:28420083

A Theoretical Study and Numerical Simulation of a Quasi-Distributed Sensor Based on the Low-Finesse Fabry-Perot Interferometer: Frequency-Division Multiplexing.

PubMed

Guillen Bonilla, José Trinidad; Guillen Bonilla, Alex; Rodríguez Betancourtt, Verónica M; Guillen Bonilla, Héctor; Casillas Zamora, Antonio

2017-04-14

The application of the sensor optical fibers in the areas of scientific instrumentation and industrial instrumentation is very attractive due to its numerous advantages. In the industry of civil engineering for example, quasi-distributed sensors made with optical fiber are used for reliable strain and temperature measurements. Here, a quasi-distributed sensor in the frequency domain is discussed. The sensor consists of a series of low-finesse Fabry-Perot interferometers where each Fabry-Perot interferometer acts as a local sensor. Fabry-Perot interferometers are formed by pairs of identical low reflective Bragg gratings imprinted in a single mode fiber. All interferometer sensors have different cavity length, provoking frequency-domain multiplexing. The optical signal represents the superposition of all interference patterns which can be decomposed using the Fourier transform. The frequency spectrum was analyzed and sensor's properties were defined. Following that, a quasi-distributed sensor was numerically simulated. Our sensor simulation considers sensor properties, signal processing, noise system, and instrumentation. The numerical results show the behavior of resolution vs. signal-to-noise ratio. From our results, the Fabry-Perot sensor has high resolution and low resolution. Both resolutions are conceivable because the Fourier Domain Phase Analysis (FDPA) algorithm elaborates two evaluations of Bragg wavelength shift.

Research on the feature extraction and pattern recognition of the distributed optical fiber sensing signal

NASA Astrophysics Data System (ADS)

Wang, Bingjie; Sun, Qi; Pi, Shaohua; Wu, Hongyan

2014-09-01

In this paper, feature extraction and pattern recognition of the distributed optical fiber sensing signal have been studied. We adopt Mel-Frequency Cepstral Coefficient (MFCC) feature extraction, wavelet packet energy feature extraction and wavelet packet Shannon entropy feature extraction methods to obtain sensing signals (such as speak, wind, thunder and rain signals, etc.) characteristic vectors respectively, and then perform pattern recognition via RBF neural network. Performances of these three feature extraction methods are compared according to the results. We choose MFCC characteristic vector to be 12-dimensional. For wavelet packet feature extraction, signals are decomposed into six layers by Daubechies wavelet packet transform, in which 64 frequency constituents as characteristic vector are respectively extracted. In the process of pattern recognition, the value of diffusion coefficient is introduced to increase the recognition accuracy, while keeping the samples for testing algorithm the same. Recognition results show that wavelet packet Shannon entropy feature extraction method yields the best recognition accuracy which is up to 97%; the performance of 12-dimensional MFCC feature extraction method is less satisfactory; the performance of wavelet packet energy feature extraction method is the worst.

Distributed ice accretion sensor for smart aircraft structures

NASA Technical Reports Server (NTRS)

Gerardi, J. J.; Hickman, G. A.

1989-01-01

A distributed ice accretion sensor is presented, based on the concept of smart structures. Ice accretion is determined using spectral techniques to process signals from piezoelectric sensors integral to the airfoil skin. Frequency shifts in the leading edge structural skin modes are correlated to ice thickness. It is suggested that this method may be used to detect ice over large areas with minimal hardware. Results are presented from preliminary tests to measure simulated ice growth.

Medical gamma ray imaging

DOEpatents

Osborne, Louis S.; Lanza, Richard C.

1984-01-01

A method and apparatus for determining the distribution of a position-emitting radioisotope into an object, the apparatus consisting of a wire mesh radiation converter, an ionizable gas for propagating ionization events caused by electrodes released by the converter, a drift field, a spatial position detector and signal processing circuitry for correlating near-simultaneous ionization events and determining their time differences, whereby the position sources of back-to-back collinear radiation can be located and a distribution image constructed.

Numerical modelling of distributed vibration sensor based on phase-sensitive OTDR

NASA Astrophysics Data System (ADS)

Masoudi, A.; Newson, T. P.

2017-04-01

A Distributed Vibration Sensor Based on Phase-Sensitive OTDR is numerically modeled. The advantage of modeling the building blocks of the sensor individually and combining the blocks to analyse the behavior of the sensing system is discussed. It is shown that the numerical model can accurately imitate the response of the experimental setup to dynamic perturbations a signal processing procedure similar to that used to extract the phase information from sensing setup.

Derivation from first principles of the statistical distribution of the mass peak intensities of MS data.

PubMed

Ipsen, Andreas

2015-02-03

Despite the widespread use of mass spectrometry (MS) in a broad range of disciplines, the nature of MS data remains very poorly understood, and this places important constraints on the quality of MS data analysis as well as on the effectiveness of MS instrument design. In the following, a procedure for calculating the statistical distribution of the mass peak intensity for MS instruments that use analog-to-digital converters (ADCs) and electron multipliers is presented. It is demonstrated that the physical processes underlying the data-generation process, from the generation of the ions to the signal induced at the detector, and on to the digitization of the resulting voltage pulse, result in data that can be well-approximated by a Gaussian distribution whose mean and variance are determined by physically meaningful instrumental parameters. This allows for a very precise understanding of the signal-to-noise ratio of mass peak intensities and suggests novel ways of improving it. Moreover, it is a prerequisite for being able to address virtually all data analytical problems in downstream analyses in a statistically rigorous manner. The model is validated with experimental data.

The bag-of-frames approach to audio pattern recognition: a sufficient model for urban soundscapes but not for polyphonic music.

PubMed

Aucouturier, Jean-Julien; Defreville, Boris; Pachet, François

2007-08-01

The "bag-of-frames" approach (BOF) to audio pattern recognition represents signals as the long-term statistical distribution of their local spectral features. This approach has proved nearly optimal for simulating the auditory perception of natural and human environments (or soundscapes), and is also the most predominent paradigm to extract high-level descriptions from music signals. However, recent studies show that, contrary to its application to soundscape signals, BOF only provides limited performance when applied to polyphonic music signals. This paper proposes to explicitly examine the difference between urban soundscapes and polyphonic music with respect to their modeling with the BOF approach. First, the application of the same measure of acoustic similarity on both soundscape and music data sets confirms that the BOF approach can model soundscapes to near-perfect precision, and exhibits none of the limitations observed in the music data set. Second, the modification of this measure by two custom homogeneity transforms reveals critical differences in the temporal and statistical structure of the typical frame distribution of each type of signal. Such differences may explain the uneven performance of BOF algorithms on soundscapes and music signals, and suggest that their human perception rely on cognitive processes of a different nature.

Real-time, in situ monitoring of nanoporation using electric field-induced acoustic signal

NASA Astrophysics Data System (ADS)

Zarafshani, Ali; Faiz, Rowzat; Samant, Pratik; Zheng, Bin; Xiang, Liangzhong

2018-02-01

The use of nanoporation in reversible or irreversible electroporation, e.g. cancer ablation, is rapidly growing. This technique uses an ultra-short and intense electric pulse to increase the membrane permeability, allowing non-permeant drugs and genes access to the cytosol via nanopores in the plasma membrane. It is vital to create a real-time in situ monitoring technique to characterize this process and answer the need created by the successful electroporation procedure of cancer treatment. All suggested monitoring techniques for electroporation currently are for pre-and post-stimulation exposure with no real-time monitoring during electric field exposure. This study was aimed at developing an innovative technology for real-time in situ monitoring of electroporation based on the typical cell exposure-induced acoustic emissions. The acoustic signals are the result of the electric field, which itself can be used in realtime to characterize the process of electroporation. We varied electric field distribution by varying the electric pulse from 1μ - 100ns and varying the voltage intensity from 0 - 1.2ܸ݇ to energize two electrodes in a bi-polar set-up. An ultrasound transducer was used for collecting acoustic signals around the subject under test. We determined the relative location of the acoustic signals by varying the position of the electrodes relative to the transducer and varying the electric field distribution between the electrodes to capture a variety of acoustic signals. Therefore, the electric field that is utilized in the nanoporation technique also produces a series of corresponding acoustic signals. This offers a novel imaging technique for the real-time in situ monitoring of electroporation that may directly improve treatment efficiency.

Time-frequency analysis of pediatric murmurs

NASA Astrophysics Data System (ADS)

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

1998-05-01

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

Correction of complex nonlinear signal response from a pixel array detector

DOE PAGES

van Driel, Tim Brandt; Herrmann, Sven; Carini, Gabriella; ...

2015-04-22

The pulsed free-electron laser light sources represent a new challenge to photon area detectors due to the intrinsic spontaneous X-ray photon generation process that makes single-pulse detection necessary. Intensity fluctuations up to 100% between individual pulses lead to high linearity requirements in order to distinguish small signal changes. In real detectors, signal distortions as a function of the intensity distribution on the entire detector can occur. Here a robust method to correct this nonlinear response in an area detector is presented for the case of exposures to similar signals. The method is tested for the case of diffuse scattering frommore » liquids where relevant sub-1% signal changes appear on the same order as artifacts induced by the detector electronics.« less

Research on human physiological parameters intelligent clothing based on distributed Fiber Bragg Grating

NASA Astrophysics Data System (ADS)

Miao, Changyun; Shi, Boya; Li, Hongqiang

2008-12-01

A human physiological parameters intelligent clothing is researched with FBG sensor technology. In this paper, the principles and methods of measuring human physiological parameters including body temperature and heart rate in intelligent clothing with distributed FBG are studied, the mathematical models of human physiological parameters measurement are built; the processing method of body temperature and heart rate detection signals is presented; human physiological parameters detection module is designed, the interference signals are filtered out, and the measurement accuracy is improved; the integration of the intelligent clothing is given. The intelligent clothing can implement real-time measurement, processing, storage and output of body temperature and heart rate. It has accurate measurement, portability, low cost, real-time monitoring, and other advantages. The intelligent clothing can realize the non-contact monitoring between doctors and patients, timely find the diseases such as cancer and infectious diseases, and make patients get timely treatment. It has great significance and value for ensuring the health of the elders and the children with language dysfunction.

Identifying and quantifying main components of physiological noise in functional near infrared spectroscopy on the prefrontal cortex.

PubMed

Kirilina, Evgeniya; Yu, Na; Jelzow, Alexander; Wabnitz, Heidrun; Jacobs, Arthur M; Tachtsidis, Ilias

2013-01-01

Functional Near-Infrared Spectroscopy (fNIRS) is a promising method to study functional organization of the prefrontal cortex. However, in order to realize the high potential of fNIRS, effective discrimination between physiological noise originating from forehead skin haemodynamic and cerebral signals is required. Main sources of physiological noise are global and local blood flow regulation processes on multiple time scales. The goal of the present study was to identify the main physiological noise contributions in fNIRS forehead signals and to develop a method for physiological de-noising of fNIRS data. To achieve this goal we combined concurrent time-domain fNIRS and peripheral physiology recordings with wavelet coherence analysis (WCA). Depth selectivity was achieved by analyzing moments of photon time-of-flight distributions provided by time-domain fNIRS. Simultaneously, mean arterial blood pressure (MAP), heart rate (HR), and skin blood flow (SBF) on the forehead were recorded. WCA was employed to quantify the impact of physiological processes on fNIRS signals separately for different time scales. We identified three main processes contributing to physiological noise in fNIRS signals on the forehead. The first process with the period of about 3 s is induced by respiration. The second process is highly correlated with time lagged MAP and HR fluctuations with a period of about 10 s often referred as Mayer waves. The third process is local regulation of the facial SBF time locked to the task-evoked fNIRS signals. All processes affect oxygenated haemoglobin concentration more strongly than that of deoxygenated haemoglobin. Based on these results we developed a set of physiological regressors, which were used for physiological de-noising of fNIRS signals. Our results demonstrate that proposed de-noising method can significantly improve the sensitivity of fNIRS to cerebral signals.

The Arabidopsis LAZY1 Family Plays a Key Role in Gravity Signaling within Statocytes and in Branch Angle Control of Roots and Shoots[OPEN

PubMed Central

Taniguchi, Masatoshi; Furutani, Masahiko; Nishimura, Takeshi; Nakamura, Moritaka; Fushita, Toyohito; Iijima, Kohta; Baba, Kenichiro; Toyota, Masatsugu

2017-01-01

During gravitropism, the directional signal of gravity is perceived by gravity-sensing cells called statocytes, leading to asymmetric distribution of auxin in the responding organs. To identify the genes involved in gravity signaling in statocytes, we performed transcriptome analyses of statocyte-deficient Arabidopsis thaliana mutants and found two candidates from the LAZY1 family, AtLAZY1/LAZY1-LIKE1 (LZY1) and AtDRO3/AtNGR1/LZY2. We showed that LZY1, LZY2, and a paralog AtDRO1/AtNGR2/LZY3 are redundantly involved in gravitropism of the inflorescence stem, hypocotyl, and root. Mutations of LZY genes affected early processes in gravity signal transduction without affecting amyloplast sedimentation. Statocyte-specific expression of LZY genes rescued the mutant phenotype, suggesting that LZY genes mediate gravity signaling in statocytes downstream of amyloplast displacement, leading to the generation of asymmetric auxin distribution in gravity-responding organs. We also found that lzy mutations reversed the growth angle of lateral branches and roots. Moreover, expression of the conserved C-terminal region of LZY proteins also reversed the growth direction of primary roots in the lzy mutant background. In lateral root tips of lzy multiple mutants, asymmetric distribution of PIN3 and auxin response were reversed, suggesting that LZY genes regulate the direction of polar auxin transport in response to gravity through the control of asymmetric PIN3 expression in the root cap columella. PMID:28765510

Processing and Analysis of Multichannel Extracellular Neuronal Signals: State-of-the-Art and Challenges

PubMed Central

Mahmud, Mufti; Vassanelli, Stefano

2016-01-01

In recent years multichannel neuronal signal acquisition systems have allowed scientists to focus on research questions which were otherwise impossible. They act as a powerful means to study brain (dys)functions in in-vivo and in in-vitro animal models. Typically, each session of electrophysiological experiments with multichannel data acquisition systems generate large amount of raw data. For example, a 128 channel signal acquisition system with 16 bits A/D conversion and 20 kHz sampling rate will generate approximately 17 GB data per hour (uncompressed). This poses an important and challenging problem of inferring conclusions from the large amounts of acquired data. Thus, automated signal processing and analysis tools are becoming a key component in neuroscience research, facilitating extraction of relevant information from neuronal recordings in a reasonable time. The purpose of this review is to introduce the reader to the current state-of-the-art of open-source packages for (semi)automated processing and analysis of multichannel extracellular neuronal signals (i.e., neuronal spikes, local field potentials, electroencephalogram, etc.), and the existing Neuroinformatics infrastructure for tool and data sharing. The review is concluded by pinpointing some major challenges that are being faced, which include the development of novel benchmarking techniques, cloud-based distributed processing and analysis tools, as well as defining novel means to share and standardize data. PMID:27313507

Gun muzzle flash detection using a single photon avalanche diode array in 0.18µm CMOS technology

NASA Astrophysics Data System (ADS)

Savuskan, Vitali; Jakobson, Claudio; Merhav, Tomer; Shoham, Avi; Brouk, Igor; Nemirovsky, Yael

2015-05-01

In this study, a CMOS Single Photon Avalanche Diode (SPAD) 2D array is used to record and sample muzzle flash events in the visible spectrum, from representative weapons. SPADs detect the emission peaks of alkali salts, potassium or sodium, with spectral emission lines around 769nm and 589nm, respectively. The alkali salts are included in the gunpowder to suppress secondary flashes ignited during the muzzle flash event. The SPADs possess two crucial properties for muzzle flash imaging: (i) very high photon detection sensitivity, (ii) a unique ability to convert the optical signal to a digital signal at the source pixel, thus practically eliminating readout noise. The sole noise sources are the ones prior to the readout circuitry (optical signal distribution, avalanche initiation distribution and nonphotonic generation). This enables high sampling frequencies in the kilohertz range without significant SNR degradation, in contrast to regular CMOS image sensors. This research will demonstrate the SPAD's ability to accurately sample and reconstruct the temporal behavior of the muzzle flash in the visible wavelength, in the presence of sunlight. The reconstructed signal is clearly distinguishable from background clutter, through exploitation of flash temporal characteristics and signal processing, which will be reported. The frame rate of ~16 KHz was chosen as an optimum between SNR degradation and temporal profile recognition accuracy. In contrast to a single SPAD, the 2D array allows for multiple events to be processed simultaneously. Moreover, a significant field of view is covered, enabling comprehensive surveillance and imaging.

The integrated design and archive of space-borne signal processing and compression coding

NASA Astrophysics Data System (ADS)

He, Qiang-min; Su, Hao-hang; Wu, Wen-bo

2017-10-01

With the increasing demand of users for the extraction of remote sensing image information, it is very urgent to significantly enhance the whole system's imaging quality and imaging ability by using the integrated design to achieve its compact structure, light quality and higher attitude maneuver ability. At this present stage, the remote sensing camera's video signal processing unit and image compression and coding unit are distributed in different devices. The volume, weight and consumption of these two units is relatively large, which unable to meet the requirements of the high mobility remote sensing camera. This paper according to the high mobility remote sensing camera's technical requirements, designs a kind of space-borne integrated signal processing and compression circuit by researching a variety of technologies, such as the high speed and high density analog-digital mixed PCB design, the embedded DSP technology and the image compression technology based on the special-purpose chips. This circuit lays a solid foundation for the research of the high mobility remote sensing camera.

A Compartment Model of VEGF Distribution in Humans in the Presence of Soluble VEGF Receptor-1 Acting as a Ligand Trap

PubMed Central

Wu, Florence T. H.; Stefanini, Marianne O.; Mac Gabhann, Feilim; Popel, Aleksander S.

2009-01-01

Vascular endothelial growth factor (VEGF), through its activation of cell surface receptor tyrosine kinases including VEGFR1 and VEGFR2, is a vital regulator of stimulatory and inhibitory processes that keep angiogenesis – new capillary growth from existing microvasculature – at a dynamic balance in normal physiology. Soluble VEGF receptor-1 (sVEGFR1) – a naturally-occurring truncated version of VEGFR1 lacking the transmembrane and intracellular signaling domains – has been postulated to exert inhibitory effects on angiogenic signaling via two mechanisms: direct sequestration of angiogenic ligands such as VEGF; or dominant-negative heterodimerization with surface VEGFRs. In pre-clinical studies, sVEGFR1 gene and protein therapy have demonstrated efficacy in inhibiting tumor angiogenesis; while in clinical studies, sVEGFR1 has shown utility as a diagnostic or prognostic marker in a widening array of angiogenesis–dependent diseases. Here we developed a novel computational multi-tissue model for recapitulating the dynamic systemic distributions of VEGF and sVEGFR1. Model features included: physiologically-based multi-scale compartmentalization of the human body; inter-compartmental macromolecular biotransport processes (vascular permeability, lymphatic drainage); and molecularly-detailed binding interactions between the ligand isoforms VEGF121 and VEGF165, signaling receptors VEGFR1 and VEGFR2, non-signaling co-receptor neuropilin-1 (NRP1), as well as sVEGFR1. The model was parameterized to represent a healthy human subject, whereupon we investigated the effects of sVEGFR1 on the distribution and activation of VEGF ligands and receptors. We assessed the healthy baseline stability of circulating VEGF and sVEGFR1 levels in plasma, as well as their reliability in indicating tissue-level angiogenic signaling potential. Unexpectedly, simulated results showed that sVEGFR1 – acting as a diffusible VEGF sink alone, i.e., without sVEGFR1-VEGFR heterodimerization – did not significantly lower interstitial VEGF, nor inhibit signaling potential in tissues. Additionally, the sensitivity of plasma VEGF and sVEGFR1 to physiological fluctuations in transport rates may partially account for the heterogeneity in clinical measurements of these circulating angiogenic markers, potentially hindering their diagnostic reliability for diseases. PMID:19352513

SGR-like behaviour of the repeating FRB 121102

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

Wang, F.Y.; Yu, H., E-mail: fayinwang@nju.edu.cn, E-mail: yuhai@smail.nju.edu.cn

2017-03-01

Fast radio bursts (FRBs) are millisecond-duration radio signals occurring at cosmological distances. However the physical model of FRBs is mystery, many models have been proposed. Here we study the frequency distributions of peak flux, fluence, duration and waiting time for the repeating FRB 121102. The cumulative distributions of peak flux, fluence and duration show power-law forms. The waiting time distribution also shows power-law distribution, and is consistent with a non-stationary Poisson process. These distributions are similar as those of soft gamma repeaters (SGRs). We also use the statistical results to test the proposed models for FRBs. These distributions are consistentmore » with the predictions from avalanche models of slowly driven nonlinear dissipative systems.« less

Local population density and group composition influence the signal-preference relationship in Enchenopa treehoppers (Hemiptera: Membracidae).

PubMed

Fowler-Finn, K D; Cruz, D C; Rodríguez, R L

2017-01-01

Many animals exhibit social plasticity - changes in phenotype or behaviour in response to experience with conspecifics that change how evolutionary processes like sexual selection play out. Here, we asked whether social plasticity arising from variation in local population density in male advertisement signals and female mate preferences influences the form of sexual selection. We manipulated local density and determined whether this changed how the distribution of male signals overlapped with female preferences - the signal preference relationship. We specifically look at the shape of female mate preference functions, which, when compared to signal distributions, provide hypotheses about the form of sexual selection. We used Enchenopa binotata treehoppers, a group of plant-feeding insects that exhibit natural variation in local densities across individual host plants, populations, species and years. We measured male signal frequency and female preference functions across the density treatments. We found that male signals varied across local social groups, but not according to local density. By contrast, female preferences varied with local density - favouring higher signal frequencies in denser environments. Thus, local density changes the signal-preference relationship and, consequently, the expected form of sexual selection. We found no influence of sex ratio on the signal-preference relationship. Our findings suggest that plasticity arising from variation in local group density and composition can alter the form of sexual selection with potentially important consequences both for the maintenance of variation and for speciation. © 2016 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2016 European Society For Evolutionary Biology.

Generalization of the normal-exponential model: exploration of a more accurate parametrisation for the signal distribution on Illumina BeadArrays.

PubMed

Plancade, Sandra; Rozenholc, Yves; Lund, Eiliv

2012-12-11

Illumina BeadArray technology includes non specific negative control features that allow a precise estimation of the background noise. As an alternative to the background subtraction proposed in BeadStudio which leads to an important loss of information by generating negative values, a background correction method modeling the observed intensities as the sum of the exponentially distributed signal and normally distributed noise has been developed. Nevertheless, Wang and Ye (2012) display a kernel-based estimator of the signal distribution on Illumina BeadArrays and suggest that a gamma distribution would represent a better modeling of the signal density. Hence, the normal-exponential modeling may not be appropriate for Illumina data and background corrections derived from this model may lead to wrong estimation. We propose a more flexible modeling based on a gamma distributed signal and a normal distributed background noise and develop the associated background correction, implemented in the R-package NormalGamma. Our model proves to be markedly more accurate to model Illumina BeadArrays: on the one hand, it is shown on two types of Illumina BeadChips that this model offers a more correct fit of the observed intensities. On the other hand, the comparison of the operating characteristics of several background correction procedures on spike-in and on normal-gamma simulated data shows high similarities, reinforcing the validation of the normal-gamma modeling. The performance of the background corrections based on the normal-gamma and normal-exponential models are compared on two dilution data sets, through testing procedures which represent various experimental designs. Surprisingly, we observe that the implementation of a more accurate parametrisation in the model-based background correction does not increase the sensitivity. These results may be explained by the operating characteristics of the estimators: the normal-gamma background correction offers an improvement in terms of bias, but at the cost of a loss in precision. This paper addresses the lack of fit of the usual normal-exponential model by proposing a more flexible parametrisation of the signal distribution as well as the associated background correction. This new model proves to be considerably more accurate for Illumina microarrays, but the improvement in terms of modeling does not lead to a higher sensitivity in differential analysis. Nevertheless, this realistic modeling makes way for future investigations, in particular to examine the characteristics of pre-processing strategies.

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.

On a Chirplet Transform Based Method for Co-channel Voice Separation

NASA Astrophysics Data System (ADS)

Dugnol, B.; Fernández, C.; Galiano, G.; Velasco, J.

We use signal and image theory based algorithms to produce estimations of the number of wolves emitting howls or barks in a given field recording as an individuals counting alternative to the traditional trace collecting methodologies. We proceed in two steps. Firstly, we clean and enhance the signal by using PDE based image processing algorithms applied to the signal spectrogram. Secondly, assuming that the wolves chorus may be modelled as an addition of nonlinear chirps, we use the quadratic energy distribution corresponding to the Chirplet Transform of the signal to produce estimates of the corresponding instantaneous frequencies, chirp-rates and amplitudes at each instant of the recording. We finally establish suitable criteria to decide how such estimates are connected in time.

Relaxation of water infiltration pulses observed with GPR

NASA Astrophysics Data System (ADS)

Hantschel, Lisa; Hemmer, Benedikt; Roth, Kurt

2017-04-01

We observe the relaxation of infiltration pulses in sandy soil with ground-penetrating radar (GPR). The spatial distribution of water in the infiltration area and its temporal evolution is represented by ordinary reflections at layer boundaries as well as multiple reflections at the wetting front and the pulse boundaries. The structure of these highly resolved signals are reproduced by numerical simulations of electromagnetic wave propagation. The temporally highly resolved electrical fields reveal the origin also of complex reflection signals. The usage of these more complex signals might allow a more detailed representation of the infiltration process by direct analysis as well as in combination with inversion techniques.

Fisher information matrix for branching processes with application to electron-multiplying charge-coupled devices

PubMed Central

Chao, Jerry; Ward, E. Sally; Ober, Raimund J.

2012-01-01

The high quantum efficiency of the charge-coupled device (CCD) has rendered it the imaging technology of choice in diverse applications. However, under extremely low light conditions where few photons are detected from the imaged object, the CCD becomes unsuitable as its readout noise can easily overwhelm the weak signal. An intended solution to this problem is the electron-multiplying charge-coupled device (EMCCD), which stochastically amplifies the acquired signal to drown out the readout noise. Here, we develop the theory for calculating the Fisher information content of the amplified signal, which is modeled as the output of a branching process. Specifically, Fisher information expressions are obtained for a general and a geometric model of amplification, as well as for two approximations of the amplified signal. All expressions pertain to the important scenario of a Poisson-distributed initial signal, which is characteristic of physical processes such as photon detection. To facilitate the investigation of different data models, a “noise coefficient” is introduced which allows the analysis and comparison of Fisher information via a scalar quantity. We apply our results to the problem of estimating the location of a point source from its image, as observed through an optical microscope and detected by an EMCCD. PMID:23049166

Robust low-frequency spread-spectrum navigation system

DOEpatents

Smith, Stephen F [Loudon, TN; Moore, James A [Powell, TN

2012-01-03

Methods and apparatus are described for a navigation system. A process includes providing a plurality of transmitters distributed throughout a desired coverage area; locking the plurality of transmitters to a common timing reference; transmitting a signal from each of the plurality of transmitters. An apparatus includes a plurality of transmitters distributed throughout a desired coverage area; wherein each of the plurality of transmitters comprises a packet generator; and wherein the plurality of transmitters are locked to a common timing reference.

Robust low-frequency spread-spectrum navigation system

DOEpatents

Smith, Stephen F [Loudon, TN; Moore, James A [Powell, TN

2011-01-25

Methods and apparatus are described for a navigation system. A process includes providing a plurality of transmitters distributed throughout a desired coverage area; locking the plurality of transmitters to a common timing reference; transmitting a signal from each of the plurality of transmitters. An apparatus includes a plurality of transmitters distributed throughout a desired coverage area; wherein each of the plurality of transmitters comprises a packet generator; and wherein the plurality of transmitters are locked to a common timing reference.

Robust low-frequency spread-spectrum navigation system

DOEpatents

Smith, Stephen F; Moore, James A

2012-10-30

Methods and apparatus are described for a navigation system. A process includes providing a plurality of transmitters distributed throughout a desired coverage area; locking the plurality of transmitters to a common timing reference; transmitting a signal from each of the plurality of transmitters. An apparatus includes a plurality of transmitters distributed throughout a desired coverage area; wherein each of the plurality of transmitters comprises a packet generator; and wherein the plurality of transmitters are locked to a common timing reference.

Robust low-frequency spread-spectrum navigation system

DOEpatents

Smith, Stephen F [Loudon, TN; Moore, James A [Powell, TN

2009-12-01

Methods and apparatus are described for a navigation system. A process includes providing a plurality of transmitters distributed throughout a desired coverage area; locking the plurality of transmitters to a common timing reference; transmitting a signal from each of the plurality of transmitters. An apparatus includes a plurality of transmitters distributed throughout a desired coverage area; wherein each of the plurality of transmitters comprises a packet generator; and wherein the plurality of transmitters are locked to a common timing reference.

Proceedings of the Annual Gravity Gradiometer Conference (17th) Held in Hanscom AFB, Massachusetts on 12-13 October 1989

DTIC Science & Technology

1990-03-28

D’IC FILE COpY G---90-0067 ENVIRONMENTAL RESEARCH PAPERS , NO. 1059 AD-A223 568 PROCEEDINGS OF THE SEVENTEENTH ANNUAL GRAVITY GRADIOICET CONFERENCE 12...AVAILABILITY STATEMENT 12b. DISTRIBUTION CODE Approved for Public Release; Distribution Unlimited 13. ABSTRACT (Maximu&m 200 words)/ Fourteen papers were...instrumentation * and applications. The technical papers covered test program results, applications to gravity field mapping, gravity signal processing

VLBA Archive &Distribution Architecture

NASA Astrophysics Data System (ADS)

Wells, D. C.

1994-01-01

Signals from the 10 antennas of NRAO's VLBA [Very Long Baseline Array] are processed by a Correlator. The complex fringe visibilities produced by the Correlator are archived on magnetic cartridges using a low-cost architecture which is capable of scaling and evolving. Archive files are copied to magnetic media to be distributed to users in FITS format, using the BINTABLE extension. Archive files are labelled using SQL INSERT statements, in order to bind the DBMS-based archive catalog to the archive media.

Multi-functional optical signal processing using optical spectrum control circuit

NASA Astrophysics Data System (ADS)

Hayashi, Shuhei; Ikeda, Tatsuhiko; Mizuno, Takayuki; Takahashi, Hiroshi; Tsuda, Hiroyuki

2015-02-01

Processing ultra-fast optical signals without optical/electronic conversion is in demand and time-to-space conversion has been proposed as an effective solution. We have designed and fabricated an arrayed-waveguide grating (AWG) based optical spectrum control circuit (OSCC) using silica planar lightwave circuit (PLC) technology. This device is composed of an AWG, tunable phase shifters and a mirror. The principle of signal processing is to spatially decompose the signal's frequency components by using the AWG. Then, the phase of each frequency component is controlled by the tunable phase shifters. Finally, the light is reflected back to the AWG by the mirror and synthesized. Amplitude of each frequency component can be controlled by distributing the power to high diffraction order light. The spectral controlling range of the OSCC is 100 GHz and its resolution is 1.67 GHz. This paper describes equipping the OSCC with optical coded division multiplex (OCDM) encoder/decoder functionality. The encoding principle is to apply certain phase patterns to the signal's frequency components and intentionally disperse the signal. The decoding principle is also to apply certain phase patterns to the frequency components at the receiving side. If the applied phase pattern compensates the intentional dispersion, the waveform is regenerated, but if the pattern is not appropriate, the waveform remains dispersed. We also propose an arbitrary filter function by exploiting the OSCC's amplitude and phase control attributes. For example, a filtered optical signal transmitted through multiple optical nodes that use the wavelength multiplexer/demultiplexer can be equalized.

Distributed processing method for arbitrary view generation in camera sensor network

NASA Astrophysics Data System (ADS)

Tehrani, Mehrdad P.; Fujii, Toshiaki; Tanimoto, Masayuki

2003-05-01

Camera sensor network as a new advent of technology is a network that each sensor node can capture video signals, process and communicate them with other nodes. The processing task in this network is to generate arbitrary view, which can be requested from central node or user. To avoid unnecessary communication between nodes in camera sensor network and speed up the processing time, we have distributed the processing tasks between nodes. In this method, each sensor node processes part of interpolation algorithm to generate the interpolated image with local communication between nodes. The processing task in camera sensor network is ray-space interpolation, which is an object independent method and based on MSE minimization by using adaptive filtering. Two methods were proposed for distributing processing tasks, which are Fully Image Shared Decentralized Processing (FIS-DP), and Partially Image Shared Decentralized Processing (PIS-DP), to share image data locally. Comparison of the proposed methods with Centralized Processing (CP) method shows that PIS-DP has the highest processing speed after FIS-DP, and CP has the lowest processing speed. Communication rate of CP and PIS-DP is almost same and better than FIS-DP. So, PIS-DP is recommended because of its better performance than CP and FIS-DP.

The subcellular distribution of T-type Ca2+ channels in interneurons of the lateral geniculate nucleus.

PubMed

Allken, Vaneeda; Chepkoech, Joy-Loi; Einevoll, Gaute T; Halnes, Geir

2014-01-01

Inhibitory interneurons (INs) in the lateral geniculate nucleus (LGN) provide both axonal and dendritic GABA output to thalamocortical relay cells (TCs). Distal parts of the IN dendrites often enter into complex arrangements known as triadic synapses, where the IN dendrite plays a dual role as postsynaptic to retinal input and presynaptic to TC dendrites. Dendritic GABA release can be triggered by retinal input, in a highly localized process that is functionally isolated from the soma, but can also be triggered by somatically elicited Ca(2+)-spikes and possibly by backpropagating action potentials. Ca(2+)-spikes in INs are predominantly mediated by T-type Ca(2+)-channels (T-channels). Due to the complex nature of the dendritic signalling, the function of the IN is likely to depend critically on how T-channels are distributed over the somatodendritic membrane (T-distribution). To study the relationship between the T-distribution and several IN response properties, we here run a series of simulations where we vary the T-distribution in a multicompartmental IN model with a realistic morphology. We find that the somatic response to somatic current injection is facilitated by a high T-channel density in the soma-region. Conversely, a high T-channel density in the distal dendritic region is found to facilitate dendritic signalling in both the outward direction (increases the response in distal dendrites to somatic input) and the inward direction (the soma responds stronger to distal synaptic input). The real T-distribution is likely to reflect a compromise between several neural functions, involving somatic response patterns and dendritic signalling.

The Subcellular Distribution of T-Type Ca2+ Channels in Interneurons of the Lateral Geniculate Nucleus

PubMed Central

Allken, Vaneeda; Chepkoech, Joy-Loi; Einevoll, Gaute T.; Halnes, Geir

2014-01-01

Inhibitory interneurons (INs) in the lateral geniculate nucleus (LGN) provide both axonal and dendritic GABA output to thalamocortical relay cells (TCs). Distal parts of the IN dendrites often enter into complex arrangements known as triadic synapses, where the IN dendrite plays a dual role as postsynaptic to retinal input and presynaptic to TC dendrites. Dendritic GABA release can be triggered by retinal input, in a highly localized process that is functionally isolated from the soma, but can also be triggered by somatically elicited Ca2+-spikes and possibly by backpropagating action potentials. Ca2+-spikes in INs are predominantly mediated by T-type Ca2+-channels (T-channels). Due to the complex nature of the dendritic signalling, the function of the IN is likely to depend critically on how T-channels are distributed over the somatodendritic membrane (T-distribution). To study the relationship between the T-distribution and several IN response properties, we here run a series of simulations where we vary the T-distribution in a multicompartmental IN model with a realistic morphology. We find that the somatic response to somatic current injection is facilitated by a high T-channel density in the soma-region. Conversely, a high T-channel density in the distal dendritic region is found to facilitate dendritic signalling in both the outward direction (increases the response in distal dendrites to somatic input) and the inward direction (the soma responds stronger to distal synaptic input). The real T-distribution is likely to reflect a compromise between several neural functions, involving somatic response patterns and dendritic signalling. PMID:25268996

Time-Frequency Approach for Stochastic Signal Detection

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

Ghosh, Ripul; Akula, Aparna; Kumar, Satish

2011-10-20

The detection of events in a stochastic signal has been a subject of great interest. One of the oldest signal processing technique, Fourier Transform of a signal contains information regarding frequency content, but it cannot resolve the exact onset of changes in the frequency, all temporal information is contained in the phase of the transform. On the other hand, Spectrogram is better able to resolve temporal evolution of frequency content, but has a trade-off in time resolution versus frequency resolution in accordance with the uncertainty principle. Therefore, time-frequency representations are considered for energetic characterisation of the non-stationary signals. Wigner Villemore » Distribution (WVD) is the most prominent quadratic time-frequency signal representation and used for analysing frequency variations in signals.WVD allows for instantaneous frequency estimation at each data point, for a typical temporal resolution of fractions of a second. This paper through simulations describes the way time frequency models are applied for the detection of event in a stochastic signal.« less

Time-Frequency Approach for Stochastic Signal Detection

NASA Astrophysics Data System (ADS)

Ghosh, Ripul; Akula, Aparna; Kumar, Satish; Sardana, H. K.

2011-10-01

The detection of events in a stochastic signal has been a subject of great interest. One of the oldest signal processing technique, Fourier Transform of a signal contains information regarding frequency content, but it cannot resolve the exact onset of changes in the frequency, all temporal information is contained in the phase of the transform. On the other hand, Spectrogram is better able to resolve temporal evolution of frequency content, but has a trade-off in time resolution versus frequency resolution in accordance with the uncertainty principle. Therefore, time-frequency representations are considered for energetic characterisation of the non-stationary signals. Wigner Ville Distribution (WVD) is the most prominent quadratic time-frequency signal representation and used for analysing frequency variations in signals.WVD allows for instantaneous frequency estimation at each data point, for a typical temporal resolution of fractions of a second. This paper through simulations describes the way time frequency models are applied for the detection of event in a stochastic signal.

Proteomic Prediction of Breast Cancer Risk: A Cohort Study

DTIC Science & Technology

2007-03-01

Total 1728 1189 68.81 (c) Data processing. Data analysis was performed using in-house software (Du P , Angeletti RH. Automatic deconvolution of...isotope-resolved mass spectra using variable selection and quantized peptide mass distribution. Anal Chem., 78:3385-92, 2006; P Du, R Sudha, MB...control. Reportable Outcomes So far our publications have been on the development of algorithms for signal processing: 1. Du P , Angeletti RH

Crosslinking EEG time-frequency decomposition and fMRI in error monitoring.

PubMed

Hoffmann, Sven; Labrenz, Franziska; Themann, Maria; Wascher, Edmund; Beste, Christian

2014-03-01

Recent studies implicate a common response monitoring system, being active during erroneous and correct responses. Converging evidence from time-frequency decompositions of the response-related ERP revealed that evoked theta activity at fronto-central electrode positions differentiates correct from erroneous responses in simple tasks, but also in more complex tasks. However, up to now it is unclear how different electrophysiological parameters of error processing, especially at the level of neural oscillations are related, or predictive for BOLD signal changes reflecting error processing at a functional-neuroanatomical level. The present study aims to provide crosslinks between time domain information, time-frequency information, MRI BOLD signal and behavioral parameters in a task examining error monitoring due to mistakes in a mental rotation task. The results show that BOLD signal changes reflecting error processing on a functional-neuroanatomical level are best predicted by evoked oscillations in the theta frequency band. Although the fMRI results in this study account for an involvement of the anterior cingulate cortex, middle frontal gyrus, and the Insula in error processing, the correlation of evoked oscillations and BOLD signal was restricted to a coupling of evoked theta and anterior cingulate cortex BOLD activity. The current results indicate that although there is a distributed functional-neuroanatomical network mediating error processing, only distinct parts of this network seem to modulate electrophysiological properties of error monitoring.

Concepts and Development of Bio-Inspired Distributed Embedded Wired/Wireless Sensor Array Architectures for Acoustic Wave Sensing in Integrated Aerospace Vehicles

NASA Technical Reports Server (NTRS)

Ghoshal, Anindya; Prosser, William H.; Kirikera, Goutham; Schulz, Mark J.; Hughes, Derke J.; Orisamolu, Wally

2003-01-01

This paper discusses the modeling of acoustic emissions in plate structures and their sensing by embedded or surface bonded piezoelectric sensor arrays. Three different modeling efforts for acoustic emission (AE) wave generation and propagation are discussed briefly along with their advantages and disadvantages. Continuous sensors placed at right angles on a plate are being discussed as a new approach to measure and locate the source of acoustic waves. Evolutionary novel signal processing algorithms and bio-inspired distributed sensor array systems are used on large structures and integrated aerospace vehicles for AE source localization and preliminary results are presented. These systems allow for a great reduction in the amount of data that needs to be processed and also reduce the chances of false alarms from ambient noises. It is envisioned that these biomimetic sensor arrays and signal processing techniques will be useful for both wireless and wired sensor arrays for real time health monitoring of large integrated aerospace vehicles and earth fixed civil structures. The sensor array architectures can also be used with other types of sensors and for other applications.

Distributed synaptic weights in a LIF neural network and learning rules

NASA Astrophysics Data System (ADS)

Perthame, Benoît; Salort, Delphine; Wainrib, Gilles

2017-09-01

Leaky integrate-and-fire (LIF) models are mean-field limits, with a large number of neurons, used to describe neural networks. We consider inhomogeneous networks structured by a connectivity parameter (strengths of the synaptic weights) with the effect of processing the input current with different intensities. We first study the properties of the network activity depending on the distribution of synaptic weights and in particular its discrimination capacity. Then, we consider simple learning rules and determine the synaptic weight distribution it generates. We outline the role of noise as a selection principle and the capacity to memorize a learned signal.

Representation and Processing of Acoustic Information in a Biomimetic Neural Network

DTIC Science & Technology

1992-01-01

Zvorykin, 1959, 1963). Bat biosonar is adapted for use in cells, whose axons form the auditory eighth nerve. Tursiops air, whereas dolphin biosonar is...adapted for use underwater. ears contain approximately 105,000 ganglion cells Bat biosonar signals are relatively long in duration (up to distributed

A Bayesian Method for Managing Uncertainties Relating to Distributed Multistatic Sensor Search

DTIC Science & Technology

2006-07-01

before - detect process. There will also be an increased probability of high signal-to-noise ratio (SNR) detections associated with specular and near...and high target strength and high Doppler opportunities give rise to the expectation of an increased number of detections that could feed a track

Regulation of Hedgehog Signalling Inside and Outside the Cell

PubMed Central

Ramsbottom, Simon A.; Pownall, Mary E.

2016-01-01

The hedgehog (Hh) signalling pathway is conserved throughout metazoans and plays an important regulatory role in both embryonic development and adult homeostasis. Many levels of regulation exist that control the release, reception, and interpretation of the hedgehog signal. The fatty nature of the Shh ligand means that it tends to associate tightly with the cell membrane, and yet it is known to act as a morphogen that diffuses to elicit pattern formation. Heparan sulfate proteoglycans (HSPGs) play a major role in the regulation of Hh distribution outside the cell. Inside the cell, the primary cilium provides an important hub for processing the Hh signal in vertebrates. This review will summarise the current understanding of how the Hh pathway is regulated from ligand production, release, and diffusion, through to signal reception and intracellular transduction. PMID:27547735

Zinc Signal in Brain Diseases.

PubMed

Portbury, Stuart D; Adlard, Paul A

2017-11-23

The divalent cation zinc is an integral requirement for optimal cellular processes, whereby it contributes to the function of over 300 enzymes, regulates intracellular signal transduction, and contributes to efficient synaptic transmission in the central nervous system. Given the critical role of zinc in a breadth of cellular processes, its cellular distribution and local tissue level concentrations remain tightly regulated via a series of proteins, primarily including zinc transporter and zinc import proteins. A loss of function of these regulatory pathways, or dietary alterations that result in a change in zinc homeostasis in the brain, can all lead to a myriad of pathological conditions with both acute and chronic effects on function. This review aims to highlight the role of zinc signaling in the central nervous system, where it may precipitate or potentiate diverse issues such as age-related cognitive decline, depression, Alzheimer's disease or negative outcomes following brain injury.

Photonic crystal nanocavity assisted rejection ratio tunable notch microwave photonic filter

PubMed Central

Long, Yun; Xia, Jinsong; Zhang, Yong; Dong, Jianji; Wang, Jian

2017-01-01

Driven by the increasing demand on handing microwave signals with compact device, low power consumption, high efficiency and high reliability, it is highly desired to generate, distribute, and process microwave signals using photonic integrated circuits. Silicon photonics offers a promising platform facilitating ultracompact microwave photonic signal processing assisted by silicon nanophotonic devices. In this paper, we propose, theoretically analyze and experimentally demonstrate a simple scheme to realize ultracompact rejection ratio tunable notch microwave photonic filter (MPF) based on a silicon photonic crystal (PhC) nanocavity with fixed extinction ratio. Using a conventional modulation scheme with only a single phase modulator (PM), the rejection ratio of the presented MPF can be tuned from about 10 dB to beyond 60 dB. Moreover, the central frequency tunable operation in the high rejection ratio region is also demonstrated in the experiment. PMID:28067332

Advanced linear and nonlinear compensations for 16QAM SC-400G unrepeatered transmission system

NASA Astrophysics Data System (ADS)

Zhang, Junwen; Yu, Jianjun; Chien, Hung-Chang

2018-02-01

Digital signal processing (DSP) with both linear equalization and nonlinear compensations are studied in this paper for the single-carrier 400G system based on 65-GBaud 16-quadrature amplitude modulation (QAM) signals. The 16-QAM signals are generated and pre-processed with pre-equalization (Pre-EQ) and Look-up-Table (LUT) based pre-distortion (Pre-DT) at the transmitter (Tx)-side. The implementation principle of training-based equalization and pre-distortion are presented here in this paper with experimental studies. At the receiver (Rx)-side, fiber-nonlinearity compensation based on digital backward propagation (DBP) are also utilized to further improve the transmission performances. With joint LUT-based Pre-DT and DBP-based post-compensation to mitigate the opto-electronic components and fiber nonlinearity impairments, we demonstrate the unrepeatered transmission of 1.6Tb/s based on 4-lane 400G single-carrier PDM-16QAM over 205-km SSMF without distributed amplifier.

Photonic crystal nanocavity assisted rejection ratio tunable notch microwave photonic filter

NASA Astrophysics Data System (ADS)

Long, Yun; Xia, Jinsong; Zhang, Yong; Dong, Jianji; Wang, Jian

2017-01-01

Driven by the increasing demand on handing microwave signals with compact device, low power consumption, high efficiency and high reliability, it is highly desired to generate, distribute, and process microwave signals using photonic integrated circuits. Silicon photonics offers a promising platform facilitating ultracompact microwave photonic signal processing assisted by silicon nanophotonic devices. In this paper, we propose, theoretically analyze and experimentally demonstrate a simple scheme to realize ultracompact rejection ratio tunable notch microwave photonic filter (MPF) based on a silicon photonic crystal (PhC) nanocavity with fixed extinction ratio. Using a conventional modulation scheme with only a single phase modulator (PM), the rejection ratio of the presented MPF can be tuned from about 10 dB to beyond 60 dB. Moreover, the central frequency tunable operation in the high rejection ratio region is also demonstrated in the experiment.

Suppression of Quasiparticle Scattering Signals in Bilayer Graphene Due to Layer Polarization and Destructive Interference

NASA Astrophysics Data System (ADS)

Jolie, Wouter; Lux, Jonathan; Pörtner, Mathias; Dombrowski, Daniela; Herbig, Charlotte; Knispel, Timo; Simon, Sabina; Michely, Thomas; Rosch, Achim; Busse, Carsten

2018-03-01

We study chemically gated bilayer graphene using scanning tunneling microscopy and spectroscopy complemented by tight-binding calculations. Gating is achieved by intercalating Cs between bilayer graphene and Ir(111), thereby shifting the conduction band minima below the chemical potential. Scattering between electronic states (both intraband and interband) is detected via quasiparticle interference. However, not all expected processes are visible in our experiment. We uncover two general effects causing this suppression: first, intercalation leads to an asymmetrical distribution of the states within the two layers, which significantly reduces the scanning tunneling spectroscopy signal of standing waves mainly present in the lower layer; second, forward scattering processes, connecting points on the constant energy contours with parallel velocities, do not produce pronounced standing waves due to destructive interference. We present a theory to describe the interference signal for a general n -band material.

Photonic crystal nanocavity assisted rejection ratio tunable notch microwave photonic filter.

PubMed

Long, Yun; Xia, Jinsong; Zhang, Yong; Dong, Jianji; Wang, Jian

2017-01-09

Driven by the increasing demand on handing microwave signals with compact device, low power consumption, high efficiency and high reliability, it is highly desired to generate, distribute, and process microwave signals using photonic integrated circuits. Silicon photonics offers a promising platform facilitating ultracompact microwave photonic signal processing assisted by silicon nanophotonic devices. In this paper, we propose, theoretically analyze and experimentally demonstrate a simple scheme to realize ultracompact rejection ratio tunable notch microwave photonic filter (MPF) based on a silicon photonic crystal (PhC) nanocavity with fixed extinction ratio. Using a conventional modulation scheme with only a single phase modulator (PM), the rejection ratio of the presented MPF can be tuned from about 10 dB to beyond 60 dB. Moreover, the central frequency tunable operation in the high rejection ratio region is also demonstrated in the experiment.

Suppression of Quasiparticle Scattering Signals in Bilayer Graphene Due to Layer Polarization and Destructive Interference.

PubMed

Jolie, Wouter; Lux, Jonathan; Pörtner, Mathias; Dombrowski, Daniela; Herbig, Charlotte; Knispel, Timo; Simon, Sabina; Michely, Thomas; Rosch, Achim; Busse, Carsten

2018-03-09

We study chemically gated bilayer graphene using scanning tunneling microscopy and spectroscopy complemented by tight-binding calculations. Gating is achieved by intercalating Cs between bilayer graphene and Ir(111), thereby shifting the conduction band minima below the chemical potential. Scattering between electronic states (both intraband and interband) is detected via quasiparticle interference. However, not all expected processes are visible in our experiment. We uncover two general effects causing this suppression: first, intercalation leads to an asymmetrical distribution of the states within the two layers, which significantly reduces the scanning tunneling spectroscopy signal of standing waves mainly present in the lower layer; second, forward scattering processes, connecting points on the constant energy contours with parallel velocities, do not produce pronounced standing waves due to destructive interference. We present a theory to describe the interference signal for a general n-band material.

Smart Microsystems with Photonic Element and Their Applications to Aerospace Platforms

NASA Technical Reports Server (NTRS)

Adamovsky, G.; Lekki, J.; Sutter, J. K.; Sarkisov, S. S.; Curley, M. J.; Martin, C. E.

2000-01-01

The need to make manufacturing, operation, and support of airborne vehicles safer and more efficient forces engineers and scientists to look for lighter, cheaper, more reliable technologies. Light weight, immunity to EMI, fire safety, high bandwidth, and high signal fidelity have already made photonics in general and fiber optics in particular an extremely attractive medium for communication purposes. With the fiber optics serving as a central nervous system of the vehicle, generation, detection, and processing of the signal occurs at the peripherals that include smart structures and devices. Due to their interdisciplinary nature, photonic technologies cover such diverse areas as optical sensors and actuators, embedded and distributed sensors, sensing schemes and architectures, harnesses and connectors, signal processing and algorithms. The paper includes a brief description of work in the photonic area that is going on at NASA, especially at the Glenn Research Center (GRC).

Architecture of PAU survey camera readout electronics

NASA Astrophysics Data System (ADS)

Castilla, Javier; Cardiel-Sas, Laia; De Vicente, Juan; Illa, Joseph; Jimenez, Jorge; Maiorino, Marino; Martinez, Gustavo

2012-07-01

PAUCam is a new camera for studying the physics of the accelerating universe. The camera will consist of eighteen 2Kx4K HPK CCDs: sixteen for science and two for guiding. The camera will be installed at the prime focus of the WHT (William Herschel Telescope). In this contribution, the architecture of the readout electronics system is presented. Back- End and Front-End electronics are described. Back-End consists of clock, bias and video processing boards, mounted on Monsoon crates. The Front-End is based on patch panel boards. These boards are plugged outside the camera feed-through panel for signal distribution. Inside the camera, individual preamplifier boards plus kapton cable completes the path to connect to each CCD. The overall signal distribution and grounding scheme is shown in this paper.

Evaluation of scattered light distributions of cw-transillumination for functional diagnostic of rheumatic disorders in interphalangeal joints

NASA Astrophysics Data System (ADS)

Prapavat, Viravuth; Schuetz, Rijk; Runge, Wolfram; Beuthan, Juergen; Mueller, Gerhard J.

1995-12-01

This paper presents in-vitro-studies using the scattered intensity distribution obtained by cw- transillumination to examine the condition of rheumatic disorders of interphalangeal joints. Inflammation of joints, due to rheumatic diseases, leads to changes in the synovial membrane, synovia composition and content, and anatomic geometrical variations. Measurements have shown that these rheumatic induced inflammation processes result in a variation in optical properties of joint systems. With a scanning system the interphalangeal joint is transilluminated with diode lasers (670 nm, 905 nm) perpendicular to the joint cavity. The detection of the entire distribution of the transmitted radiation intensity was performed with a CCD camera. As a function of the structure and optical properties of the transilluminated volume we achieved distributions of scattered radiation which show characteristic variations in intensity and shape. Using signal and image processing procedures we evaluated the measured scattered distributions regarding their information weight, shape and scale features. Mathematical methods were used to find classification criteria to determine variations of the joint condition.

Glycogen distribution in the microwave‐fixed mouse brain reveals heterogeneous astrocytic patterns

PubMed Central

Baba, Otto; Ashida, Hitoshi; Nakamura, Kouichi C.

2016-01-01

In the brain, glycogen metabolism has been implied in synaptic plasticity and learning, yet the distribution of this molecule has not been fully described. We investigated cerebral glycogen of the mouse by immunohistochemistry (IHC) using two monoclonal antibodies that have different affinities depending on the glycogen size. The use of focused microwave irradiation yielded well‐defined glycogen immunoreactive signals compared with the conventional periodic acid‐Schiff method. The IHC signals displayed a punctate distribution localized predominantly in astrocytic processes. Glycogen immunoreactivity (IR) was high in the hippocampus, striatum, cortex, and cerebellar molecular layer, whereas it was low in the white matter and most of the subcortical structures. Additionally, glycogen distribution in the hippocampal CA3‐CA1 and striatum had a ‘patchy’ appearance with glycogen‐rich and glycogen‐poor astrocytes appearing in alternation. The glycogen patches were more evident with large‐molecule glycogen in young adult mice but they were hardly observable in aged mice (1–2 years old). Our results reveal brain region‐dependent glycogen accumulation and possibly metabolic heterogeneity of astrocytes. GLIA 2016;64:1532–1545 PMID:27353480

Method and apparatus for anti-islanding protection of distributed generations

DOEpatents

Ye, Zhihong; John, Vinod; Wang, Changyong; Garces, Luis Jose; Zhou, Rui; Li, Lei; Walling, Reigh Allen; Premerlani, William James; Sanza, Peter Claudius; Liu, Yan; Dame, Mark Edward

2006-03-21

An apparatus for anti-islanding protection of a distributed generation with respect to a feeder connected to an electrical grid is disclosed. The apparatus includes a sensor adapted to generate a voltage signal representative of an output voltage and/or a current signal representative of an output current at the distributed generation, and a controller responsive to the signals from the sensor. The controller is productive of a control signal directed to the distributed generation to drive an operating characteristic of the distributed generation out of a nominal range in response to the electrical grid being disconnected from the feeder.

Data Acquisition and Processing System for Airborne Wind Profiling with a Pulsed, 2-Micron, Coherent-Detection, Doppler Lidar System

NASA Technical Reports Server (NTRS)

Beyon, J. Y.; Koch, G. J.; Kavaya, M. J.

2010-01-01

A data acquisition and signal processing system is being developed for a 2-micron airborne wind profiling coherent Doppler lidar system. This lidar, called the Doppler Aerosol Wind Lidar (DAWN), is based on a Ho:Tm:LuLiF laser transmitter and 15-cm diameter telescope. It is being packaged for flights onboard the NASA DC-8, with the first flights in the summer of 2010 in support of the NASA Genesis and Rapid Intensification Processes (GRIP) campaign for the study of hurricanes. The data acquisition and processing system is housed in a compact PCI chassis and consists of four components such as a digitizer, a digital signal processing (DSP) module, a video controller, and a serial port controller. The data acquisition and processing software (DAPS) is also being developed to control the system including real-time data analysis and display. The system detects an external 10 Hz trigger pulse and initiates the data acquisition and processing process, and displays selected wind profile parameters such as Doppler shift, power distribution, wind directions and velocities. Doppler shift created by aircraft motion is measured by an inertial navigation/GPS sensor and fed to the signal processing system for real-time removal of aircraft effects from wind measurements. A general overview of the system and the DAPS as well as the coherent Doppler lidar system is presented in this paper.

Multiplicative point process as a model of trading activity

NASA Astrophysics Data System (ADS)

Gontis, V.; Kaulakys, B.

2004-11-01

Signals consisting of a sequence of pulses show that inherent origin of the 1/ f noise is a Brownian fluctuation of the average interevent time between subsequent pulses of the pulse sequence. In this paper, we generalize the model of interevent time to reproduce a variety of self-affine time series exhibiting power spectral density S( f) scaling as a power of the frequency f. Furthermore, we analyze the relation between the power-law correlations and the origin of the power-law probability distribution of the signal intensity. We introduce a stochastic multiplicative model for the time intervals between point events and analyze the statistical properties of the signal analytically and numerically. Such model system exhibits power-law spectral density S( f)∼1/ fβ for various values of β, including β= {1}/{2}, 1 and {3}/{2}. Explicit expressions for the power spectra in the low-frequency limit and for the distribution density of the interevent time are obtained. The counting statistics of the events is analyzed analytically and numerically, as well. The specific interest of our analysis is related with the financial markets, where long-range correlations of price fluctuations largely depend on the number of transactions. We analyze the spectral density and counting statistics of the number of transactions. The model reproduces spectral properties of the real markets and explains the mechanism of power-law distribution of trading activity. The study provides evidence that the statistical properties of the financial markets are enclosed in the statistics of the time interval between trades. A multiplicative point process serves as a consistent model generating this statistics.

Multi-scale Slip Inversion Based on Simultaneous Spatial and Temporal Domain Wavelet Transform

NASA Astrophysics Data System (ADS)

Liu, W.; Yao, H.; Yang, H. Y.

2017-12-01

Finite fault inversion is a widely used method to study earthquake rupture processes. Some previous studies have proposed different methods to implement finite fault inversion, including time-domain, frequency-domain, and wavelet-domain methods. Many previous studies have found that different frequency bands show different characteristics of the seismic rupture (e.g., Wang and Mori, 2011; Yao et al., 2011, 2013; Uchide et al., 2013; Yin et al., 2017). Generally, lower frequency waveforms correspond to larger-scale rupture characteristics while higher frequency data are representative of smaller-scale ones. Therefore, multi-scale analysis can help us understand the earthquake rupture process thoroughly from larger scale to smaller scale. By the use of wavelet transform, the wavelet-domain methods can analyze both the time and frequency information of signals in different scales. Traditional wavelet-domain methods (e.g., Ji et al., 2002) implement finite fault inversion with both lower and higher frequency signals together to recover larger-scale and smaller-scale characteristics of the rupture process simultaneously. Here we propose an alternative strategy with a two-step procedure, i.e., firstly constraining the larger-scale characteristics with lower frequency signals, and then resolving the smaller-scale ones with higher frequency signals. We have designed some synthetic tests to testify our strategy and compare it with the traditional one. We also have applied our strategy to study the 2015 Gorkha Nepal earthquake using tele-seismic waveforms. Both the traditional method and our two-step strategy only analyze the data in different temporal scales (i.e., different frequency bands), while the spatial distribution of model parameters also shows multi-scale characteristics. A more sophisticated strategy is to transfer the slip model into different spatial scales, and then analyze the smooth slip distribution (larger scales) with lower frequency data firstly and more detailed slip distribution (smaller scales) with higher frequency data subsequently. We are now implementing the slip inversion using both spatial and temporal domain wavelets. This multi-scale analysis can help us better understand frequency-dependent rupture characteristics of large earthquakes.

Gene Signal Distribution and HER2 Amplification in Gastroesophageal Cancer.

PubMed

Jørgensen, Jan Trøst; Nielsen, Karsten Bork; Kjærsgaard, Gitte; Jepsen, Anna; Mollerup, Jens

2017-01-01

Background : HER2 serves as an important therapeutic target in gastroesophageal cancer. Differences in HER2 gene signal distribution patterns can be observed at the tissue level, but how it influences the HER2 amplification status has not been studied so far. Here, we investigated the link between HER2 amplification and the different types of gene signal distribution. Methods : Tumor samples from 140 patients with gastroesophageal adenocarcinoma where analyzed using the HER2 IQFISH pharmDx™ assay. Specimens covered non-amplified and amplified cases with a preselected high proportion of HER2 amplified cases. Based on the HER2 /CEN-17 ratio, specimens were categorized into amplified or non-amplified. The signal distribution patterns were divided into homogeneous, heterogeneous focal or heterogeneous mosaic. The study was conducted based on anonymized specimens with limited access to clinicopathological data. Results: Among the 140 analyzed specimens 83 had a heterogeneous HER2 signal distribution, with 62 being focal and 21 of the mosaic type. The remaining 57 specimens had a homogeneous signal distribution. HER2 amplification was observed in 63 of the 140 specimens, and nearly all (93.7%) were found among specimens with a heterogeneous focal signal distribution (p<0.0001). The mean HER2 /CEN-17 ratio for the focal heterogeneous group was 8.75 (CI95%: 6.87 - 10.63), compared to 1.53 (CI95%: 1.45 - 1.61) and 1.70 (CI95%: 1.22 - 2.18) for the heterogeneous mosaic and homogeneous groups, respectively, (p<0.0001). Conclusions: A clear relationship between HER2 amplification and the focal heterogeneous signal distribution was demonstrated in tumor specimens from patients with gastroesophageal cancer. Furthermore, we raise the hypothesis that the signal distribution patterns observed with FISH might be related to different subpopulations of HER2 positive tumor cells.

The technique of entropy optimization in motor current signature analysis and its application in the fault diagnosis of gear transmission

NASA Astrophysics Data System (ADS)

Chen, Xiaoguang; Liang, Lin; Liu, Fei; Xu, Guanghua; Luo, Ailing; Zhang, Sicong

2012-05-01

Nowadays, Motor Current Signature Analysis (MCSA) is widely used in the fault diagnosis and condition monitoring of machine tools. However, although the current signal has lower SNR (Signal Noise Ratio), it is difficult to identify the feature frequencies of machine tools from complex current spectrum that the feature frequencies are often dense and overlapping by traditional signal processing method such as FFT transformation. With the study in the Motor Current Signature Analysis (MCSA), it is found that the entropy is of importance for frequency identification, which is associated with the probability distribution of any random variable. Therefore, it plays an important role in the signal processing. In order to solve the problem that the feature frequencies are difficult to be identified, an entropy optimization technique based on motor current signal is presented in this paper for extracting the typical feature frequencies of machine tools which can effectively suppress the disturbances. Some simulated current signals were made by MATLAB, and a current signal was obtained from a complex gearbox of an iron works made in Luxembourg. In diagnosis the MCSA is combined with entropy optimization. Both simulated and experimental results show that this technique is efficient, accurate and reliable enough to extract the feature frequencies of current signal, which provides a new strategy for the fault diagnosis and the condition monitoring of machine tools.

The Arabidopsis LAZY1 Family Plays a Key Role in Gravity Signaling within Statocytes and in Branch Angle Control of Roots and Shoots.

PubMed

Taniguchi, Masatoshi; Furutani, Masahiko; Nishimura, Takeshi; Nakamura, Moritaka; Fushita, Toyohito; Iijima, Kohta; Baba, Kenichiro; Tanaka, Hirokazu; Toyota, Masatsugu; Tasaka, Masao; Morita, Miyo Terao

2017-08-01

During gravitropism, the directional signal of gravity is perceived by gravity-sensing cells called statocytes, leading to asymmetric distribution of auxin in the responding organs. To identify the genes involved in gravity signaling in statocytes, we performed transcriptome analyses of statocyte-deficient Arabidopsis thaliana mutants and found two candidates from the LAZY1 family, AtLAZY1 / LAZY1-LIKE1 ( LZY1 ) and AtDRO3 / AtNGR1 / LZY2 We showed that LZY1 , LZY2 , and a paralog AtDRO1/AtNGR2/LZY3 are redundantly involved in gravitropism of the inflorescence stem, hypocotyl, and root. Mutations of LZY genes affected early processes in gravity signal transduction without affecting amyloplast sedimentation. Statocyte-specific expression of LZY genes rescued the mutant phenotype, suggesting that LZY genes mediate gravity signaling in statocytes downstream of amyloplast displacement, leading to the generation of asymmetric auxin distribution in gravity-responding organs. We also found that lzy mutations reversed the growth angle of lateral branches and roots. Moreover, expression of the conserved C-terminal region of LZY proteins also reversed the growth direction of primary roots in the lzy mutant background. In lateral root tips of lzy multiple mutants, asymmetric distribution of PIN3 and auxin response were reversed, suggesting that LZY genes regulate the direction of polar auxin transport in response to gravity through the control of asymmetric PIN3 expression in the root cap columella. © 2017 American Society of Plant Biologists. All rights reserved.

A scalable neuroinformatics data flow for electrophysiological signals using MapReduce.

PubMed

Jayapandian, Catherine; Wei, Annan; Ramesh, Priya; Zonjy, Bilal; Lhatoo, Samden D; Loparo, Kenneth; Zhang, Guo-Qiang; Sahoo, Satya S

2015-01-01

Data-driven neuroscience research is providing new insights in progression of neurological disorders and supporting the development of improved treatment approaches. However, the volume, velocity, and variety of neuroscience data generated from sophisticated recording instruments and acquisition methods have exacerbated the limited scalability of existing neuroinformatics tools. This makes it difficult for neuroscience researchers to effectively leverage the growing multi-modal neuroscience data to advance research in serious neurological disorders, such as epilepsy. We describe the development of the Cloudwave data flow that uses new data partitioning techniques to store and analyze electrophysiological signal in distributed computing infrastructure. The Cloudwave data flow uses MapReduce parallel programming algorithm to implement an integrated signal data processing pipeline that scales with large volume of data generated at high velocity. Using an epilepsy domain ontology together with an epilepsy focused extensible data representation format called Cloudwave Signal Format (CSF), the data flow addresses the challenge of data heterogeneity and is interoperable with existing neuroinformatics data representation formats, such as HDF5. The scalability of the Cloudwave data flow is evaluated using a 30-node cluster installed with the open source Hadoop software stack. The results demonstrate that the Cloudwave data flow can process increasing volume of signal data by leveraging Hadoop Data Nodes to reduce the total data processing time. The Cloudwave data flow is a template for developing highly scalable neuroscience data processing pipelines using MapReduce algorithms to support a variety of user applications.

A scalable neuroinformatics data flow for electrophysiological signals using MapReduce

PubMed Central

Jayapandian, Catherine; Wei, Annan; Ramesh, Priya; Zonjy, Bilal; Lhatoo, Samden D.; Loparo, Kenneth; Zhang, Guo-Qiang; Sahoo, Satya S.

2015-01-01

Data-driven neuroscience research is providing new insights in progression of neurological disorders and supporting the development of improved treatment approaches. However, the volume, velocity, and variety of neuroscience data generated from sophisticated recording instruments and acquisition methods have exacerbated the limited scalability of existing neuroinformatics tools. This makes it difficult for neuroscience researchers to effectively leverage the growing multi-modal neuroscience data to advance research in serious neurological disorders, such as epilepsy. We describe the development of the Cloudwave data flow that uses new data partitioning techniques to store and analyze electrophysiological signal in distributed computing infrastructure. The Cloudwave data flow uses MapReduce parallel programming algorithm to implement an integrated signal data processing pipeline that scales with large volume of data generated at high velocity. Using an epilepsy domain ontology together with an epilepsy focused extensible data representation format called Cloudwave Signal Format (CSF), the data flow addresses the challenge of data heterogeneity and is interoperable with existing neuroinformatics data representation formats, such as HDF5. The scalability of the Cloudwave data flow is evaluated using a 30-node cluster installed with the open source Hadoop software stack. The results demonstrate that the Cloudwave data flow can process increasing volume of signal data by leveraging Hadoop Data Nodes to reduce the total data processing time. The Cloudwave data flow is a template for developing highly scalable neuroscience data processing pipelines using MapReduce algorithms to support a variety of user applications. PMID:25852536

Audio distribution and Monitoring Circuit

NASA Technical Reports Server (NTRS)

Kirkland, J. M.

1983-01-01

Versatile circuit accepts and distributes TV audio signals. Three-meter audio distribution and monitoring circuit provides flexibility in monitoring, mixing, and distributing audio inputs and outputs at various signal and impedance levels. Program material is simultaneously monitored on three channels, or single-channel version built to monitor transmitted or received signal levels, drive speakers, interface to building communications, and drive long-line circuits.

NADPH oxidases of the brain: distribution, regulation, and function.

PubMed

Infanger, David W; Sharma, Ram V; Davisson, Robin L

2006-01-01

The NADPH oxidase is a multi-subunit enzyme that catalyzes the reduction of molecular oxygen to form superoxide (O(2)(-)). While classically linked to the respiratory burst in neutrophils, recent evidence now shows that O(2)(-) (and associated reactive oxygen species, ROS) generated by NADPH oxidase in nonphagocytic cells serves myriad functions in health and disease. An entire new family of NADPH Oxidase (Nox) homologues has emerged, which vary widely in cell and tissue distribution, as well as in function and regulation. A major concept in redox signaling is that while NADPH oxidase-derived ROS are necessary for normal cellular function, excessive oxidative stress can contribute to pathological disease. This certainly is true in the central nervous system (CNS), where normal NADPH oxidase function appears to be required for processes such as neuronal signaling, memory, and central cardiovascular homeostasis, but overproduction of ROS contributes to neurotoxicity, neurodegeneration, and cardiovascular diseases. Despite implications of NADPH oxidase in normal and pathological CNS processes, still relatively little is known about the mechanisms involved. This paper summarizes the evidence for NADPH oxidase distribution, regulation, and function in the CNS, emphasizing the diversity of Nox isoforms and their new and emerging role in neuro-cardiovascular function. In addition, perspectives for future research and novel therapeutic targets are offered.

[Study on the arc spectral information for welding quality diagnosis].

PubMed

Li, Zhi-Yong; Gu, Xiao-Yan; Li, Huan; Yang, Li-Jun

2009-03-01

Through collecting the spectral signals of TIG and MIG welding arc with spectrometer, the arc light radiations were analyzed based on the basic theory of plasma physics. The radiation of welding arc distributes over a broad range of frequency, from infrared to ultraviolet. The arc spectrum is composed of line spectra and continuous spectra. Due to the variation of metal density in the welding arc, there is great difference between the welding arc spectra of TIG and MIG in both their intensity and distribution. The MIG welding arc provides more line spectra of metal and the intensity of radiation is greater than TIG. The arc spectrum of TIG welding is stable during the welding process, disturbance factors that cause the spectral variations can be reflected by the spectral line related to the corresponding element entering the welding arc. The arc spectrum of MIG welding will fluctuate severely due to droplet transfer, which produces "noise" in the line spectrum aggregation zone. So for MIG welding, the spectral zone lacking spectral line is suitable for welding quality diagnosis. According to the characteristic of TIG and MIG, special spectral zones were selected for welding quality diagnosis. For TIG welding, the selected zone is in ultraviolet zone (230-300 nm). For MIG welding, the selected zone is in visible zone (570-590 nm). With the basic theory provided for welding quality diagnosis, the integral intensity of spectral signal in the selected zone of welding process with disturbing factor was studied to prove the theory. The results show that the welding quality and disturbance factors can be diagnosed with good signal to noise ratio in the selected spectral zone compared with signal in other spectral zone. The spectral signal can be used for real-time diagnosis of the welding quality.

Persistence of exponential bed thickness distributions in the stratigraphic record: Experiments and theory

NASA Astrophysics Data System (ADS)

Straub, K. M.; Ganti, V. K.; Paola, C.; Foufoula-Georgiou, E.

2010-12-01

Stratigraphy preserved in alluvial basins houses the most complete record of information necessary to reconstruct past environmental conditions. Indeed, the character of the sedimentary record is inextricably related to the surface processes that formed it. In this presentation we explore how the signals of surface processes are recorded in stratigraphy through the use of physical and numerical experiments. We focus on linking surface processes to stratigraphy in 1D by quantifying the probability distributions of processes that govern the evolution of depositional systems to the probability distribution of preserved bed thicknesses. In this study we define a bed as a package of sediment bounded above and below by erosional surfaces. In a companion presentation we document heavy-tailed statistics of erosion and deposition from high-resolution temporal elevation data recorded during a controlled physical experiment. However, the heavy tails in the magnitudes of erosional and depositional events are not preserved in the experimental stratigraphy. Similar to many bed thickness distributions reported in field studies we find that an exponential distribution adequately describes the thicknesses of beds preserved in our experiment. We explore the generation of exponential bed thickness distributions from heavy-tailed surface statistics using 1D numerical models. These models indicate that when the full distribution of elevation fluctuations (both erosional and depositional events) is symmetrical, the resulting distribution of bed thicknesses is exponential in form. Finally, we illustrate that a predictable relationship exists between the coefficient of variation of surface elevation fluctuations and the scale-parameter of the resulting exponential distribution of bed thicknesses.

Plant hormone signaling during development: insights from computational models.

PubMed

Oliva, Marina; Farcot, Etienne; Vernoux, Teva

2013-02-01

Recent years have seen an impressive increase in our knowledge of the topology of plant hormone signaling networks. The complexity of these topologies has motivated the development of models for several hormones to aid understanding of how signaling networks process hormonal inputs. Such work has generated essential insights into the mechanisms of hormone perception and of regulation of cellular responses such as transcription in response to hormones. In addition, modeling approaches have contributed significantly to exploring how spatio-temporal regulation of hormone signaling contributes to plant growth and patterning. New tools have also been developed to obtain quantitative information on hormone distribution during development and to test model predictions, opening the way for quantitative understanding of the developmental roles of hormones. Copyright © 2012 Elsevier Ltd. All rights reserved.

Design distributed simulation platform for vehicle management system

NASA Astrophysics Data System (ADS)

Wen, Zhaodong; Wang, Zhanlin; Qiu, Lihua

2006-11-01

Next generation military aircraft requires the airborne management system high performance. General modules, data integration, high speed data bus and so on are needed to share and manage information of the subsystems efficiently. The subsystems include flight control system, propulsion system, hydraulic power system, environmental control system, fuel management system, electrical power system and so on. The unattached or mixed architecture is changed to integrated architecture. That means the whole airborne system is regarded into one system to manage. So the physical devices are distributed but the system information is integrated and shared. The process function of each subsystem are integrated (including general process modules, dynamic reconfiguration), furthermore, the sensors and the signal processing functions are shared. On the other hand, it is a foundation for power shared. Establish a distributed vehicle management system using 1553B bus and distributed processors which can provide a validation platform for the research of airborne system integrated management. This paper establishes the Vehicle Management System (VMS) simulation platform. Discuss the software and hardware configuration and analyze the communication and fault-tolerant method.

Multichannel/Multisensor Signal Processing In Uncertain Environments With Application To Multitarget Tracking.

DTIC Science & Technology

1998-05-22

NUMBER PR-98-1 T. SPONSORING / MONITORING AGENCY NAME(S) AND ADDRESS(ES) Office of Naval Research Ballston Center Tower One One North Quincy...unlimited. 12 b. DISTRIBUTION CODE 19980601 082 13. ABSTRACT (Maximum 200 words) This research project is concerned with two distinct aspects of analysis...Environments With Application To Multitarget Tracking This research project is concerned with two distinct aspects of analysis and processing of sig

Nonlinear dispersion-based incoherent photonic processing for microwave pulse generation with full reconfigurability.

PubMed

Bolea, Mario; Mora, José; Ortega, Beatriz; Capmany, José

2012-03-12

A novel all-optical technique based on the incoherent processing of optical signals using high-order dispersive elements is analyzed for microwave arbitrary pulse generation. We show an approach which allows a full reconfigurability of a pulse in terms of chirp, envelope and central frequency by the proper control of the second-order dispersion and the incoherent optical source power distribution, achieving large values of time-bandwidth product.

Integrated Sensing and Processing (ISP) Phase 2: Demonstration and Evaluation for Distributed Sensor Networks and Missile Seeker Systems

DTIC Science & Technology

2007-05-29

International Conference Acoustics Speech and Signal Processing (ICASSP 2007) conference 15 − 20 April 2007 in Honolulu, Hawaii. 1. E. Near Term...from the sensor measured in feet. The detection performance of the footstep in the presence of interfering speech was characterized in previously...investigation, we developed a simple piecewise linear approximation to the probability of detection curve with no interfering speech . This approximation was

Two-dimensional optical architectures for the receive mode of phased-array antennas.

PubMed

Pastur, L; Tonda-Goldstein, S; Dolfi, D; Huignard, J P; Merlet, T; Maas, O; Chazelas, J

1999-05-10

We propose and experimentally demonstrate two optical architectures that process the receive mode of a p x p element phased-array antenna. The architectures are based on free-space propagation and switching of the channelized optical carriers of microwave signals. With the first architecture a direct transposition of the received signals in the optical domain is assumed. The second architecture is based on the optical generation and distribution of a microwave local oscillator matched in frequency and direction. Preliminary experimental results at microwave frequencies of approximately 3 GHz are presented.

Optical rogue-wave-like extreme value fluctuations in fiber Raman amplifiers.

PubMed

Hammani, Kamal; Finot, Christophe; Dudley, John M; Millot, Guy

2008-10-13

We report experimental observation and characterization of rogue wave-like extreme value statistics arising from pump-signal noise transfer in a fiber Raman amplifier. Specifically, by exploiting Raman amplification with an incoherent pump, the amplified signal is shown to develop a series of temporal intensity spikes whose peak power follows a power-law probability distribution. The results are interpreted using a numerical model of the Raman gain process using coupled nonlinear Schrödinger equations, and the numerical model predicts results in good agreement with experiment.

Software/hardware distributed processing network supporting the Ada environment

NASA Astrophysics Data System (ADS)

Wood, Richard J.; Pryk, Zen

1993-09-01

A high-performance, fault-tolerant, distributed network has been developed, tested, and demonstrated. The network is based on the MIPS Computer Systems, Inc. R3000 Risc for processing, VHSIC ASICs for high speed, reliable, inter-node communications and compatible commercial memory and I/O boards. The network is an evolution of the Advanced Onboard Signal Processor (AOSP) architecture. It supports Ada application software with an Ada- implemented operating system. A six-node implementation (capable of expansion up to 256 nodes) of the RISC multiprocessor architecture provides 120 MIPS of scalar throughput, 96 Mbytes of RAM and 24 Mbytes of non-volatile memory. The network provides for all ground processing applications, has merit for space-qualified RISC-based network, and interfaces to advanced Computer Aided Software Engineering (CASE) tools for application software development.

Revealing the cellular localization of STAT1 during the cell cycle by super-resolution imaging

PubMed Central

Gao, Jing; Wang, Feng; Liu, Yanhou; Cai, Mingjun; Xu, Haijiao; Jiang, Junguang; Wang, Hongda

2015-01-01

Signal transducers and activators of transcription (STATs) can transduce cytokine signals and regulate gene expression. The cellular localization and nuclear trafficking of STAT1, a representative of the STAT family with multiple transcriptional functions, is tightly related with transcription process, which usually happens in the interphase of the cell cycle. However, these priority questions regarding STAT1 distribution and localization at the different cell-cycle stages remain unclear. By using direct stochastic optical reconstruction microscopy (dSTORM), we found that the nuclear expression level of STAT1 increased gradually as the cell cycle carried out, especially after EGF stimulation. Furthermore, STAT1 formed clusters in the whole cell during the cell cycle, with the size and the number of clusters also increasing significantly from G1 to G2 phase, suggesting that transcription and other cell-cycle related activities can promote STAT1 to form more and larger clusters for fast response to signals. Our work reveals that the cellular localization and clustering distribution of STAT1 are associated with the cell cycle, and further provides an insight into the mechanism of cell-cycle regulated STAT1 signal transduction. PMID:25762114

How learning to abstract shapes neural sound representations

PubMed Central

Ley, Anke; Vroomen, Jean; Formisano, Elia

2014-01-01

The transformation of acoustic signals into abstract perceptual representations is the essence of the efficient and goal-directed neural processing of sounds in complex natural environments. While the human and animal auditory system is perfectly equipped to process the spectrotemporal sound features, adequate sound identification and categorization require neural sound representations that are invariant to irrelevant stimulus parameters. Crucially, what is relevant and irrelevant is not necessarily intrinsic to the physical stimulus structure but needs to be learned over time, often through integration of information from other senses. This review discusses the main principles underlying categorical sound perception with a special focus on the role of learning and neural plasticity. We examine the role of different neural structures along the auditory processing pathway in the formation of abstract sound representations with respect to hierarchical as well as dynamic and distributed processing models. Whereas most fMRI studies on categorical sound processing employed speech sounds, the emphasis of the current review lies on the contribution of empirical studies using natural or artificial sounds that enable separating acoustic and perceptual processing levels and avoid interference with existing category representations. Finally, we discuss the opportunities of modern analyses techniques such as multivariate pattern analysis (MVPA) in studying categorical sound representations. With their increased sensitivity to distributed activation changes—even in absence of changes in overall signal level—these analyses techniques provide a promising tool to reveal the neural underpinnings of perceptually invariant sound representations. PMID:24917783

Tailpulse signal generator

DOEpatents

Baker, John [Walnut Creek, CA; Archer, Daniel E [Knoxville, TN; Luke, Stanley John [Pleasanton, CA; Decman, Daniel J [Livermore, CA; White, Gregory K [Livermore, CA

2009-06-23

A tailpulse signal generating/simulating apparatus, system, and method designed to produce electronic pulses which simulate tailpulses produced by a gamma radiation detector, including the pileup effect caused by the characteristic exponential decay of the detector pulses, and the random Poisson distribution pulse timing for radioactive materials. A digital signal process (DSP) is programmed and configured to produce digital values corresponding to pseudo-randomly selected pulse amplitudes and pseudo-randomly selected Poisson timing intervals of the tailpulses. Pulse amplitude values are exponentially decayed while outputting the digital value to a digital to analog converter (DAC). And pulse amplitudes of new pulses are added to decaying pulses to simulate the pileup effect for enhanced realism in the simulation.

Sequence and batch language programs and alarm related C Programs for the 242-A MCS

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

Berger, J.F.

1996-04-15

A Distributive Process Control system was purchased by Project B-534, 242-A Evaporator/Crystallizer Upgrades. This control system, called the Monitor and Control system (MCS), was installed in the 242-A evaporator located in the 200 East Area. The purpose of the MCS is to monitor and control the Evaporator and monitor a number of alarms and other signals from various Tank Farm facilities. Applications software for the MCS was developed by the Waste Treatment Systems Engineering (WTSE) group of Westinghouse. The standard displays and alarm scheme provide for control and monitoring, but do not directly indicate the signal location or depict themore » overall process. To do this, WTSE developed a second alarm scheme.« less

FIBER AND INTEGRATED OPTICS. OPTOELECTRONICS: Some characteristics of formation of volume dynamic holograms by concurrent waves propagating in resonant atomic media

NASA Astrophysics Data System (ADS)

Kirilenko, A. K.

1989-07-01

An investigation was made of the transient process of formation of volume dynamic holograms by light within the spectral limits of the D2 resonant absorption line of sodium. The observed asymmetry of the spectral distribution of the gain of the signal waves in the case of a concurrent interaction between four beams was attributed to different mechanisms of the interaction, the main of which were a four-wave interaction in the long-wavelength wing and transient two-beam energy transfer in the short-wavelength wing. The results obtained were used to recommend an experimental method for the determination of the relative contributions of these processes to the amplification of signal waves.

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

DTIC Science & Technology

1991-12-01

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

Analysis of haptic information in the cerebral cortex

PubMed Central

2016-01-01

Haptic sensing of objects acquires information about a number of properties. This review summarizes current understanding about how these properties are processed in the cerebral cortex of macaques and humans. Nonnoxious somatosensory inputs, after initial processing in primary somatosensory cortex, are partially segregated into different pathways. A ventrally directed pathway carries information about surface texture into parietal opercular cortex and thence to medial occipital cortex. A dorsally directed pathway transmits information regarding the location of features on objects to the intraparietal sulcus and frontal eye fields. Shape processing occurs mainly in the intraparietal sulcus and lateral occipital complex, while orientation processing is distributed across primary somatosensory cortex, the parietal operculum, the anterior intraparietal sulcus, and a parieto-occipital region. For each of these properties, the respective areas outside primary somatosensory cortex also process corresponding visual information and are thus multisensory. Consistent with the distributed neural processing of haptic object properties, tactile spatial acuity depends on interaction between bottom-up tactile inputs and top-down attentional signals in a distributed neural network. Future work should clarify the roles of the various brain regions and how they interact at the network level. PMID:27440247

Sources of Bias in the Goodman-Kruskal Gamma Coefficient Measure of Association: Implications for Studies of Metacognitive Processes

ERIC Educational Resources Information Center

Masson, Michael E. J.; Rotello, Caren M.

2009-01-01

In many cognitive, metacognitive, and perceptual tasks, measurement of performance or prediction accuracy may be influenced by response bias. Signal detection theory provides a means of assessing discrimination accuracy independent of such bias, but its application crucially depends on distributional assumptions. The Goodman-Kruskal gamma…

Sensors Technology and Advanced Signal Processing Concepts for Layered Warfare/Layered Sensing

DTIC Science & Technology

2010-04-01

for challenged environments will require contributions from many diverse technical disciplines across AFRL, the Air Force and beyond. By providing a...APPROVED FOR PUBLIC RELEASE; DISTRIBUTION UNLIMITED. STINFO COPY AIR FORCE...UNITED STATES AIR FORCE AIR FORCE MATERIEL COMMAND NOTICE AND SIGNATURE PAGE Using Government drawings, specifications, or other data

Attentional Control in Visual Signal Detection: Effects of Abrupt-Onset and No-Onset Stimuli

ERIC Educational Resources Information Center

Sewell, David K.; Smith, Philip L.

2012-01-01

The attention literature distinguishes two general mechanisms by which attention can benefit performance: gain (or resource) models and orienting (or switching) models. In gain models, processing efficiency is a function of a spatial distribution of capacity or resources; in orienting models, an attentional spotlight must be aligned with the…

A comparison of decentralized, distributed, and centralized vibro-acoustic control.

PubMed

Frampton, Kenneth D; Baumann, Oliver N; Gardonio, Paolo

2010-11-01

Direct velocity feedback control of structures is well known to increase structural damping and thus reduce vibration. In multi-channel systems the way in which the velocity signals are used to inform the actuators ranges from decentralized control, through distributed or clustered control to fully centralized control. The objective of distributed controllers is to exploit the anticipated performance advantage of the centralized control while maintaining the scalability, ease of implementation, and robustness of decentralized control. However, and in seeming contradiction, some investigations have concluded that decentralized control performs as well as distributed and centralized control, while other results have indicated that distributed control has significant performance advantages over decentralized control. The purpose of this work is to explain this seeming contradiction in results, to explore the effectiveness of decentralized, distributed, and centralized vibro-acoustic control, and to expand the concept of distributed control to include the distribution of the optimization process and the cost function employed.

Spatially distributed modal signals of free shallow membrane shell structronic system

NASA Astrophysics Data System (ADS)

Yue, H. H.; Deng, Z. Q.; Tzou, H. S.

2008-11-01

Based on the smart material and structronics technology, distributed sensor and control of shell structures have been rapidly developed for the last 20 years. This emerging technology has been utilized in aerospace, telecommunication, micro-electromechanical systems and other engineering applications. However, distributed monitoring technique and its resulting global spatially distributed sensing signals of shallow paraboloidal membrane shells are not clearly understood. In this paper, modeling of free flexible paraboloidal shell with spatially distributed sensor, micro-sensing signal characteristics, and location of distributed piezoelectric sensor patches are investigated based on a new set of assumed mode shape functions. Parametric analysis indicates that the signal generation depends on modal membrane strains in the meridional and circumferential directions in which the latter is more significant than the former, when all bending strains vanish in membrane shells. This study provides a modeling and analysis technique for distributed sensors laminated on lightweight paraboloidal flexible structures and identifies critical components and regions that generate significant signals.

Pseudoinverse Decoding Process in Delay-Encoded Synthetic Transmit Aperture Imaging.

PubMed

Gong, Ping; Kolios, Michael C; Xu, Yuan

2016-09-01

Recently, we proposed a new method to improve the signal-to-noise ratio of the prebeamformed radio-frequency data in synthetic transmit aperture (STA) imaging: the delay-encoded STA (DE-STA) imaging. In the decoding process of DE-STA, the equivalent STA data were obtained by directly inverting the coding matrix. This is usually regarded as an ill-posed problem, especially under high noise levels. Pseudoinverse (PI) is usually used instead for seeking a more stable inversion process. In this paper, we apply singular value decomposition to the coding matrix to conduct the PI. Our numerical studies demonstrate that the singular values of the coding matrix have a special distribution, i.e., all the values are the same except for the first and last ones. We compare the PI in two cases: complete PI (CPI), where all the singular values are kept, and truncated PI (TPI), where the last and smallest singular value is ignored. The PI (both CPI and TPI) DE-STA processes are tested against noise with both numerical simulations and experiments. The CPI and TPI can restore the signals stably, and the noise mainly affects the prebeamformed signals corresponding to the first transmit channel. The difference in the overall enveloped beamformed image qualities between the CPI and TPI is negligible. Thus, it demonstrates that DE-STA is a relatively stable encoding and decoding technique. Also, according to the special distribution of the singular values of the coding matrix, we propose a new efficient decoding formula that is based on the conjugate transpose of the coding matrix. We also compare the computational complexity of the direct inverse and the new formula.

Machine learning based Intelligent cognitive network using fog computing

NASA Astrophysics Data System (ADS)

Lu, Jingyang; Li, Lun; Chen, Genshe; Shen, Dan; Pham, Khanh; Blasch, Erik

2017-05-01

In this paper, a Cognitive Radio Network (CRN) based on artificial intelligence is proposed to distribute the limited radio spectrum resources more efficiently. The CRN framework can analyze the time-sensitive signal data close to the signal source using fog computing with different types of machine learning techniques. Depending on the computational capabilities of the fog nodes, different features and machine learning techniques are chosen to optimize spectrum allocation. Also, the computing nodes send the periodic signal summary which is much smaller than the original signal to the cloud so that the overall system spectrum source allocation strategies are dynamically updated. Applying fog computing, the system is more adaptive to the local environment and robust to spectrum changes. As most of the signal data is processed at the fog level, it further strengthens the system security by reducing the communication burden of the communications network.

Operational safety assessment of turbo generators with wavelet Rényi entropy from sensor-dependent vibration signals.

PubMed

Zhang, Xiaoli; Wang, Baojian; Chen, Xuefeng

2015-04-16

With the rapid development of sensor technology, various professional sensors are installed on modern machinery to monitor operational processes and assure operational safety, which play an important role in industry and society. In this work a new operational safety assessment approach with wavelet Rényi entropy utilizing sensor-dependent vibration signals is proposed. On the basis of a professional sensor and the corresponding system, sensor-dependent vibration signals are acquired and analyzed by a second generation wavelet package, which reflects time-varying operational characteristic of individual machinery. Derived from the sensor-dependent signals' wavelet energy distribution over the observed signal frequency range, wavelet Rényi entropy is defined to compute the operational uncertainty of a turbo generator, which is then associated with its operational safety degree. The proposed method is applied in a 50 MW turbo generator, whereupon it is proved to be reasonable and effective for operation and maintenance.

Residual stress evaluation by Barkhausen signals with a magnetic field sensor for high efficiency electrical motors

NASA Astrophysics Data System (ADS)

Tsuchida, Yuji; Enokizono, Masato

2018-04-01

The iron loss of industrial motors increases by residual stress during manufacturing processes. It is very important to make clear the distribution of the residual stress in the motor cores to reduce the iron loss in the motors. Barkhausen signals which occur on electrical steel sheets can be used for the evaluation of the residual stress because they are very sensitive to the material properties. Generally, a B-sensor is used to measure Barkhausen signals, however, we developed a new H-sensor to measure them and applied it into the stress evaluation. It is supposed that the Barkhausen signals by using a H-sensor can be much effective to the residual stress on the electrical steel sheets by referring our results regarding to the stress evaluations. We evaluated the tensile stress of the electrical steel sheets by measuring Barkhausen signals by using our developed H-sensor for high efficiency electrical motors.

A Signal Processing Module for the Analysis of Heart Sounds and Heart Murmurs

NASA Astrophysics Data System (ADS)

Javed, Faizan; Venkatachalam, P. A.; H, Ahmad Fadzil M.

2006-04-01

In this paper a Signal Processing Module (SPM) for the computer-aided analysis of heart sounds has been developed. The module reveals important information of cardiovascular disorders and can assist general physician to come up with more accurate and reliable diagnosis at early stages. It can overcome the deficiency of expert doctors in rural as well as urban clinics and hospitals. The module has five main blocks: Data Acquisition & Pre-processing, Segmentation, Feature Extraction, Murmur Detection and Murmur Classification. The heart sounds are first acquired using an electronic stethoscope which has the capability of transferring these signals to the near by workstation using wireless media. Then the signals are segmented into individual cycles as well as individual components using the spectral analysis of heart without using any reference signal like ECG. Then the features are extracted from the individual components using Spectrogram and are used as an input to a MLP (Multiple Layer Perceptron) Neural Network that is trained to detect the presence of heart murmurs. Once the murmur is detected they are classified into seven classes depending on their timing within the cardiac cycle using Smoothed Pseudo Wigner-Ville distribution. The module has been tested with real heart sounds from 40 patients and has proved to be quite efficient and robust while dealing with a large variety of pathological conditions.

Identification and classification of failure modes in laminated composites by using a multivariate statistical analysis of wavelet coefficients

NASA Astrophysics Data System (ADS)

Baccar, D.; Söffker, D.

2017-11-01

Acoustic Emission (AE) is a suitable method to monitor the health of composite structures in real-time. However, AE-based failure mode identification and classification are still complex to apply due to the fact that AE waves are generally released simultaneously from all AE-emitting damage sources. Hence, the use of advanced signal processing techniques in combination with pattern recognition approaches is required. In this paper, AE signals generated from laminated carbon fiber reinforced polymer (CFRP) subjected to indentation test are examined and analyzed. A new pattern recognition approach involving a number of processing steps able to be implemented in real-time is developed. Unlike common classification approaches, here only CWT coefficients are extracted as relevant features. Firstly, Continuous Wavelet Transform (CWT) is applied to the AE signals. Furthermore, dimensionality reduction process using Principal Component Analysis (PCA) is carried out on the coefficient matrices. The PCA-based feature distribution is analyzed using Kernel Density Estimation (KDE) allowing the determination of a specific pattern for each fault-specific AE signal. Moreover, waveform and frequency content of AE signals are in depth examined and compared with fundamental assumptions reported in this field. A correlation between the identified patterns and failure modes is achieved. The introduced method improves the damage classification and can be used as a non-destructive evaluation tool.

Ship Detection in SAR Image Based on the Alpha-stable Distribution

PubMed Central

Wang, Changcheng; Liao, Mingsheng; Li, Xiaofeng

2008-01-01

This paper describes an improved Constant False Alarm Rate (CFAR) ship detection algorithm in spaceborne synthetic aperture radar (SAR) image based on Alpha-stable distribution model. Typically, the CFAR algorithm uses the Gaussian distribution model to describe statistical characteristics of a SAR image background clutter. However, the Gaussian distribution is only valid for multilook SAR images when several radar looks are averaged. As sea clutter in SAR images shows spiky or heavy-tailed characteristics, the Gaussian distribution often fails to describe background sea clutter. In this study, we replace the Gaussian distribution with the Alpha-stable distribution, which is widely used in impulsive or spiky signal processing, to describe the background sea clutter in SAR images. In our proposed algorithm, an initial step for detecting possible ship targets is employed. Then, similar to the typical two-parameter CFAR algorithm, a local process is applied to the pixel identified as possible target. A RADARSAT-1 image is used to validate this Alpha-stable distribution based algorithm. Meanwhile, known ship location data during the time of RADARSAT-1 SAR image acquisition is used to validate ship detection results. Validation results show improvements of the new CFAR algorithm based on the Alpha-stable distribution over the CFAR algorithm based on the Gaussian distribution. PMID:27873794

Faint Debris Detection by Particle Based Track-Before-Detect Method

NASA Astrophysics Data System (ADS)

Uetsuhara, M.; Ikoma, N.

2014-09-01

This study proposes a particle method to detect faint debris, which is hardly seen in single frame, from an image sequence based on the concept of track-before-detect (TBD). The most widely used detection method is detect-before-track (DBT), which firstly detects signals of targets from single frame by distinguishing difference of intensity between foreground and background then associate the signals for each target between frames. DBT is capable of tracking bright targets but limited. DBT is necessary to consider presence of false signals and is difficult to recover from false association. On the other hand, TBD methods try to track targets without explicitly detecting the signals followed by evaluation of goodness of each track and obtaining detection results. TBD has an advantage over DBT in detecting weak signals around background level in single frame. However, conventional TBD methods for debris detection apply brute-force search over candidate tracks then manually select true one from the candidates. To reduce those significant drawbacks of brute-force search and not-fully automated process, this study proposes a faint debris detection algorithm by a particle based TBD method consisting of sequential update of target state and heuristic search of initial state. The state consists of position, velocity direction and magnitude, and size of debris over the image at a single frame. The sequential update process is implemented by a particle filter (PF). PF is an optimal filtering technique that requires initial distribution of target state as a prior knowledge. An evolutional algorithm (EA) is utilized to search the initial distribution. The EA iteratively applies propagation and likelihood evaluation of particles for the same image sequences and resulting set of particles is used as an initial distribution of PF. This paper describes the algorithm of the proposed faint debris detection method. The algorithm demonstrates performance on image sequences acquired during observation campaigns dedicated to GEO breakup fragments, which would contain a sufficient number of faint debris images. The results indicate the proposed method is capable of tracking faint debris with moderate computational costs at operational level.

The sequentially discounting autoregressive (SDAR) method for on-line automatic seismic event detecting on long term observation

NASA Astrophysics Data System (ADS)

Wang, L.; Toshioka, T.; Nakajima, T.; Narita, A.; Xue, Z.

2017-12-01

In recent years, more and more Carbon Capture and Storage (CCS) studies focus on seismicity monitoring. For the safety management of geological CO2 storage at Tomakomai, Hokkaido, Japan, an Advanced Traffic Light System (ATLS) combined different seismic messages (magnitudes, phases, distributions et al.) is proposed for injection controlling. The primary task for ATLS is the seismic events detection in a long-term sustained time series record. Considering the time-varying characteristics of Signal to Noise Ratio (SNR) of a long-term record and the uneven energy distributions of seismic event waveforms will increase the difficulty in automatic seismic detecting, in this work, an improved probability autoregressive (AR) method for automatic seismic event detecting is applied. This algorithm, called sequentially discounting AR learning (SDAR), can identify the effective seismic event in the time series through the Change Point detection (CPD) of the seismic record. In this method, an anomaly signal (seismic event) can be designed as a change point on the time series (seismic record). The statistical model of the signal in the neighborhood of event point will change, because of the seismic event occurrence. This means the SDAR aims to find the statistical irregularities of the record thought CPD. There are 3 advantages of SDAR. 1. Anti-noise ability. The SDAR does not use waveform messages (such as amplitude, energy, polarization) for signal detecting. Therefore, it is an appropriate technique for low SNR data. 2. Real-time estimation. When new data appears in the record, the probability distribution models can be automatic updated by SDAR for on-line processing. 3. Discounting property. the SDAR introduces a discounting parameter to decrease the influence of present statistic value on future data. It makes SDAR as a robust algorithm for non-stationary signal processing. Within these 3 advantages, the SDAR method can handle the non-stationary time-varying long-term series and achieve real-time monitoring. Finally, we employ the SDAR on a synthetic model and Tomakomai Ocean Bottom Cable (OBC) baseline data to prove the feasibility and advantage of our method.

Design and Analysis of a Neuromemristive Reservoir Computing Architecture for Biosignal Processing

PubMed Central

Kudithipudi, Dhireesha; Saleh, Qutaiba; Merkel, Cory; Thesing, James; Wysocki, Bryant

2016-01-01

Reservoir computing (RC) is gaining traction in several signal processing domains, owing to its non-linear stateful computation, spatiotemporal encoding, and reduced training complexity over recurrent neural networks (RNNs). Previous studies have shown the effectiveness of software-based RCs for a wide spectrum of applications. A parallel body of work indicates that realizing RNN architectures using custom integrated circuits and reconfigurable hardware platforms yields significant improvements in power and latency. In this research, we propose a neuromemristive RC architecture, with doubly twisted toroidal structure, that is validated for biosignal processing applications. We exploit the device mismatch to implement the random weight distributions within the reservoir and propose mixed-signal subthreshold circuits for energy efficiency. A comprehensive analysis is performed to compare the efficiency of the neuromemristive RC architecture in both digital(reconfigurable) and subthreshold mixed-signal realizations. Both Electroencephalogram (EEG) and Electromyogram (EMG) biosignal benchmarks are used for validating the RC designs. The proposed RC architecture demonstrated an accuracy of 90 and 84% for epileptic seizure detection and EMG prosthetic finger control, respectively. PMID:26869876

Using a Simple Neural Network to Delineate Some Principles of Distributed Economic Choice.

PubMed

Balasubramani, Pragathi P; Moreno-Bote, Rubén; Hayden, Benjamin Y

2018-01-01

The brain uses a mixture of distributed and modular organization to perform computations and generate appropriate actions. While the principles under which the brain might perform computations using modular systems have been more amenable to modeling, the principles by which the brain might make choices using distributed principles have not been explored. Our goal in this perspective is to delineate some of those distributed principles using a neural network method and use its results as a lens through which to reconsider some previously published neurophysiological data. To allow for direct comparison with our own data, we trained the neural network to perform binary risky choices. We find that value correlates are ubiquitous and are always accompanied by non-value information, including spatial information (i.e., no pure value signals). Evaluation, comparison, and selection were not distinct processes; indeed, value signals even in the earliest stages contributed directly, albeit weakly, to action selection. There was no place, other than at the level of action selection, at which dimensions were fully integrated. No units were specialized for specific offers; rather, all units encoded the values of both offers in an anti-correlated format, thus contributing to comparison. Individual network layers corresponded to stages in a continuous rotation from input to output space rather than to functionally distinct modules. While our network is likely to not be a direct reflection of brain processes, we propose that these principles should serve as hypotheses to be tested and evaluated for future studies.

Using a Simple Neural Network to Delineate Some Principles of Distributed Economic Choice

PubMed Central

Balasubramani, Pragathi P.; Moreno-Bote, Rubén; Hayden, Benjamin Y.

2018-01-01

The brain uses a mixture of distributed and modular organization to perform computations and generate appropriate actions. While the principles under which the brain might perform computations using modular systems have been more amenable to modeling, the principles by which the brain might make choices using distributed principles have not been explored. Our goal in this perspective is to delineate some of those distributed principles using a neural network method and use its results as a lens through which to reconsider some previously published neurophysiological data. To allow for direct comparison with our own data, we trained the neural network to perform binary risky choices. We find that value correlates are ubiquitous and are always accompanied by non-value information, including spatial information (i.e., no pure value signals). Evaluation, comparison, and selection were not distinct processes; indeed, value signals even in the earliest stages contributed directly, albeit weakly, to action selection. There was no place, other than at the level of action selection, at which dimensions were fully integrated. No units were specialized for specific offers; rather, all units encoded the values of both offers in an anti-correlated format, thus contributing to comparison. Individual network layers corresponded to stages in a continuous rotation from input to output space rather than to functionally distinct modules. While our network is likely to not be a direct reflection of brain processes, we propose that these principles should serve as hypotheses to be tested and evaluated for future studies. PMID:29643773

Parametric adaptive filtering and data validation in the bar GW detector AURIGA

NASA Astrophysics Data System (ADS)

Ortolan, A.; Baggio, L.; Cerdonio, M.; Prodi, G. A.; Vedovato, G.; Vitale, S.

2002-04-01

We report on our experience gained in the signal processing of the resonant GW detector AURIGA. Signal amplitude and arrival time are estimated by means of a matched-adaptive Wiener filter. The detector noise, entering in the filter set-up, is modelled as a parametric ARMA process; to account for slow non-stationarity of the noise, the ARMA parameters are estimated on an hourly basis. A requirement of the set-up of an unbiased Wiener filter is the separation of time spans with 'almost Gaussian' noise from non-Gaussian and/or strongly non-stationary time spans. The separation algorithm consists basically of a variance estimate with the Chauvenet convergence method and a threshold on the Curtosis index. The subsequent validation of data is strictly connected with the separation procedure: in fact, by injecting a large number of artificial GW signals into the 'almost Gaussian' part of the AURIGA data stream, we have demonstrated that the effective probability distributions of the signal-to-noise ratio χ2 and the time of arrival are those that are expected.

Speech coding and compression using wavelets and lateral inhibitory networks

NASA Astrophysics Data System (ADS)

Ricart, Richard

1990-12-01

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

On estimating the phase of periodic waveform in additive Gaussian noise, part 2

NASA Astrophysics Data System (ADS)

Rauch, L. L.

1984-11-01

Motivated by advances in signal processing technology that support more complex algorithms, a new look is taken at the problem of estimating the phase and other parameters of a periodic waveform in additive Gaussian noise. The general problem was introduced and the maximum a posteriori probability criterion with signal space interpretation was used to obtain the structures of optimum and some suboptimum phase estimators for known constant frequency and unknown constant phase with an a priori distribution. Optimal algorithms are obtained for some cases where the frequency is a parameterized function of time with the unknown parameters and phase having a joint a priori distribution. In the last section, the intrinsic and extrinsic geometry of hypersurfaces is introduced to provide insight to the estimation problem for the small noise and large noise cases.

On Estimating the Phase of Periodic Waveform in Additive Gaussian Noise, Part 2

NASA Technical Reports Server (NTRS)

Rauch, L. L.

1984-01-01

Motivated by advances in signal processing technology that support more complex algorithms, a new look is taken at the problem of estimating the phase and other parameters of a periodic waveform in additive Gaussian noise. The general problem was introduced and the maximum a posteriori probability criterion with signal space interpretation was used to obtain the structures of optimum and some suboptimum phase estimators for known constant frequency and unknown constant phase with an a priori distribution. Optimal algorithms are obtained for some cases where the frequency is a parameterized function of time with the unknown parameters and phase having a joint a priori distribution. In the last section, the intrinsic and extrinsic geometry of hypersurfaces is introduced to provide insight to the estimation problem for the small noise and large noise cases.

Distributed magnetic field positioning system using code division multiple access

NASA Technical Reports Server (NTRS)

Prigge, Eric A. (Inventor)

2003-01-01

An apparatus and methods for a magnetic field positioning system use a fundamentally different, and advantageous, signal structure and multiple access method, known as Code Division Multiple Access (CDMA). This signal architecture, when combined with processing methods, leads to advantages over the existing technologies, especially when applied to a system with a large number of magnetic field generators (beacons). Beacons at known positions generate coded magnetic fields, and a magnetic sensor measures a sum field and decomposes it into component fields to determine the sensor position and orientation. The apparatus and methods can have a large `building-sized` coverage area. The system allows for numerous beacons to be distributed throughout an area at a number of different locations. A method to estimate position and attitude, with no prior knowledge, uses dipole fields produced by these beacons in different locations.

Far-field DOA estimation and source localization for different scenarios in a distributed sensor network

NASA Astrophysics Data System (ADS)

Asgari, Shadnaz

Recent developments in the integrated circuits and wireless communications not only open up many possibilities but also introduce challenging issues for the collaborative processing of signals for source localization and beamforming in an energy-constrained distributed sensor network. In signal processing, various sensor array processing algorithms and concepts have been adopted, but must be further tailored to match the communication and computational constraints. Sometimes the constraints are such that none of the existing algorithms would be an efficient option for the defined problem and as the result; the necessity of developing a new algorithm becomes undeniable. In this dissertation, we present the theoretical and the practical issues of Direction-Of-Arrival (DOA) estimation and source localization using the Approximate-Maximum-Likelihood (AML) algorithm for different scenarios. We first investigate a robust algorithm design for coherent source DOA estimation in a limited reverberant environment. Then, we provide a least-square (LS) solution for source localization based on our newly proposed virtual array model. In another scenario, we consider the determination of the location of a disturbance source which emits both wideband acoustic and seismic signals. We devise an enhanced AML algorithm to process the data collected at the acoustic sensors. For processing the seismic signals, two distinct algorithms are investigated to determine the DOAs. Then, we consider a basic algorithm for fusion of the results yielded by the acoustic and seismic arrays. We also investigate the theoretical and practical issues of DOA estimation in a three-dimensional (3D) scenario. We show that the performance of the proposed 3D AML algorithm converges to the Cramer-Rao Bound. We use the concept of an isotropic array to reduce the complexity of the proposed algorithm by advocating a decoupled 3D version. We also explore a modified version of the decoupled 3D AML algorithm which can be used for DOA estimation with non-isotropic arrays. In this dissertation, for each scenario, efficient numerical implementations of the corresponding AML algorithm are derived and applied into a real-time sensor network testbed. Extensive simulations as well as experimental results are presented to verify the effectiveness of the proposed algorithms.

Proton Radiation Effects on Dark Signal Distribution of PPD CMOS Image Sensors: Both TID and DDD Effects.

PubMed

Xue, Yuanyuan; Wang, Zujun; Chen, Wei; Liu, Minbo; He, Baoping; Yao, Zhibin; Sheng, Jiangkun; Ma, Wuying; Dong, Guantao; Jin, Junshan

2017-11-30

Four-transistor (T) pinned photodiode (PPD) CMOS image sensors (CISs) with four-megapixel resolution using 11µm pitch high dynamic range pixel were radiated with 3 MeV and 10MeV protons. The dark signal was measured pre- and post-radiation, with the dark signal post irradiation showing a remarkable increase. A theoretical method of dark signal distribution pre- and post-radiation is used to analyze the degradation mechanisms of the dark signal distribution. The theoretical results are in good agreement with experimental results. This research would provide a good understanding of the proton radiation effects on the CIS and make it possible to predict the dark signal distribution of the CIS under the complex proton radiation environments.

Statistical learning in songbirds: from self-tutoring to song culture.

PubMed

Fehér, Olga; Ljubičić, Iva; Suzuki, Kenta; Okanoya, Kazuo; Tchernichovski, Ofer

2017-01-05

At the onset of vocal development, both songbirds and humans produce variable vocal babbling with broadly distributed acoustic features. Over development, these vocalizations differentiate into the well-defined, categorical signals that characterize adult vocal behaviour. A broadly distributed signal is ideal for vocal exploration, that is, for matching vocal production to the statistics of the sensory input. The developmental transition to categorical signals is a gradual process during which the vocal output becomes differentiated and stable. But does it require categorical input? We trained juvenile zebra finches with playbacks of their own developing song, produced just a few moments earlier, updated continuously over development. Although the vocalizations of these self-tutored (ST) birds were initially broadly distributed, birds quickly developed categorical signals, as fast as birds that were trained with a categorical, adult song template. By contrast, siblings of those birds that received no training (isolates) developed phonological categories much more slowly and never reached the same level of category differentiation as their ST brothers. Therefore, instead of simply mirroring the statistical properties of their sensory input, songbirds actively transform it into distinct categories. We suggest that the early self-generation of phonological categories facilitates the establishment of vocal culture by making the song easier to transmit at the micro level, while promoting stability of shared vocabulary at the group level over generations.This article is part of the themed issue 'New frontiers for statistical learning in the cognitive sciences'. © 2016 The Authors.

Nanoscale femtosecond imaging of transient hot solid density plasmas with elemental and charge state sensitivity using resonant coherent diffraction

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

Kluge, T., E-mail: t.kluge@hzdr.de; Bussmann, M.; Huang, L. G., E-mail: lingen.huang@hzdr.de

Here, we propose to exploit the low energy bandwidth, small wavelength, and penetration power of ultrashort pulses from XFELs for resonant Small Angle Scattering (SAXS) on plasma structures in laser excited plasmas. Small angle scattering allows to detect nanoscale density fluctuations in forward scattering direction. Typically, the SAXS signal from laser excited plasmas is expected to be dominated by the free electron distribution. We propose that the ionic scattering signal becomes visible when the X-ray energy is in resonance with an electron transition between two bound states (resonant coherent X-ray diffraction). In this case, the scattering cross-section dramatically increases somore » that the signal of X-ray scattering from ions silhouettes against the free electron scattering background which allows to measure the opacity and derived quantities with high spatial and temporal resolution, being fundamentally limited only by the X-ray wavelength and timing. Deriving quantities such as ion spatial distribution, charge state distribution, and plasma temperature with such high spatial and temporal resolution will make a vast number of processes in shortpulse laser-solid interaction accessible for direct experimental observation, e.g., hole-boring and shock propagation, filamentation and instability dynamics, electron transport, heating, and ultrafast ionization dynamics.« less

Quantification of thrombus formation in malapposed coronary stents deployed in vitro through imaging analysis.

PubMed

Brown, Jonathan; O'Brien, Caroline C; Lopes, Augusto C; Kolandaivelu, Kumaran; Edelman, Elazer R

2018-04-11

Stent thrombosis is a major complication of coronary stent and scaffold intervention. While often unanticipated and lethal, its incidence is low making mechanistic examination difficult through clinical investigation alone. Thus, throughout the technological advancement of these devices, experimental models have been indispensable in furthering our understanding of device safety and efficacy. As we refine model systems to gain deeper insight into adverse events, it is equally important that we continue to refine our measurement methods. We used digital signal processing in an established flow loop model to investigate local flow effects due to geometric stent features and ultimately its relationship to thrombus formation. A new metric of clot distribution on each microCT slice termed normalized clot ratio was defined to quantify this distribution. Three under expanded coronary bare-metal stents were run in a flow loop model to induce clotting. Samples were then scanned in a MicroCT machine and digital signal processing methods applied to analyze geometric stent conformation and spatial clot formation. Results indicated that geometric stent features play a significant role in clotting patterns, specifically at a frequency of 0.6225 Hz corresponding to a geometric distance of 1.606 mm. The magnitude-squared coherence between geometric features and clot distribution was greater than 0.4 in all samples. In stents with poor wall apposition, ranging from 0.27 mm to 0.64 mm maximum malapposition (model of real-world heterogeneity), clots were found to have formed in between stent struts rather than directly adjacent to struts. This early work shows how the combination of tools in the areas of image processing and signal analysis can advance the resolution at which we are able to define thrombotic mechanisms in in vitro models, and ultimately, gain further insight into clinical performance. Copyright © 2018 Elsevier Ltd. All rights reserved.

Packaging signals in single-stranded RNA viruses: nature's alternative to a purely electrostatic assembly mechanism.

PubMed

Stockley, Peter G; Twarock, Reidun; Bakker, Saskia E; Barker, Amy M; Borodavka, Alexander; Dykeman, Eric; Ford, Robert J; Pearson, Arwen R; Phillips, Simon E V; Ranson, Neil A; Tuma, Roman

2013-03-01

The formation of a protective protein container is an essential step in the life-cycle of most viruses. In the case of single-stranded (ss)RNA viruses, this step occurs in parallel with genome packaging in a co-assembly process. Previously, it had been thought that this process can be explained entirely by electrostatics. Inspired by recent single-molecule fluorescence experiments that recapitulate the RNA packaging specificity seen in vivo for two model viruses, we present an alternative theory, which recognizes the important cooperative roles played by RNA-coat protein interactions, at sites we have termed packaging signals. The hypothesis is that multiple copies of packaging signals, repeated according to capsid symmetry, aid formation of the required capsid protein conformers at defined positions, resulting in significantly enhanced assembly efficiency. The precise mechanistic roles of packaging signal interactions may vary between viruses, as we have demonstrated for MS2 and STNV. We quantify the impact of packaging signals on capsid assembly efficiency using a dodecahedral model system, showing that heterogeneous affinity distributions of packaging signals for capsid protein out-compete those of homogeneous affinities. These insights pave the way to a new anti-viral therapy, reducing capsid assembly efficiency by targeting of the vital roles of the packaging signals, and opens up new avenues for the efficient construction of protein nanocontainers in bionanotechnology.

An artificial EMG generation model based on signal-dependent noise and related application to motion classification

PubMed Central

Hayashi, Hideaki; Nakamura, Go; Chin, Takaaki; Tsuji, Toshio

2017-01-01

This paper proposes an artificial electromyogram (EMG) signal generation model based on signal-dependent noise, which has been ignored in existing methods, by introducing the stochastic construction of the EMG signals. In the proposed model, an EMG signal variance value is first generated from a probability distribution with a shape determined by a commanded muscle force and signal-dependent noise. Artificial EMG signals are then generated from the associated Gaussian distribution with a zero mean and the generated variance. This facilitates representation of artificial EMG signals with signal-dependent noise superimposed according to the muscle activation levels. The frequency characteristics of the EMG signals are also simulated via a shaping filter with parameters determined by an autoregressive model. An estimation method to determine EMG variance distribution using rectified and smoothed EMG signals, thereby allowing model parameter estimation with a small number of samples, is also incorporated in the proposed model. Moreover, the prediction of variance distribution with strong muscle contraction from EMG signals with low muscle contraction and related artificial EMG generation are also described. The results of experiments conducted, in which the reproduction capability of the proposed model was evaluated through comparison with measured EMG signals in terms of amplitude, frequency content, and EMG distribution demonstrate that the proposed model can reproduce the features of measured EMG signals. Further, utilizing the generated EMG signals as training data for a neural network resulted in the classification of upper limb motion with a higher precision than by learning from only measured EMG signals. This indicates that the proposed model is also applicable to motion classification. PMID:28640883

Nonlinear optical coupler using a doped optical waveguide

DOEpatents

Pantell, Richard H.; Sadowski, Robert W.; Digonnet, Michel J. F.; Shaw, Herbert J.

1994-01-01

An optical mode coupling apparatus includes an Erbium-doped optical waveguide in which an optical signal at a signal wavelength propagates in a first spatial propagation mode and a second spatial propagation mode of the waveguide. The optical signal propagating in the waveguide has a beat length. The coupling apparatus includes a pump source of perturbational light signal at a perturbational wavelength that propagates in the waveguide in the first spatial propagation mode. The perturbational signal has a sufficient intensity distribution in the waveguide that it causes a perturbation of the effective refractive index of the first spatial propagation mode of the waveguide in accordance with the optical Kerr effect. The perturbation of the effective refractive index of the first spatial propagation mode of the optical waveguide causes a change in the differential phase delay in the optical signal propagating in the first and second spatial propagation modes. The change in the differential phase delay is detected as a change in the intensity distribution between two lobes of the optical intensity distribution pattern of an output signal. The perturbational light signal can be selectively enabled and disabled to selectively change the intensity distribution in the two lobes of the optical intensity distribution pattern.

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.

Spatiotemporal intracellular dynamics of neurotrophin and its receptors. Implications for neurotrophin signaling and neuronal function.

PubMed

Bronfman, F C; Lazo, O M; Flores, C; Escudero, C A

2014-01-01

Neurons possess a polarized morphology specialized to contribute to neuronal networks, and this morphology imposes an important challenge for neuronal signaling and communication. The physiology of the network is regulated by neurotrophic factors that are secreted in an activity-dependent manner modulating neuronal connectivity. Neurotrophins are a well-known family of neurotrophic factors that, together with their cognate receptors, the Trks and the p75 neurotrophin receptor, regulate neuronal plasticity and survival and determine the neuronal phenotype in healthy and regenerating neurons. Is it now becoming clear that neurotrophin signaling and vesicular transport are coordinated to modify neuronal function because disturbances of vesicular transport mechanisms lead to disturbed neurotrophin signaling and to diseases of the nervous system. This chapter summarizes our current understanding of how the regulated secretion of neurotrophin, the distribution of neurotrophin receptors in different locations of neurons, and the intracellular transport of neurotrophin-induced signaling in distal processes are achieved to allow coordinated neurotrophin signaling in the cell body and axons.

Vps35 loss promotes hyperresorptive osteoclastogenesis and osteoporosis via sustained RANKL signaling

PubMed Central

Xia, Wen-Fang; Tang, Fu-Lei; Xiong, Lei; Xiong, Shan; Jung, Ji-Ung; Lee, Dae-Hoon; Li, Xing-Sheng; Feng, Xu; Mei, Lin

2013-01-01

Receptor activator of NF-κB (RANK) plays a critical role in osteoclastogenesis, an essential process for the initiation of bone remodeling to maintain healthy bone mass and structure. Although the signaling and function of RANK have been investigated extensively, much less is known about the negative regulatory mechanisms of its signaling. We demonstrate in this paper that RANK trafficking, signaling, and function are regulated by VPS35, a major component of the retromer essential for selective endosome to Golgi retrieval of membrane proteins. VPS35 loss of function altered RANK ligand (RANKL)–induced RANK distribution, enhanced RANKL sensitivity, sustained RANKL signaling, and increased hyperresorptive osteoclast (OC) formation. Hemizygous deletion of the Vps35 gene in mice promoted hyperresorptive osteoclastogenesis, decreased bone formation, and caused a subsequent osteoporotic deficit, including decreased trabecular bone volumes and reduced trabecular thickness and density in long bones. These results indicate that VPS35 critically deregulates RANK signaling, thus restraining increased formation of hyperresorptive OCs and preventing osteoporotic deficits. PMID:23509071

The impact of command signal power distribution, processing delays, and speed scaling on neurally-controlled devices.

PubMed

Marathe, A R; Taylor, D M

2015-08-01

Decoding algorithms for brain-machine interfacing (BMI) are typically only optimized to reduce the magnitude of decoding errors. Our goal was to systematically quantify how four characteristics of BMI command signals impact closed-loop performance: (1) error magnitude, (2) distribution of different frequency components in the decoding errors, (3) processing delays, and (4) command gain. To systematically evaluate these different command features and their interactions, we used a closed-loop BMI simulator where human subjects used their own wrist movements to command the motion of a cursor to targets on a computer screen. Random noise with three different power distributions and four different relative magnitudes was added to the ongoing cursor motion in real time to simulate imperfect decoding. These error characteristics were tested with four different visual feedback delays and two velocity gains. Participants had significantly more trouble correcting for errors with a larger proportion of low-frequency, slow-time-varying components than they did with jittery, higher-frequency errors, even when the error magnitudes were equivalent. When errors were present, a movement delay often increased the time needed to complete the movement by an order of magnitude more than the delay itself. Scaling down the overall speed of the velocity command can actually speed up target acquisition time when low-frequency errors and delays are present. This study is the first to systematically evaluate how the combination of these four key command signal features (including the relatively-unexplored error power distribution) and their interactions impact closed-loop performance independent of any specific decoding method. The equations we derive relating closed-loop movement performance to these command characteristics can provide guidance on how best to balance these different factors when designing BMI systems. The equations reported here also provide an efficient way to compare a diverse range of decoding options offline.

The impact of command signal power distribution, processing delays, and speed scaling on neurally-controlled devices

NASA Astrophysics Data System (ADS)

Marathe, A. R.; Taylor, D. M.

2015-08-01

Objective. Decoding algorithms for brain-machine interfacing (BMI) are typically only optimized to reduce the magnitude of decoding errors. Our goal was to systematically quantify how four characteristics of BMI command signals impact closed-loop performance: (1) error magnitude, (2) distribution of different frequency components in the decoding errors, (3) processing delays, and (4) command gain. Approach. To systematically evaluate these different command features and their interactions, we used a closed-loop BMI simulator where human subjects used their own wrist movements to command the motion of a cursor to targets on a computer screen. Random noise with three different power distributions and four different relative magnitudes was added to the ongoing cursor motion in real time to simulate imperfect decoding. These error characteristics were tested with four different visual feedback delays and two velocity gains. Main results. Participants had significantly more trouble correcting for errors with a larger proportion of low-frequency, slow-time-varying components than they did with jittery, higher-frequency errors, even when the error magnitudes were equivalent. When errors were present, a movement delay often increased the time needed to complete the movement by an order of magnitude more than the delay itself. Scaling down the overall speed of the velocity command can actually speed up target acquisition time when low-frequency errors and delays are present. Significance. This study is the first to systematically evaluate how the combination of these four key command signal features (including the relatively-unexplored error power distribution) and their interactions impact closed-loop performance independent of any specific decoding method. The equations we derive relating closed-loop movement performance to these command characteristics can provide guidance on how best to balance these different factors when designing BMI systems. The equations reported here also provide an efficient way to compare a diverse range of decoding options offline.

Integrating physically based simulators with Event Detection Systems: Multi-site detection approach.

PubMed

Housh, Mashor; Ohar, Ziv

2017-03-01

The Fault Detection (FD) Problem in control theory concerns of monitoring a system to identify when a fault has occurred. Two approaches can be distinguished for the FD: Signal processing based FD and Model-based FD. The former concerns of developing algorithms to directly infer faults from sensors' readings, while the latter uses a simulation model of the real-system to analyze the discrepancy between sensors' readings and expected values from the simulation model. Most contamination Event Detection Systems (EDSs) for water distribution systems have followed the signal processing based FD, which relies on analyzing the signals from monitoring stations independently of each other, rather than evaluating all stations simultaneously within an integrated network. In this study, we show that a model-based EDS which utilizes a physically based water quality and hydraulics simulation models, can outperform the signal processing based EDS. We also show that the model-based EDS can facilitate the development of a Multi-Site EDS (MSEDS), which analyzes the data from all the monitoring stations simultaneously within an integrated network. The advantage of the joint analysis in the MSEDS is expressed by increased detection accuracy (higher true positive alarms and fewer false alarms) and shorter detection time. Copyright © 2016 Elsevier Ltd. All rights reserved.

Modeling Array Stations in SIG-VISA

NASA Astrophysics Data System (ADS)

Ding, N.; Moore, D.; Russell, S.

2013-12-01

We add support for array stations to SIG-VISA, a system for nuclear monitoring using probabilistic inference on seismic signals. Array stations comprise a large portion of the IMS network; they can provide increased sensitivity and more accurate directional information compared to single-component stations. Our existing model assumed that signals were independent at each station, which is false when lots of stations are close together, as in an array. The new model removes that assumption by jointly modeling signals across array elements. This is done by extending our existing Gaussian process (GP) regression models, also known as kriging, from a 3-dimensional single-component space of events to a 6-dimensional space of station-event pairs. For each array and each event attribute (including coda decay, coda height, amplitude transfer and travel time), we model the joint distribution across array elements using a Gaussian process that learns the correlation lengthscale across the array, thereby incorporating information of array stations into the probabilistic inference framework. To evaluate the effectiveness of our model, we perform ';probabilistic beamforming' on new events using our GP model, i.e., we compute the event azimuth having highest posterior probability under the model, conditioned on the signals at array elements. We compare the results from our probabilistic inference model to the beamforming currently performed by IMS station processing.

On the properties of stochastic intermittency in rainfall processes.

PubMed

Molini, A; La, Barbera P; Lanza, L G

2002-01-01

In this work we propose a mixed approach to deal with the modelling of rainfall events, based on the analysis of geometrical and statistical properties of rain intermittency in time, combined with the predictability power derived from the analysis of no-rain periods distribution and from the binary decomposition of the rain signal. Some recent hypotheses on the nature of rain intermittency are reviewed too. In particular, the internal intermittent structure of a high resolution pluviometric time series covering one decade and recorded at the tipping bucket station of the University of Genova is analysed, by separating the internal intermittency of rainfall events from the inter-arrival process through a simple geometrical filtering procedure. In this way it is possible to associate no-rain intervals with a probability distribution both in virtue of their position within the event and their percentage. From this analysis, an invariant probability distribution for the no-rain periods within the events is obtained at different aggregation levels and its satisfactory agreement with a typical extreme value distribution is shown.

Adaptive signal processing and higher order time- frequency analysis for acoustic and vibration signatures in condition monitoring

NASA Astrophysics Data System (ADS)

Lee, Sang-Kwon

This thesis is concerned with the development of a useful engineering technique to detect and analyse faults in rotating machinery. The methods developed are based on the advanced signal processing such as the adaptive signal processing and higher-order time frequency methods. The two-stage Adaptive Line Enhancer (ALE), using adaptive signal processing, has been developed for increasing the Signal to Noise Ratio of impulsive signals. The enhanced signal can then be analysed using time frequency methods to identify fault characteristics. However, if after pre-processing by the two stage ALE, the SNR of the signals is low, the residual noise often hinders clear identification of the fault characteristics in the time-frequency domain. In such cases, higher order time-frequency methods have been proposed and studied. As examples of rotating machinery, the internal combustion engine and an industrial gear box are considered in this thesis. The noise signal from an internal combustion engine and vibration signal measured on a gear box are studied in detail. Typically an impulsive signal manifests itself when the fault occurs in the machinery and is embedded in background noise, such as the fundamental frequency and its harmonic orders of the rotation speed and broadband noise. The two-stage ALE is developed for reducing this background noise. Conditions for the choice of adaptive filter parameters are studied and suitable adaptive algorithms given. The enhanced impulsive signal is analysed in the time- frequency domain using the Wigner higher order moment spectra (WHOMS) and the multi-time WHOMS (which is a dual form of the WHOMS). The WHOMS suffers from unwanted cross-terms, which increase dramatically as the order increases. Novel expressions for the cross-terms in WHOMS have been presented. The number of cross-terms can be reduced by taking the principal slice of the WHOMS. The residual cross-terms are smoothed by using a general class of kernel functions and the γ-method kernel function which is a novel development in this thesis. The WVD and the sliced WHOMS for synthesised signals and measured data from rotating machinery are analysed. The estimated ROC (Receive Operating Characteristic) curves for these methods are computed. These results lead to the conclusion that the detection performance when using the sliced WHOMS, for impulsive signals in embedded in broadband noise, is better than that of the Wigner-Ville distribution. Real data from a faulty car engine and faulty industrial gears are analysed. The car engine radiates an impulsive noise signal due to the loosening of a spark plug. The faulty industrial gear produces an impulsive vibration signal due to a spall on the tooth face in gear. The two- stage ALE and WHOMS are successfully applied to detection and analysis of these impulsive signals.

Some-or-none recollection: Evidence from item and source memory.

PubMed

Onyper, Serge V; Zhang, Yaofei X; Howard, Marc W

2010-05-01

Dual-process theory hypothesizes that recognition memory depends on 2 distinguishable memory signals. Recollection reflects conscious recovery of detailed information about the learning episode. Familiarity reflects a memory signal that is not accompanied by a vivid conscious experience but nonetheless enables participants to distinguish recently experienced probe items from novel ones. This dual-process explanation of recognition memory has gained wide acceptance among cognitive neuroscientists and some cognitive psychologists. Nonetheless, its difficulty in providing a quantitatively satisfactory description of performance has precluded a consensus not only regarding the theoretical structure of recognition memory but also about how to best measure recognition accuracy. In 2 experiments we show that neither the standard formulation of dual-process signal detection (DPSD) theory nor a widely used single-process model called the unequal-variance signal-detection (UVSD) model provides a satisfactory explanation of recognition memory across different types of stimuli (words and travel scenes). In the variable-recollection dual-process (VRDP) model, recollection fails for some old probe items, as in standard formulations of DPSD, but gives rise to a continuous distribution of memory strengths when it succeeds. The VRDP can approximate both the DPSD and UVSD. In both experiments it provides a consistently superior fit across materials to the superset of the DPSD and UVSD. The VRDP offers a simple explanation of the form of conjoint item-source judgments, something neither the DPSD nor UVSD accomplishes. The success of the VRDP supports the core assumptions of dual-process theory by providing an excellent quantitative description of recognition performance across materials and response criteria.

ICC '86; Proceedings of the International Conference on Communications, Toronto, Canada, June 22-25, 1986, Conference Record. Volumes 1, 2, & 3

NASA Astrophysics Data System (ADS)

Papers are presented on ISDN, mobile radio systems and techniques for digital connectivity, centralized and distributed algorithms in computer networks, communications networks, quality assurance and impact on cost, adaptive filters in communications, the spread spectrum, signal processing, video communication techniques, and digital satellite services. Topics discussed include performance evaluation issues for integrated protocols, packet network operations, the computer network theory and multiple-access, microwave single sideband systems, switching architectures, fiber optic systems, wireless local communications, modulation, coding, and synchronization, remote switching, software quality, transmission, and expert systems in network operations. Consideration is given to wide area networks, image and speech processing, office communications application protocols, multimedia systems, customer-controlled network operations, digital radio systems, channel modeling and signal processing in digital communications, earth station/on-board modems, computer communications system performance evaluation, source encoding, compression, and quantization, and adaptive communications systems.

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.

Modified DCTNet for audio signals classification

NASA Astrophysics Data System (ADS)

Xian, Yin; Pu, Yunchen; Gan, Zhe; Lu, Liang; Thompson, Andrew

2016-10-01

In this paper, we investigate DCTNet for audio signal classification. Its output feature is related to Cohen's class of time-frequency distributions. We introduce the use of adaptive DCTNet (A-DCTNet) for audio signals feature extraction. The A-DCTNet applies the idea of constant-Q transform, with its center frequencies of filterbanks geometrically spaced. The A-DCTNet is adaptive to different acoustic scales, and it can better capture low frequency acoustic information that is sensitive to human audio perception than features such as Mel-frequency spectral coefficients (MFSC). We use features extracted by the A-DCTNet as input for classifiers. Experimental results show that the A-DCTNet and Recurrent Neural Networks (RNN) achieve state-of-the-art performance in bird song classification rate, and improve artist identification accuracy in music data. They demonstrate A-DCTNet's applicability to signal processing problems.

Anticipatory control of xenon in a pressurized water reactor

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

Impink, A.J. Jr.

1987-02-10

A method is described for automatically dampening xenon-135 spatial transients in the core of a pressurized water reactor having control rods which regulate reactor power level, comprising the steps of: measuring the neutron flu in the reactor core at a plurality of axially spaced locations on a real-time, on-line basis; repetitively generating from the neutron flux measurements, on a point-by-point basis, signals representative of the current axial distribution of xenon-135, and signals representative of the current rate of change of the axial distribution of xenon-135; generating from the xenon-135 distribution signals and the rate of change of xenon distribution signals,more » control signals for reducing the xenon transients; and positioning the control rods as a function of the control signals to dampen the xenon-135 spatial transients.« less

A hybrid optic-fiber sensor network with the function of self-diagnosis and self-healing

NASA Astrophysics Data System (ADS)

Xu, Shibo; Liu, Tiegen; Ge, Chunfeng; Chen, Cheng; Zhang, Hongxia

2014-11-01

We develop a hybrid wavelength division multiplexing optical fiber network with distributed fiber-optic sensors and quasi-distributed FBG sensor arrays which detect vibrations, temperatures and strains at the same time. The network has the ability to locate the failure sites automatically designated as self-diagnosis and make protective switching to reestablish sensing service designated as self-healing by cooperative work of software and hardware. The processes above are accomplished by master-slave processors with the help of optical and wireless telemetry signals. All the sensing and optical telemetry signals transmit in the same fiber either working fiber or backup fiber. We take wavelength 1450nm as downstream signal and wavelength 1350nm as upstream signal to control the network in normal circumstances, both signals are sent by a light emitting node of the corresponding processor. There is also a continuous laser wavelength 1310nm sent by each node and received by next node on both working and backup fibers to monitor their healthy states, but it does not carry any message like telemetry signals do. When fibers of two sensor units are completely damaged, the master processor will lose the communication with the node between the damaged ones.However we install RF module in each node to solve the possible problem. Finally, the whole network state is transmitted to host computer by master processor. Operator could know and control the network by human-machine interface if needed.

Cascaded analysis of signal and noise propagation through a heterogeneous breast model.

PubMed

Mainprize, James G; Yaffe, Martin J

2010-10-01

The detectability of lesions in radiographic images can be impaired by patterns caused by the surrounding anatomic structures. The presence of such patterns is often referred to as anatomic noise. Others have previously extended signal and noise propagation theory to include variable background structure as an additional noise term and used in simulations for analysis by human and ideal observers. Here, the analytic forms of the signal and noise transfer are derived to obtain an exact expression for any input random distribution and the "power law" filter used to generate the texture of the tissue distribution. A cascaded analysis of propagation through a heterogeneous model is derived for x-ray projection through simulated heterogeneous backgrounds. This is achieved by considering transmission through the breast as a correlated amplification point process. The analytic forms of the cascaded analysis were compared to monoenergetic Monte Carlo simulations of x-ray propagation through power law structured backgrounds. As expected, it was found that although the quantum noise power component scales linearly with the x-ray signal, the anatomic noise will scale with the square of the x-ray signal. There was a good agreement between results obtained using analytic expressions for the noise power and those from Monte Carlo simulations for different background textures, random input functions, and x-ray fluence. Analytic equations for the signal and noise properties of heterogeneous backgrounds were derived. These may be used in direct analysis or as a tool to validate simulations in evaluating detectability.

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

PubMed

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

2006-01-01

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

Distributing Frequency And Time Signals On Optical Fibers

NASA Technical Reports Server (NTRS)

Lutes, George F.

1993-01-01

Paper reports progress in distribution of frequency and time reference signals over optical fibers. Describes current performance at frequencies of 100 MHz, 1 GHz, and 8.4 GHz. Also describes transmitting and receiving equipment and discusses tradeoff between cost and performance. Concludes with discussion of likely future development and effects of developments on systems using distributed frequency reference signals.

Glycogen distribution in the microwave-fixed mouse brain reveals heterogeneous astrocytic patterns.

PubMed

Oe, Yuki; Baba, Otto; Ashida, Hitoshi; Nakamura, Kouichi C; Hirase, Hajime

2016-09-01

In the brain, glycogen metabolism has been implied in synaptic plasticity and learning, yet the distribution of this molecule has not been fully described. We investigated cerebral glycogen of the mouse by immunohistochemistry (IHC) using two monoclonal antibodies that have different affinities depending on the glycogen size. The use of focused microwave irradiation yielded well-defined glycogen immunoreactive signals compared with the conventional periodic acid-Schiff method. The IHC signals displayed a punctate distribution localized predominantly in astrocytic processes. Glycogen immunoreactivity (IR) was high in the hippocampus, striatum, cortex, and cerebellar molecular layer, whereas it was low in the white matter and most of the subcortical structures. Additionally, glycogen distribution in the hippocampal CA3-CA1 and striatum had a 'patchy' appearance with glycogen-rich and glycogen-poor astrocytes appearing in alternation. The glycogen patches were more evident with large-molecule glycogen in young adult mice but they were hardly observable in aged mice (1-2 years old). Our results reveal brain region-dependent glycogen accumulation and possibly metabolic heterogeneity of astrocytes. GLIA 2016;64:1532-1545. © 2016 The Authors. Glia Published by Wiley Periodicals, Inc.

Perceptually controlled doping for audio source separation

NASA Astrophysics Data System (ADS)

Mahé, Gaël; Nadalin, Everton Z.; Suyama, Ricardo; Romano, João MT

2014-12-01

The separation of an underdetermined audio mixture can be performed through sparse component analysis (SCA) that relies however on the strong hypothesis that source signals are sparse in some domain. To overcome this difficulty in the case where the original sources are available before the mixing process, the informed source separation (ISS) embeds in the mixture a watermark, which information can help a further separation. Though powerful, this technique is generally specific to a particular mixing setup and may be compromised by an additional bitrate compression stage. Thus, instead of watermarking, we propose a `doping' method that makes the time-frequency representation of each source more sparse, while preserving its audio quality. This method is based on an iterative decrease of the distance between the distribution of the signal and a target sparse distribution, under a perceptual constraint. We aim to show that the proposed approach is robust to audio coding and that the use of the sparsified signals improves the source separation, in comparison with the original sources. In this work, the analysis is made only in instantaneous mixtures and focused on voice sources.

Axin localizes to mitotic spindles and centrosomes in mitotic cells

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

Kim, Shi-Mun; Choi, Eun-Jin; Song, Ki-Joon

2009-04-01

Wnt signaling plays critical roles in cell proliferation and carcinogenesis. In addition, numerous recent studies have shown that various Wnt signaling components are involved in mitosis and chromosomal instability. However, the role of Axin, a negative regulator of Wnt signaling, in mitosis has remained unclear. Using monoclonal antibodies against Axin, we found that Axin localizes to the centrosome and along mitotic spindles. This localization was suppressed by siRNA specific for Aurora A kinase and by Aurora kinase inhibitor. Interestingly, Axin over-expression altered the subcellular distribution of Plk1 and of phosphorylated glycogen synthase kinase (GSK3{beta}) without producing any notable changes inmore » cellular phenotype. In the presence of Aurora kinase inhibitor, Axin over-expression induced the formation of cleavage furrow-like structures and of prominent astral microtubules lacking midbody formation in a subset of cells. Our results suggest that Axin modulates distribution of Axin-associated proteins such as Plk1 and GSK3{beta} in an expression level-dependent manner and these interactions affect the mitotic process, including cytokinesis under certain conditions, such as in the presence of Aurora kinase inhibitor.« less

A neuronal reward inequity signal in primate striatum

PubMed Central

van Coeverden, Charlotte R.; Schultz, Wolfram

2015-01-01

Primates are social animals, and their survival depends on social interactions with others. Especially important for social interactions and welfare is the observation of rewards obtained by other individuals and the comparison with own reward. The fundamental social decision variable for the comparison process is reward inequity, defined by an asymmetric reward distribution among individuals. An important brain structure for coding reward inequity may be the striatum, a component of the basal ganglia involved in goal-directed behavior. Two rhesus monkeys were seated opposite each other and contacted a touch-sensitive table placed between them to obtain specific magnitudes of reward that were equally or unequally distributed among them. Response times in one of the animals demonstrated differential behavioral sensitivity to reward inequity. A group of neurons in the striatum showed distinct signals reflecting disadvantageous and advantageous reward inequity. These neuronal signals occurred irrespective of, or in conjunction with, own reward coding. These data demonstrate that striatal neurons of macaque monkeys sense the differences between other's and own reward. The neuronal activities are likely to contribute crucial reward information to neuronal mechanisms involved in social interactions. PMID:26378202

Spatial Signal Characteristics of Shallow Paraboloidal Shell Structronic Systems

NASA Astrophysics Data System (ADS)

Yue, H. H.; Deng, Z. Q.; Tzou, H. S.

Based on the smart material and structronics technology, distributed sensor and control of shell structures have been rapidly developed for the last twenty years. This emerging technology has been utilized in aerospace, telecommunication, micro-electromechanical systems and other engineering applications. However, distributed monitoring technique and its resulting global spatially distributed sensing signals of thin flexible membrane shells are not clearly understood. In this paper, modeling of free thin paraboloidal shell with spatially distributed sensor, micro-sensing signal characteristics, and location of distributed piezoelectric sensor patches are investigated based on a new set of assumed mode shape functions. Parametric analysis indicates that the signal generation depends on modal membrane strains in the meridional and circumferential directions in which the latter is more significant than the former, when all bending strains vanish in membrane shells. This study provides a modeling and analysis technique for distributed sensors laminated on lightweight paraboloidal flexible structures and identifies critical components and regions that generate significant signals.

Ventromedial prefrontal cortex supports affective future simulation by integrating distributed knowledge

PubMed Central

Benoit, Roland G.; Szpunar, Karl K.; Schacter, Daniel L.

2014-01-01

Although the future often seems intangible, we can make it more concrete by imagining prospective events. Here, using functional MRI, we demonstrate a mechanism by which the ventromedial prefrontal cortex supports such episodic simulations, and thereby contributes to affective foresight: This region supports processes that (i) integrate knowledge related to the elements that constitute an episode and (ii) represent the episode’s emergent affective quality. The ventromedial prefrontal cortex achieves such integration via interactions with distributed cortical regions that process the individual elements. Its activation then signals the affective quality of the ensuing episode, which goes beyond the combined affective quality of its constituting elements. The integrative process further augments long-term retention of the episode, making it available at later time points. This mechanism thus renders the future tangible, providing a basis for farsighted behavior. PMID:25368170

Ventromedial prefrontal cortex supports affective future simulation by integrating distributed knowledge.

PubMed

Benoit, Roland G; Szpunar, Karl K; Schacter, Daniel L

2014-11-18

Although the future often seems intangible, we can make it more concrete by imagining prospective events. Here, using functional MRI, we demonstrate a mechanism by which the ventromedial prefrontal cortex supports such episodic simulations, and thereby contributes to affective foresight: This region supports processes that (i) integrate knowledge related to the elements that constitute an episode and (ii) represent the episode's emergent affective quality. The ventromedial prefrontal cortex achieves such integration via interactions with distributed cortical regions that process the individual elements. Its activation then signals the affective quality of the ensuing episode, which goes beyond the combined affective quality of its constituting elements. The integrative process further augments long-term retention of the episode, making it available at later time points. This mechanism thus renders the future tangible, providing a basis for farsighted behavior.

Dynamic association with donor cell filopodia and lipid-modification are essential features of Wnt8a during patterning of the zebrafish neuroectoderm.

PubMed

Luz, Marta; Spannl-Müller, Stephanie; Özhan, Günes; Kagermeier-Schenk, Birgit; Rhinn, Muriel; Weidinger, Gilbert; Brand, Michael

2014-01-01

Wnt proteins are conserved signaling molecules that regulate pattern formation during animal development. Many Wnt proteins are post-translationally modified by addition of lipid adducts. Wnt8a provides a crucial signal for patterning the anteroposterior axis of the developing neural plate in vertebrates. However, it is not clear how this protein propagates from its source, the blastoderm margin, to the target cells in the prospective neural plate, and how lipid-modifications might influence Wnt8a propagation and activity. We have dynamically imaged biologically active, fluorescently tagged Wnt8a in living zebrafish embryos. We find that Wnt8a localizes to membrane-associated, punctate structures in live tissue. In Wnt8a expressing cells, these puncta are found on filopodial cellular processes, from where the protein can be released. In addition, Wnt8a is found colocalized with Frizzled receptor-containing clusters on signal receiving cells. Combining in vitro and in vivo assays, we compare the roles of conserved Wnt8a residues in cell and non-cell-autonomous signaling activity and secretion. Non-signaling Wnt8 variants show these residues can regulate Wnt8a distribution in producing cell membranes and filopodia as well as in the receiving tissue. Together, our results show that Wnt8a forms dynamic clusters found on filopodial donor cell and on signal receiving cell membranes. Moreover, they demonstrate a differential requirement of conserved residues in Wnt8a protein for distribution in producing cells and receiving tissue and signaling activity during neuroectoderm patterning.

Dynamic Association with Donor Cell Filopodia and Lipid-Modification Are Essential Features of Wnt8a during Patterning of the Zebrafish Neuroectoderm

PubMed Central

Luz, Marta; Spannl-Müller, Stephanie; Özhan, Günes; Kagermeier-Schenk, Birgit; Rhinn, Muriel; Weidinger, Gilbert; Brand, Michael

2014-01-01

Background Wnt proteins are conserved signaling molecules that regulate pattern formation during animal development. Many Wnt proteins are post-translationally modified by addition of lipid adducts. Wnt8a provides a crucial signal for patterning the anteroposterior axis of the developing neural plate in vertebrates. However, it is not clear how this protein propagates from its source, the blastoderm margin, to the target cells in the prospective neural plate, and how lipid-modifications might influence Wnt8a propagation and activity. Results We have dynamically imaged biologically active, fluorescently tagged Wnt8a in living zebrafish embryos. We find that Wnt8a localizes to membrane-associated, punctate structures in live tissue. In Wnt8a expressing cells, these puncta are found on filopodial cellular processes, from where the protein can be released. In addition, Wnt8a is found colocalized with Frizzled receptor-containing clusters on signal receiving cells. Combining in vitro and in vivo assays, we compare the roles of conserved Wnt8a residues in cell and non-cell-autonomous signaling activity and secretion. Non-signaling Wnt8 variants show these residues can regulate Wnt8a distribution in producing cell membranes and filopodia as well as in the receiving tissue. Conclusions Together, our results show that Wnt8a forms dynamic clusters found on filopodial donor cell and on signal receiving cell membranes. Moreover, they demonstrate a differential requirement of conserved residues in Wnt8a protein for distribution in producing cells and receiving tissue and signaling activity during neuroectoderm patterning. PMID:24427298

SNR enhancement for downhole microseismic data based on scale classification shearlet transform

NASA Astrophysics Data System (ADS)

Li, Juan; Ji, Shuo; Li, Yue; Qian, Zhihong; Lu, Weili

2018-06-01

Shearlet transform (ST) can be effective in 2D signal processing, due to its parabolic scaling, high directional sensitivity, and optimal sparsity. ST combined with thresholding has been successfully applied to suppress random noise. However, because of the low magnitude and high frequency of a downhole microseismic signal, the coefficient values of valid signals and noise are similar in the shearlet domain. As a result, it is difficult to use for denoising. In this paper, we present a scale classification ST to solve this problem. The ST is used to decompose noisy microseismic data into serval scales. By analyzing the spectrum and energy distribution of the shearlet coefficients of microseismic data, we divide the scales into two types: low-frequency scales which contain less useful signal and high-frequency scales which contain more useful signal. After classification, we use two different methods to deal with the coefficients on different scales. For the low-frequency scales, the noise is attenuated using a thresholding method. As for the high-frequency scales, we propose to use a generalized Gauss distribution model based a non-local means filter, which takes advantage of the temporal and spatial similarity of microseismic data. The experimental results on both synthetic records and field data illustrate that our proposed method preserves the useful components and attenuates the noise well.

INTRACELLULAR CHOLESTEROL HOMEOSTASIS AND AMYLOID PRECURSOR PROTEIN PROCESSING

PubMed Central

Burns, Mark; Rebeck, G. William

2010-01-01

Many preclinical and clinical studies have implied a role for cholesterol in the pathogenesis of Alzheimer's disease (AD). In this review we will discuss the movement of intracellular cholesterol and how normal distribution, transport, and export of cholesterol is vital for regulation of the AD related protein, Aβ. We focus on cholesterol distribution in the plasma membrane, transport through the endosomal/lysosomal system, control of cholesterol intracellular signaling at the endoplasmic reticulum and Golgi, the HMG-CoA reductase pathway and finally export of cholesterol from the cell. PMID:20304094

Studies of Beam Expansion and Distributed Bragg Reflector Lasers for Fiber Optics and Optical Signal Processing.

DTIC Science & Technology

1981-03-03

described theory and experiments on the DBR laser and on the use of the Distributed Bragg Deflector ( DBD ) to act as a grating bean expander. The DBD is a...and telescope. 9 .\\pplications requiring more power can use the DBD as a power combiner for several laser stripes, as shown in Fig. 3. In design...Bragg deflector ( DBD ). This device consists of a corrugated waveguide, whose grating is slanted at an angle 6 with respect to the incident beam. The

Accurate determination of Brillouin frequency based on cross recurrence plot analysis in Brillouin distributed fiber sensor

NASA Astrophysics Data System (ADS)

Haneef, Shahna M.; Srijith, K.; Venkitesh, D.; Srinivasan, B.

2017-04-01

We propose and demonstrate the use of cross recurrence plot analysis (CRPA) to accurately determine the Brillouin shift due to strain and temperature in a Brillouin distributed fiber sensor. This signal processing technique, which is implemented in Brillouin sensors for the first time relies on apriori data i.e, the lineshape of the Brillouin gain spectrum and its similarity with the spectral features measured at different locations along the fiber. Analytical and experimental investigation of the proposed scheme is presented in this paper.

High spatial resolution distributed optical fiber dynamic strain sensor with enhanced frequency and strain resolution.

PubMed

Masoudi, Ali; Newson, Trevor P

2017-01-15

A distributed optical fiber dynamic strain sensor with high spatial and frequency resolution is demonstrated. The sensor, which uses the ϕ-OTDR interrogation technique, exhibited a higher sensitivity thanks to an improved optical arrangement and a new signal processing procedure. The proposed sensing system is capable of fully quantifying multiple dynamic perturbations along a 5 km long sensing fiber with a frequency and spatial resolution of 5 Hz and 50 cm, respectively. The strain resolution of the sensor was measured to be 40 nε.

Fiber optic sensors; Proceedings of the Meeting, Cannes, France, November 26, 27, 1985

NASA Technical Reports Server (NTRS)

Arditty, Herve J. (Editor); Jeunhomme, Luc B. (Editor)

1986-01-01

The conference presents papers on distributed sensors and sensor networks, signal processing and detection techniques, temperature measurements, chemical sensors, and the measurement of pressure, strain, and displacements. Particular attention is given to optical fiber distributed sensors and sensor networks, tactile sensing in robotics using an optical network and Z-plane techniques, and a spontaneous Raman temperature sensor. Other topics include coherence in optical fiber gyroscopes, a high bandwidth two-phase flow void fraction fiber optic sensor, and a fiber-optic dark-field microbend sensor.

Mathematical representation of joint time-chroma distributions

NASA Astrophysics Data System (ADS)

Wakefield, Gregory H.

1999-11-01

Originally coined by the sensory psychologist Roger Shepard in the 1960s, chroma transforms frequency into octave equivalence classes. By extending the concept of chroma to chroma strength and how it varies over time, we have demonstrated the utility of chroma in simplifying the processing and representation of signals dominated by harmonically-related narrowband components. These investigations have utilized an ad hoc procedure for calculating the chromagram from a given time-frequency distribution. The present paper is intended to put this ad hoc procedure on more sound mathematical ground.

Simulated laser fluorosensor signals from subsurface chlorophyll distributions

NASA Technical Reports Server (NTRS)

Venable, D. D.; Khatun, S.; Punjabi, A.; Poole, L.

1986-01-01

A semianalytic Monte Carlo model has been used to simulate laser fluorosensor signals returned from subsurface distributions of chlorophyll. This study assumes the only constituent of the ocean medium is the common coastal zone dinoflagellate Prorocentrum minimum. The concentration is represented by Gaussian distributions in which the location of the distribution maximum and the standard deviation are variable. Most of the qualitative features observed in the fluorescence signal for total chlorophyll concentrations up to 1.0 microg/liter can be accounted for with a simple analytic solution assuming a rectangular chlorophyll distribution function.

Robust Modulo Remaindering and Applications in Radar and Sensor Signal Processing

DTIC Science & Technology

2015-08-27

Chinese Remainder Theorem in FDD Systems, Science China -- Information Sciences, vol.55, no.7, pp. 1605 -1616, July 2012. 3) Y. Liu, X.-G. Xia, and H. L...Sciences, vol.55, no.7, pp. 1605 -1616, July 2012. 3) Y. Liu, X.-G. Xia, and H. L. Zhang, Distributed Space-Time Coding for Full-DuplexAsynchronous

Multi-filter spectrophotometry of quasar environments

NASA Technical Reports Server (NTRS)

Craven, Sally E.; Hickson, Paul; Yee, Howard K. C.

1993-01-01

A many-filter photometric technique for determining redshifts and morphological types, by fitting spectral templates to spectral energy distributions, has good potential for application in surveys. Despite success in studies performed on simulated data, the results have not been fully reliable when applied to real, low signal-to-noise data. We are investigating techniques to improve the fitting process.

Method and system for determining depth distribution of radiation-emitting material located in a source medium and radiation detector system for use therein

DOEpatents

Benke, Roland R.; Kearfott, Kimberlee J.; McGregor, Douglas S.

2003-03-04

A method, system and a radiation detector system for use therein are provided for determining the depth distribution of radiation-emitting material distributed in a source medium, such as a contaminated field, without the need to take samples, such as extensive soil samples, to determine the depth distribution. The system includes a portable detector assembly with an x-ray or gamma-ray detector having a detector axis for detecting the emitted radiation. The radiation may be naturally-emitted by the material, such as gamma-ray-emitting radionuclides, or emitted when the material is struck by other radiation. The assembly also includes a hollow collimator in which the detector is positioned. The collimator causes the emitted radiation to bend toward the detector as rays parallel to the detector axis of the detector. The collimator may be a hollow cylinder positioned so that its central axis is perpendicular to the upper surface of the large area source when positioned thereon. The collimator allows the detector to angularly sample the emitted radiation over many ranges of polar angles. This is done by forming the collimator as a single adjustable collimator or a set of collimator pieces having various possible configurations when connected together. In any one configuration, the collimator allows the detector to detect only the radiation emitted from a selected range of polar angles measured from the detector axis. Adjustment of the collimator or the detector therein enables the detector to detect radiation emitted from a different range of polar angles. The system further includes a signal processor for processing the signals from the detector wherein signals obtained from different ranges of polar angles are processed together to obtain a reconstruction of the radiation-emitting material as a function of depth, assuming, but not limited to, a spatially-uniform depth distribution of the material within each layer. The detector system includes detectors having different properties (sensitivity, energy resolution) which are combined so that excellent spectral information may be obtained along with good determinations of the radiation field as a function of position.

The invariant statistical rule of aerosol scattering pulse signal modulated by random noise

NASA Astrophysics Data System (ADS)

Yan, Zhen-gang; Bian, Bao-Min; Yang, Juan; Peng, Gang; Li, Zhen-hua

2010-11-01

A model of the random background noise acting on particle signals is established to study the impact of the background noise of the photoelectric sensor in the laser airborne particle counter on the statistical character of the aerosol scattering pulse signals. The results show that the noises broaden the statistical distribution of the particle's measurement. Further numerical research shows that the output of the signal amplitude still has the same distribution when the airborne particle with the lognormal distribution was modulated by random noise which has lognormal distribution. Namely it follows the statistics law of invariance. Based on this model, the background noise of photoelectric sensor and the counting distributions of random signal for aerosol's scattering pulse are obtained and analyzed by using a high-speed data acquisition card PCI-9812. It is found that the experiment results and simulation results are well consistent.

Characteristics of traffic flow at a non-signalized intersection in the framework of game theory

NASA Astrophysics Data System (ADS)

Fan, Hongqiang; Jia, Bin; Tian, Junfang; Yun, Lifen

2014-12-01

At a non-signalized intersection, some vehicles violate the traffic rules to pass the intersection as soon as possible. These behaviors may cause many traffic conflicts even traffic accidents. In this paper, a simulation model is proposed to research the effects of these behaviors at a non-signalized intersection. Vehicle’s movement is simulated by the cellular automaton (CA) model. The game theory is introduced for simulating the intersection dynamics. Two types of driver participate the game process: cooperator (C) and defector (D). The cooperator obey the traffic rules, but the defector does not. A transition process may occur when the cooperator is waiting before the intersection. The critical value of waiting time follows the Weibull distribution. One transition regime is found in the phase diagram. The simulation results illustrate the applicability of the proposed model and reveal a number of interesting insights into the intersection management, including that the existence of defectors is benefit for the capacity of intersection, but also reduce the safety of intersection.

Tactile objects based on an amplitude disturbed diffraction pattern method

NASA Astrophysics Data System (ADS)

Liu, Yuan; Nikolovski, Jean-Pierre; Mechbal, Nazih; Hafez, Moustapha; Vergé, Michel

2009-12-01

Tactile sensing is becoming widely used in human-computer interfaces. Recent advances in acoustic approaches demonstrated the possibilities to transform ordinary solid objects into interactive interfaces. This letter proposes a static finger contact localization process using an amplitude disturbed diffraction pattern method. The localization method is based on the following physical phenomenon: a finger contact modifies the energy distribution of acoustic wave in a solid; these variations depend on the wave frequency and the contact position. The presented method first consists of exciting the object with an acoustic signal with plural frequency components. In a second step, a measured acoustic signal is compared with prerecorded values to deduce the contact position. This position is then used for human-machine interaction (e.g., finger tracking on computer screen). The selection of excitation signals is discussed and a frequency choice criterion based on contrast value is proposed. Tests on a sandwich plate (liquid crystal display screen) prove the simplicity and easiness to apply the process in various solids.

Regulation of branching dynamics by axon-intrinsic asymmetries in Tyrosine Kinase Receptor signaling

PubMed Central

Zschätzsch, Marlen; Oliva, Carlos; Langen, Marion; De Geest, Natalie; Özel, Mehmet Neset; Williamson, W Ryan; Lemon, William C; Soldano, Alessia; Munck, Sebastian; Hiesinger, P Robin; Sanchez-Soriano, Natalia; Hassan, Bassem A

2014-01-01

Axonal branching allows a neuron to connect to several targets, increasing neuronal circuit complexity. While axonal branching is well described, the mechanisms that control it remain largely unknown. We find that in the Drosophila CNS branches develop through a process of excessive growth followed by pruning. In vivo high-resolution live imaging of developing brains as well as loss and gain of function experiments show that activation of Epidermal Growth Factor Receptor (EGFR) is necessary for branch dynamics and the final branching pattern. Live imaging also reveals that intrinsic asymmetry in EGFR localization regulates the balance between dynamic and static filopodia. Elimination of signaling asymmetry by either loss or gain of EGFR function results in reduced dynamics leading to excessive branch formation. In summary, we propose that the dynamic process of axon branch development is mediated by differential local distribution of signaling receptors. DOI: http://dx.doi.org/10.7554/eLife.01699.001 PMID:24755286

Concepts for on board satellite image registration. Volume 4: Impact of data set selection on satellite on board signal processing

NASA Technical Reports Server (NTRS)

Ruedger, W. H.; Aanstoos, J. V.; Snyder, W. E.

1982-01-01

The NASA NEEDS program goals present a requirement for on-board signal processing to achieve user-compatible, information-adaptive data acquisition. This volume addresses the impact of data set selection on data formatting required for efficient telemetering of the acquired satellite sensor data. More specifically, the FILE algorithm developed by Martin-Marietta provides a means for the determination of those pixels from the data stream effects an improvement in the achievable system throughput. It will be seen that based on the lack of statistical stationarity in cloud cover, spatial distribution periods exist where data acquisition rates exceed the throughput capability. The study therefore addresses various approaches to data compression and truncation as applicable to this sensor mission.

Objective fitting of hemoglobin dynamics in traumatic bruises based on temperature depth profiling

NASA Astrophysics Data System (ADS)

Vidovič, Luka; Milanič, Matija; Majaron, Boris

2014-02-01

Pulsed photothermal radiometry (PPTR) allows noninvasive measurement of laser-induced temperature depth profiles. The obtained profiles provide information on depth distribution of absorbing chromophores, such as melanin and hemoglobin. We apply this technique to objectively characterize mass diffusion and decomposition rate of extravasated hemoglobin during the bruise healing process. In present study, we introduce objective fitting of PPTR data obtained over the course of the bruise healing process. By applying Monte Carlo simulation of laser energy deposition and simulation of the corresponding PPTR signal, quantitative analysis of underlying bruise healing processes is possible. Introduction of objective fitting enables an objective comparison between the simulated and experimental PPTR signals. In this manner, we avoid reconstruction of laser-induced depth profiles and thus inherent loss of information in the process. This approach enables us to determine the value of hemoglobin mass diffusivity, which is controversial in existing literature. Such information will be a valuable addition to existing bruise age determination techniques.

Time-Frequency Distribution Analyses of Ku-Band Radar Doppler Echo Signals

NASA Astrophysics Data System (ADS)

Bujaković, Dimitrije; Andrić, Milenko; Bondžulić, Boban; Mitrović, Srđan; Simić, Slobodan

2015-03-01

Real radar echo signals of a pedestrian, vehicle and group of helicopters are analyzed in order to maximize signal energy around central Doppler frequency in time-frequency plane. An optimization, preserving this concentration, is suggested based on three well-known concentration measures. Various window functions and time-frequency distributions were optimization inputs. Conducted experiments on an analytic and three real signals have shown that energy concentration significantly depends on used time-frequency distribution and window function, for all three used criteria.

Atmospheric Quantum Channels with Weak and Strong Turbulence.

PubMed

Vasylyev, D; Semenov, A A; Vogel, W

2016-08-26

The free-space transfer of high-fidelity optical signals between remote locations has many applications, including both classical and quantum communication, precision navigation, clock synchronization, etc. The physical processes that contribute to signal fading and loss need to be carefully analyzed in the theory of light propagation through the atmospheric turbulence. Here we derive the probability distribution for the atmospheric transmittance including beam wandering, beam shape deformation, and beam-broadening effects. Our model, referred to as the elliptic beam approximation, applies to weak, weak-to-moderate, and strong turbulence and hence to the most important regimes in atmospheric communication scenarios.

The SKA1 LOW telescope: system architecture and design performance

NASA Astrophysics Data System (ADS)

Waterson, Mark F.; Labate, Maria Grazia; Schnetler, Hermine; Wagg, Jeff; Turner, Wallace; Dewdney, Peter

2016-07-01

The SKA1-LOW radio telescope will be a low-frequency (50-350 MHz) aperture array located in Western Australia. Its scientific objectives will prioritize studies of the Epoch of Reionization and pulsar physics. Development of the telescope has been allocated to consortia responsible for the aperture array front end, timing distribution, signal and data transport, correlation and beamforming signal processors, infrastructure, monitor and control systems, and science data processing. This paper will describe the system architectural design and key performance parameters of the telescope and summarize the high-level sub-system designs of the consortia.

Application of spectral decomposition of ²²²Rn activity concentration signal series measured in Niedźwiedzia Cave to identification of mechanisms responsible for different time-period variations.

PubMed

Przylibski, Tadeusz Andrzej; Wyłomańska, Agnieszka; Zimroz, Radosław; Fijałkowska-Lichwa, Lidia

2015-10-01

The authors present an application of spectral decomposition of (222)Rn activity concentration signal series as a mathematical tool used for distinguishing processes determining temporal changes of radon concentration in cave air. The authors demonstrate that decomposition of monitored signal such as (222)Rn activity concentration in cave air facilitates characterizing the processes affecting changes in the measured concentration of this gas. Thanks to this, one can better correlate and characterize the influence of various processes on radon behaviour in cave air. Distinguishing and characterising these processes enables the understanding of radon behaviour in cave environment and it may also enable and facilitate using radon as a precursor of geodynamic phenomena in the lithosphere. Thanks to the conducted analyses, the authors confirmed the unquestionable influence of convective air exchange between the cave and the atmosphere on seasonal and short-term (diurnal) changes in (222)Rn activity concentration in cave air. Thanks to the applied methodology of signal analysis and decomposition, the authors also identified a third process affecting (222)Rn activity concentration changes in cave air. This is a deterministic process causing changes in radon concentration, with a distribution different from the Gaussian one. The authors consider these changes to be the effect of turbulent air movements caused by the movement of visitors in caves. This movement is heterogeneous in terms of the number of visitors per group and the number of groups visiting a cave per day and per year. Such a process perfectly elucidates the observed character of the registered changes in (222)Rn activity concentration in one of the decomposed components of the analysed signal. The obtained results encourage further research into precise relationships between the registered (222)Rn activity concentration changes and factors causing them, as well as into using radon as a precursor of geodynamic phenomena in the lithosphere. Copyright © 2015 Elsevier Ltd. All rights reserved.

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.

The impact of global signal regression on resting state correlations: Are anti-correlated networks introduced?

PubMed Central

Murphy, Kevin; Birn, Rasmus M.; Handwerker, Daniel A.; Jones, Tyler B.; Bandettini, Peter A.

2009-01-01

Low-frequency fluctuations in fMRI signal have been used to map several consistent resting state networks in the brain. Using the posterior cingulate cortex as a seed region, functional connectivity analyses have found not only positive correlations in the default mode network but negative correlations in another resting state network related to attentional processes. The interpretation is that the human brain is intrinsically organized into dynamic, anti-correlated functional networks. Global variations of the BOLD signal are often considered nuisance effects and are commonly removed using a general linear model (GLM) technique. This global signal regression method has been shown to introduce negative activation measures in standard fMRI analyses. The topic of this paper is whether such a correction technique could be the cause of anti-correlated resting state networks in functional connectivity analyses. Here we show that, after global signal regression, correlation values to a seed voxel must sum to a negative value. Simulations also show that small phase differences between regions can lead to spurious negative correlation values. A combination breath holding and visual task demonstrates that the relative phase of global and local signals can affect connectivity measures and that, experimentally, global signal regression leads to bell-shaped correlation value distributions, centred on zero. Finally, analyses of negatively correlated networks in resting state data show that global signal regression is most likely the cause of anti-correlations. These results call into question the interpretation of negatively correlated regions in the brain when using global signal regression as an initial processing step. PMID:18976716

The impact of global signal regression on resting state correlations: are anti-correlated networks introduced?

PubMed

Murphy, Kevin; Birn, Rasmus M; Handwerker, Daniel A; Jones, Tyler B; Bandettini, Peter A

2009-02-01

Low-frequency fluctuations in fMRI signal have been used to map several consistent resting state networks in the brain. Using the posterior cingulate cortex as a seed region, functional connectivity analyses have found not only positive correlations in the default mode network but negative correlations in another resting state network related to attentional processes. The interpretation is that the human brain is intrinsically organized into dynamic, anti-correlated functional networks. Global variations of the BOLD signal are often considered nuisance effects and are commonly removed using a general linear model (GLM) technique. This global signal regression method has been shown to introduce negative activation measures in standard fMRI analyses. The topic of this paper is whether such a correction technique could be the cause of anti-correlated resting state networks in functional connectivity analyses. Here we show that, after global signal regression, correlation values to a seed voxel must sum to a negative value. Simulations also show that small phase differences between regions can lead to spurious negative correlation values. A combination breath holding and visual task demonstrates that the relative phase of global and local signals can affect connectivity measures and that, experimentally, global signal regression leads to bell-shaped correlation value distributions, centred on zero. Finally, analyses of negatively correlated networks in resting state data show that global signal regression is most likely the cause of anti-correlations. These results call into question the interpretation of negatively correlated regions in the brain when using global signal regression as an initial processing step.

Mixed mechanisms of multi-site phosphorylation

PubMed Central

Suwanmajo, Thapanar; Krishnan, J.

2015-01-01

Multi-site phosphorylation is ubiquitous in cell biology and has been widely studied experimentally and theoretically. The underlying chemical modification mechanisms are typically assumed to be distributive or processive. In this paper, we study the behaviour of mixed mechanisms that can arise either because phosphorylation and dephosphorylation involve different mechanisms or because phosphorylation and/or dephosphorylation can occur through a combination of mechanisms. We examine a hierarchy of models to assess chemical information processing through different mixed mechanisms, using simulations, bifurcation analysis and analytical work. We demonstrate how mixed mechanisms can show important and unintuitive differences from pure distributive and processive mechanisms, in some cases resulting in monostable behaviour with simple dose–response behaviour, while in other cases generating new behaviour-like oscillations. Our results also suggest patterns of information processing that are relevant as the number of modification sites increases. Overall, our work creates a framework to examine information processing arising from complexities of multi-site modification mechanisms and their impact on signal transduction. PMID:25972433

Comparison of Internal Energy Distributions of Ions Created by Electrospray Ionization and Laser Ablation-Liquid Vortex Capture-Electrospray Ionization

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

Cahill, John F.; Kertesz, Vilmos; Ovchinnikova, Olga S.

2015-06-27

Recently a number of techniques have combined laser ablation with liquid capture for mass spectrometry spot sampling and imaging applications. The newly developed non-contact liquid-vortex capture probe has been used to efficiently collect 355 nm UV laser ablated material in a continuous flow solvent stream in which the captured material dissolves and then undergoes electrospray ionization. This sampling and ionization approach has produced what appear to be classic electrospray ionization spectra; however, the softness of this sampling/ionization process versus simple electrospray ionization has not been definitely determined. A series of benzlypyridinium salts, known as thermometer ions, were used to comparemore » internal energy distributions between electrospray ionization and the UV laser ablation liquid-vortex capture probe electrospray combination. Measured internal energy distributions were identical between the two techniques, even with differences in laser fluence (0.7-3.1 J cm-2) and when using UV-absorbing or non-UV-absorbing sample substrates. This data indicates ions formed directly by UV laser ablation, if any, are likely an extremely small constituent of the total ion signal observed. Instead, neutral molecules, clusters or particulates ejected from the surface during laser ablation, subsequently captured and dissolved in the flowing solvent stream then electrosprayed are the predominant source of ion signal observed. The electrospray ionization process used controls the softness of the technique.« less

Efficient dynamic events discrimination technique for fiber distributed Brillouin sensors.

PubMed

Galindez, Carlos A; Madruga, Francisco J; Lopez-Higuera, Jose M

2011-09-26

A technique to detect real time variations of temperature or strain in Brillouin based distributed fiber sensors is proposed and is investigated in this paper. The technique is based on anomaly detection methods such as the RX-algorithm. Detection and isolation of dynamic events from the static ones are demonstrated by a proper processing of the Brillouin gain values obtained by using a standard BOTDA system. Results also suggest that better signal to noise ratio, dynamic range and spatial resolution can be obtained. For a pump pulse of 5 ns the spatial resolution is enhanced, (from 0.541 m obtained by direct gain measurement, to 0.418 m obtained with the technique here exposed) since the analysis is concentrated in the variation of the Brillouin gain and not only on the averaging of the signal along the time. © 2011 Optical Society of America

Approximations to camera sensor noise

NASA Astrophysics Data System (ADS)

Jin, Xiaodan; Hirakawa, Keigo

2013-02-01

Noise is present in all image sensor data. Poisson distribution is said to model the stochastic nature of the photon arrival process, while it is common to approximate readout/thermal noise by additive white Gaussian noise (AWGN). Other sources of signal-dependent noise such as Fano and quantization also contribute to the overall noise profile. Question remains, however, about how best to model the combined sensor noise. Though additive Gaussian noise with signal-dependent noise variance (SD-AWGN) and Poisson corruption are two widely used models to approximate the actual sensor noise distribution, the justification given to these types of models are based on limited evidence. The goal of this paper is to provide a more comprehensive characterization of random noise. We concluded by presenting concrete evidence that Poisson model is a better approximation to real camera model than SD-AWGN. We suggest further modification to Poisson that may improve the noise model.

MNE software for processing MEG and EEG data

PubMed Central

Gramfort, A.; Luessi, M.; Larson, E.; Engemann, D.; Strohmeier, D.; Brodbeck, C.; Parkkonen, L.; Hämäläinen, M.

2013-01-01

Magnetoencephalography and electroencephalography (M/EEG) measure the weak electromagnetic signals originating from neural currents in the brain. Using these signals to characterize and locate brain activity is a challenging task, as evidenced by several decades of methodological contributions. MNE, whose name stems from its capability to compute cortically-constrained minimum-norm current estimates from M/EEG data, is a software package that provides comprehensive analysis tools and workflows including preprocessing, source estimation, time–frequency analysis, statistical analysis, and several methods to estimate functional connectivity between distributed brain regions. The present paper gives detailed information about the MNE package and describes typical use cases while also warning about potential caveats in analysis. The MNE package is a collaborative effort of multiple institutes striving to implement and share best methods and to facilitate distribution of analysis pipelines to advance reproducibility of research. Full documentation is available at http://martinos.org/mne. PMID:24161808

A simple two-stage model predicts response time distributions.

PubMed

Carpenter, R H S; Reddi, B A J; Anderson, A J

2009-08-15

The neural mechanisms underlying reaction times have previously been modelled in two distinct ways. When stimuli are hard to detect, response time tends to follow a random-walk model that integrates noisy sensory signals. But studies investigating the influence of higher-level factors such as prior probability and response urgency typically use highly detectable targets, and response times then usually correspond to a linear rise-to-threshold mechanism. Here we show that a model incorporating both types of element in series - a detector integrating noisy afferent signals, followed by a linear rise-to-threshold performing decision - successfully predicts not only mean response times but, much more stringently, the observed distribution of these times and the rate of decision errors over a wide range of stimulus detectability. By reconciling what previously may have seemed to be conflicting theories, we are now closer to having a complete description of reaction time and the decision processes that underlie it.

Image motion environments: background noise for movement-based animal signals.

PubMed

Peters, Richard; Hemmi, Jan; Zeil, Jochen

2008-05-01

Understanding the evolution of animal signals has to include consideration of the structure of signal and noise, and the sensory mechanisms that detect the signals. Considerable progress has been made in understanding sounds and colour signals, however, the degree to which movement-based signals are constrained by the particular patterns of environmental image motion is poorly understood. Here we have quantified the image motion generated by wind-blown plants at 12 sites in the coastal habitat of the Australian lizard Amphibolurus muricatus. Sampling across different plant communities and meteorological conditions revealed distinct image motion environments. At all locations, image motion became more directional and apparent speed increased as wind speeds increased. The magnitude of these changes and the spatial distribution of image motion, however, varied between locations probably as a function of plant structure and the topographic location. In addition, we show that the background motion noise depends strongly on the particular depth-structure of the environment and argue that such micro-habitat differences suggest specific strategies to preserve signal efficacy. Movement-based signals and motion processing mechanisms, therefore, may reveal the same type of habitat specific structural variation that we see for signals from other modalities.

The Influence of Volcanic Processes on the Distribution of Seismic Velocity Changes at Piton de la Fournaise Volcano (La Reunion)

NASA Astrophysics Data System (ADS)

Sens-Schönfelder, Christoph; Pomponi, Eraldo

2014-05-01

The velocity of seismic waves propagating in the edifice of Piton de la Fournaise volcano (La Reunion) is known to change in response to volcanic eruptions. Here we present a detailed investigation of a the period from end of 2009 until end of 2011 that contains eruptions, non-eruptive intrusions and periods of relaxation and perform a detailed comparison of the associated velocity signals. We use data from by 21 seismograph stations of the IPGP/OVPF seismic network installed on Piton de la Fournaise volcano within the UnderVolc project. Seismic noise of vertical and horizontal components of all possible station pairs is cross-correlated in chunks of 24 hours to obtain daily approximations of Green's functions in order to monitor tiny changes in therein that are related to changes of the elastic properties in the volcano. Velocity changes are measured as apparent stretching of the coda. For some station pairs the apparent velocity changes exceed 1% and a decorrelation of waveforms is observed at the time of volcanic activity. This distorts monitoring results if changes are measured with respect to a global reference. To overcome this we present a method to estimate changes using multiple references that stabilizes the quality of estimated velocity changes. We observe abrupt changes that occur coincident with volcanic events as well as long term transient signals. Using a simple assumption about the spatial sensitivity of our measurements we can map the spatial distribution of velocity changes for selected periods. Comparing these signals with volcanic activity and GPS derived surface displacement we can identify patterns of the velocity changes that appear characteristic for the different types of volcanic activity. We can differentiate intrusive processes associated with inflation and increased seismic activity, periods of relaxation without seismicity and eruptions solely based on the velocity signal. This information can help to assess the processes acting in the volcano by offering an alternative observable to GPS, seismicity and tilt.

Quantum cryptographic system with reduced data loss

DOEpatents

Lo, H.K.; Chau, H.F.

1998-03-24

A secure method for distributing a random cryptographic key with reduced data loss is disclosed. Traditional quantum key distribution systems employ similar probabilities for the different communication modes and thus reject at least half of the transmitted data. The invention substantially reduces the amount of discarded data (those that are encoded and decoded in different communication modes e.g. using different operators) in quantum key distribution without compromising security by using significantly different probabilities for the different communication modes. Data is separated into various sets according to the actual operators used in the encoding and decoding process and the error rate for each set is determined individually. The invention increases the key distribution rate of the BB84 key distribution scheme proposed by Bennett and Brassard in 1984. Using the invention, the key distribution rate increases with the number of quantum signals transmitted and can be doubled asymptotically. 23 figs.

Quantum cryptographic system with reduced data loss

DOEpatents

Lo, Hoi-Kwong; Chau, Hoi Fung

1998-01-01

A secure method for distributing a random cryptographic key with reduced data loss. Traditional quantum key distribution systems employ similar probabilities for the different communication modes and thus reject at least half of the transmitted data. The invention substantially reduces the amount of discarded data (those that are encoded and decoded in different communication modes e.g. using different operators) in quantum key distribution without compromising security by using significantly different probabilities for the different communication modes. Data is separated into various sets according to the actual operators used in the encoding and decoding process and the error rate for each set is determined individually. The invention increases the key distribution rate of the BB84 key distribution scheme proposed by Bennett and Brassard in 1984. Using the invention, the key distribution rate increases with the number of quantum signals transmitted and can be doubled asymptotically.

Characterizing pulmonary blood flow distribution measured using arterial spin labeling.

PubMed

Henderson, A Cortney; Prisk, G Kim; Levin, David L; Hopkins, Susan R; Buxton, Richard B

2009-12-01

The arterial spin labeling (ASL) method provides images in which, ideally, the signal intensity of each image voxel is proportional to the local perfusion. For studies of pulmonary perfusion, the relative dispersion (RD, standard deviation/mean) of the ASL signal across a lung section is used as a reliable measure of flow heterogeneity. However, the RD of the ASL signals within the lung may systematically differ from the true RD of perfusion because the ASL image also includes signals from larger vessels, which can reflect the blood volume rather than blood flow if the vessels are filled with tagged blood during the imaging time. Theoretical studies suggest that the pulmonary vasculature exhibits a lognormal distribution for blood flow and thus an appropriate measure of heterogeneity is the geometric standard deviation (GSD). To test whether the ASL signal exhibits a lognormal distribution for pulmonary blood flow, determine whether larger vessels play an important role in the distribution, and extract physiologically relevant measures of heterogeneity from the ASL signal, we quantified the ASL signal before and after an intervention (head-down tilt) in six subjects. The distribution of ASL signal was better characterized by a lognormal distribution than a normal distribution, reducing the mean squared error by 72% (p < 0.005). Head-down tilt significantly reduced the lognormal scale parameter (p = 0.01) but not the shape parameter or GSD. The RD increased post-tilt and remained significantly elevated (by 17%, p < 0.05). Test case results and mathematical simulations suggest that RD is more sensitive than the GSD to ASL signal from tagged blood in larger vessels, a probable explanation of the change in RD without a statistically significant change in GSD. This suggests that the GSD is a useful measure of pulmonary blood flow heterogeneity with the advantage of being less affected by the ASL signal from tagged blood in larger vessels.

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

Nondestructive Integrity Evaluation of PC Pile Using Wigner-Ville Distribution Method

NASA Astrophysics Data System (ADS)

Ni, Sheng-Huoo; Lo, Kuo-Feng; Huang, Yan-Hong

Nondestructive evaluation (NDE) techniques have been used for years to provide a quality control of the construction for both drilled shafts and driven concrete piles. This trace is typically made up of transient pulses reflected from structural features of the pile or changes in its surrounding environment. It is often analyzed in conjunction with the spectral response, mobility curve, arrival time, etc. The Wigner-Ville Distribution is a new numerical analysis tool for signal process technique in the time-frequency domain and it can offer assistance and enhance signal characteristics for better resolution both easily and quickly. In this study, five single pre-cast concrete piles have been tested and evaluated by both sonic echo method and Wigner-Ville distribution (WVD). Furthermore, two difficult problems in nondestructive evaluation problems are discussed and solved: the first one is with a pile with slight defect, whose necking area percentage is less than 10%, and the other is a pile with multiple defects. The results show that WVD can not only recognize the characteristics easily, but also locate the defects more clearly than the traditional pile integrity testing method.

Study on time-frequency analysis method of very fast transient overvoltage

NASA Astrophysics Data System (ADS)

Li, Shuai; Liu, Shiming; Huang, Qiyan; Fu, Chuanshun

2018-04-01

The operation of the disconnector in the gas insulated substation (GIS) may produce very fast transient overvoltage (VFTO), which has the characteristics of short rise time, short duration, high amplitude and rich frequency components. VFTO can cause damage to GIS and secondary equipment, and the frequency components contained in the VFTO can cause resonance overvoltage inside the transformer, so it is necessary to study the spectral characteristics of the VFTO. From the perspective of signal processing, VFTO is a kind of non-stationary signal, the traditional Fourier transform is difficult to describe its frequency which changes with time, so it is necessary to use time-frequency analysis to analyze VFTO spectral characteristics. In this paper, we analyze the performance of short time Fourier transform (STFT), Wigner-Ville distribution (WVD), pseudo Wigner-Ville distribution (PWVD) and smooth pseudo Wigner-Ville distribution (SPWVD). The results show that SPWVD transform is the best. The time-frequency aggregation of SPWVD is higher than STFT, and it does not have cross-interference terms, which can meet the requirements of VFTO spectrum analysis.

Distributed Optical Fiber Sensors with Ultrafast Laser Enhanced Rayleigh Backscattering Profiles for Real-Time Monitoring of Solid Oxide Fuel Cell Operations.

PubMed

Yan, Aidong; Huang, Sheng; Li, Shuo; Chen, Rongzhang; Ohodnicki, Paul; Buric, Michael; Lee, Shiwoo; Li, Ming-Jun; Chen, Kevin P

2017-08-24

This paper reports a technique to enhance the magnitude and high-temperature stability of Rayleigh back-scattering signals in silica fibers for distributed sensing applications. With femtosecond laser radiation, more than 40-dB enhancement of Rayleigh backscattering signal was generated in silica fibers using 300-nJ laser pulses at 250 kHz repetition rate. The laser-induced Rayleigh scattering defects were found to be stable from the room temperature to 800 °C in hydrogen gas. The Rayleigh scatter at high temperatures was correlated to the formation and modification of nanogratings in the fiber core. Using optical fibers with enhanced Rayleigh backscattering profiles as distributed temperature sensors, we demonstrated real-time monitoring of solid oxide fuel cell (SOFC) operations with 5-mm spatial resolution at 800 °C. Information gathered by these fiber sensor tools can be used to verify simulation results or operated in a process-control system to improve the operational efficiency and longevity of SOFC-based energy generation systems.

Modeled and Observed Altitude Distributions of the Micrometeoroid Influx in Radar Detection

NASA Astrophysics Data System (ADS)

Swarnalingam, N.; Janches, D.; Plane, J. M. C.; Carrillo-Sánchez, J. D.; Sternovsky, Z.; Pokorny, P.; Nesvorny, D.

2017-12-01

The altitude distributions of the micrometeoroids are a representation of the radar response function of the incoming flux and thus can be utilized to calibrate radar measurements. These in turn, can be used to determine the rate of ablation and ionization of the meteoroids and ultimately the input flux. During the ablation process, electrons are created and subsequently these electrons produce backscatter signals when they encounter the transmitted signals from radar. In this work, we investigate the altitude distribution by exploring different sizes as well as the aspect sensitivity of the meteor head echoes. We apply an updated version of the Chemical Ablation Model (CABMOD), which includes results from laboratory simulation of meteor ablation for different metallic constituents. In particular, the updated version simulates the ablation of Na. It is observed in the updated version that electrons are produced to a wider altitude range with the peak production occurs at lower altitudes compared to the previous version. The results are compared to head echo meteor observations utilizing the Arecibo 430 MHz radar.

Distinguishing graded and ultrasensitive signalling cascade kinetics by the shape of morphogen gradients in Drosophila.

PubMed

MacNamara, Shev; Baker, Ruth E; Maini, Philip K

2011-09-21

Recently, signalling gradients in cascades of two-state reaction-diffusion systems were described as a model for understanding key biochemical mechanisms that underlie development and differentiation processes in the Drosophila embryo. Diffusion-trapping at the exterior of the cell membrane triggers the mitogen-activated protein kinase (MAPK) cascade to relay an appropriate signal from the membrane to the inner part of the cytosol, whereupon another diffusion-trapping mechanism involving the nucleus reads out this signal to trigger appropriate changes in gene expression. Proposed mathematical models exhibit equilibrium distributions consistent with experimental measurements of key spatial gradients in these processes. A significant property of the formulation is that the signal is assumed to be relayed from one system to the next in a linear fashion. However, the MAPK cascade often exhibits nonlinear dose-response properties and the final remark of Berezhkovskii et al. (2009) is that this assumption remains an important property to be tested experimentally, perhaps via a new quantitative assay across multiple genetic backgrounds. In anticipation of the need to be able to sensibly interpret data from such experiments, here we provide a complementary analysis that recovers existing formulae as a special case but is also capable of handling nonlinear functional forms. Predictions of linear and nonlinear signal relays and, in particular, graded and ultrasensitive MAPK kinetics, are compared. Copyright © 2011 Elsevier Ltd. All rights reserved.

State Recognition of Bone Drilling Based on Acoustic Emission in Pedicle Screw Operation.

PubMed

Guan, Fengqing; Sun, Yu; Qi, Xiaozhi; Hu, Ying; Yu, Gang; Zhang, Jianwei

2018-05-09

Pedicle drilling is an important step in pedicle screw fixation and the most significant challenge in this operation is how to determine a key point in the transition region between cancellous and inner cortical bone. The purpose of this paper is to find a method to achieve the recognition for the key point. After acquiring acoustic emission (AE) signals during the drilling process, this paper proposed a novel frequency distribution-based algorithm (FDB) to analyze the AE signals in the frequency domain after certain processes. Then we select a specific frequency domain of the signal for standard operations and choose a fitting function to fit the obtained sequence. Characters of the fitting function are extracted as outputs for identification of different bone layers. The results, which are obtained by detecting force signal and direct measurement, are given in the paper. Compared with the results above, the results obtained by AE signals are distinguishable for different bone layers and are more accurate and precise. The results of the algorithm are trained and identified by a neural network and the recognition rate reaches 84.2%. The proposed method is proved to be efficient and can be used for bone layer identification in pedicle screw fixation.

Analysis of Digital Communication Signals and Extraction of Parameters.

DTIC Science & Technology

1994-12-01

Fast Fourier Transform (FFT). The correlation methods utilize modified time-frequency distributions , where one of these is based on the Wigner - Ville ... Distribution ( WVD ). Gaussian white noise is added to the signal to simulate various signal-to-noise ratios (SNRs).

Signal and noise modeling in confocal laser scanning fluorescence microscopy.

PubMed

Herberich, Gerlind; Windoffer, Reinhard; Leube, Rudolf E; Aach, Til

2012-01-01

Fluorescence confocal laser scanning microscopy (CLSM) has revolutionized imaging of subcellular structures in biomedical research by enabling the acquisition of 3D time-series of fluorescently-tagged proteins in living cells, hence forming the basis for an automated quantification of their morphological and dynamic characteristics. Due to the inherently weak fluorescence, CLSM images exhibit a low SNR. We present a novel model for the transfer of signal and noise in CLSM that is both theoretically sound as well as corroborated by a rigorous analysis of the pixel intensity statistics via measurement of the 3D noise power spectra, signal-dependence and distribution. Our model provides a better fit to the data than previously proposed models. Further, it forms the basis for (i) the simulation of the CLSM imaging process indispensable for the quantitative evaluation of CLSM image analysis algorithms, (ii) the application of Poisson denoising algorithms and (iii) the reconstruction of the fluorescence signal.

Characterizing near-surface firn from the scattered signal component of glacier surface reflections detected in airborne radio-echo sounding measurements

NASA Astrophysics Data System (ADS)

Rutishauser, A.; Grima, C.; Sharp, M. J.; Blankenship, D. D.; Young, D. A.; Cawkwell, F.; Dowdeswell, J. A.

2016-12-01

With recent summer warming, surface melt on Canadian Arctic ice caps has intensified and extended to higher elevations in ice cap accumulation areas. Consequently, more meltwater percolates into the near-surface firn, and refreezes as ice layers where firn temperatures are below freezing. This process can increase firn densification rates, causing a lowering of the glacier surface height even in the absence of mass changes. Thus, knowledge of spatio-temporal variations in the near-surface firn stratigraphy is important for interpreting altimetrically-derived estimates of ice cap mass balance. We investigate the use of the scattering signal component of glacier surface reflections in airborne radio-echo sounding (RES) measurements to characterize the near-surface firn stratigraphy. The scattering signal distribution over Devon Ice Cap is compared to firn stratigraphy derived from ground-based radar data. We identify three distinct firn facies zones at different elevation ranges. The scattered signal component changes significantly between the different firn facies zones: low scattering correlates to laterally homogeneous firn containing thin, flat and continuous ice layers at elevations above 1800 m and below 1200 m, where firn consists mainly of ice. Higher scattering values are found from 1200-1800 m where the firn contains discrete, undulating ice layers. No correlation was found between the scattering component and surface roughness. Modelled scattering values for the measured roughness were significantly less than the observed values, and did not reproduce their observed spatial distribution. This indicates that the scattering component is determined mainly by the structure of near-surface firn. Our results suggest that the scattering component of surface reflections from airborne RES measurements has potential for characterizing heterogeneity in the spatial structure of firn that is affected by melting and refreezing processes.

Age slowing down in detection and visual discrimination under varying presentation times.

PubMed

Moret-Tatay, Carmen; Lemus-Zúñiga, Lenin-Guillermo; Tortosa, Diana Abad; Gamermann, Daniel; Vázquez-Martínez, Andrea; Navarro-Pardo, Esperanza; Conejero, J Alberto

2017-08-01

The reaction time has been described as a measure of perception, decision making, and other cognitive processes. The aim of this work is to examine age-related changes in executive functions in terms of demand load under varying presentation times. Two tasks were employed where a signal detection and a discrimination task were performed by young and older university students. Furthermore, a characterization of the response time distribution by an ex-Gaussian fit was carried out. The results indicated that the older participants were slower than the younger ones in signal detection and discrimination. Moreover, the differences between both processes for the older participants were higher, and they also showed a higher distribution average except for the lower and higher presentation time. The results suggest a general slowdown in both tasks for age under different presentation times, except for the cases where presentation times were lower and higher. Moreover, if these parameters are understood to be a reflection of executive functions, these findings are consistent with the common view that age-related cognitive deficits show a decline in this function. © 2017 Scandinavian Psychological Associations and John Wiley & Sons Ltd.

Model-based ultrasound temperature visualization during and following HIFU exposure.

PubMed

Ye, Guoliang; Smith, Penny Probert; Noble, J Alison

2010-02-01

This paper describes the application of signal processing techniques to improve the robustness of ultrasound feedback for displaying changes in temperature distribution in treatment using high-intensity focused ultrasound (HIFU), especially at the low signal-to-noise ratios that might be expected in in vivo abdominal treatment. Temperature estimation is based on the local displacements in ultrasound images taken during HIFU treatment, and a method to improve robustness to outliers is introduced. The main contribution of the paper is in the application of a Kalman filter, a statistical signal processing technique, which uses a simple analytical temperature model of heat dispersion to improve the temperature estimation from the ultrasound measurements during and after HIFU exposure. To reduce the sensitivity of the method to previous assumptions on the material homogeneity and signal-to-noise ratio, an adaptive form is introduced. The method is illustrated using data from HIFU exposure of ex vivo bovine liver. A particular advantage of the stability it introduces is that the temperature can be visualized not only in the intervals between HIFU exposure but also, for some configurations, during the exposure itself. 2010 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

[Response of arbuscular mycorrhizal fungal lipid metabolism to symbiotic signals in mycorrhiza].

PubMed

Tian, Lei; Li, Yuanjing; Tian, Chunjie

2016-01-04

Arbuscular mycorrhizal (AM) fungi play an important role in energy flow and nutrient cycling, besides their wide distribution in the cosystem. With a long co-evolution, AM fungi and host plant have formed a symbiotic relationship, and fungal lipid metabolism may be the key point to find the symbiotic mechanism in arbusculart mycorrhiza. Here, we reviewed the most recent progress on the interaction between AM fungal lipid metabolism and symbiotic signaling networks, especially the response of AM fungal lipid metabolism to symbiotic signals. Furthermore, we discussed the response of AM fungal lipid storage and release to symbiotic or non-symbiotic status, and the correlation between fungal lipid metabolism and nutrient transfer in mycorrhiza. In addition, we explored the feedback of the lipolysis process to molecular signals during the establishment of symbiosis, and the corresponding material conversion and energy metabolism besides the crosstalk of fungal lipid metabolism and signaling networks. This review will help understand symbiotic mechanism of arbuscular mycorrhiza fungi and further application in ecosystem.

Adaptive threshold shearlet transform for surface microseismic data denoising

NASA Astrophysics Data System (ADS)

Tang, Na; Zhao, Xian; Li, Yue; Zhu, Dan

2018-06-01

Random noise suppression plays an important role in microseismic data processing. The microseismic data is often corrupted by strong random noise, which would directly influence identification and location of microseismic events. Shearlet transform is a new multiscale transform, which can effectively process the low magnitude of microseismic data. In shearlet domain, due to different distributions of valid signals and random noise, shearlet coefficients can be shrunk by threshold. Therefore, threshold is vital in suppressing random noise. The conventional threshold denoising algorithms usually use the same threshold to process all coefficients, which causes noise suppression inefficiency or valid signals loss. In order to solve above problems, we propose the adaptive threshold shearlet transform (ATST) for surface microseismic data denoising. In the new algorithm, we calculate the fundamental threshold for each direction subband firstly. In each direction subband, the adjustment factor is obtained according to each subband coefficient and its neighboring coefficients, in order to adaptively regulate the fundamental threshold for different shearlet coefficients. Finally we apply the adaptive threshold to deal with different shearlet coefficients. The experimental denoising results of synthetic records and field data illustrate that the proposed method exhibits better performance in suppressing random noise and preserving valid signal than the conventional shearlet denoising method.

Scalable Multiprocessor for High-Speed Computing in Space

NASA Technical Reports Server (NTRS)

Lux, James; Lang, Minh; Nishimoto, Kouji; Clark, Douglas; Stosic, Dorothy; Bachmann, Alex; Wilkinson, William; Steffke, Richard

2004-01-01

A report discusses the continuing development of a scalable multiprocessor computing system for hard real-time applications aboard a spacecraft. "Hard realtime applications" signifies applications, like real-time radar signal processing, in which the data to be processed are generated at "hundreds" of pulses per second, each pulse "requiring" millions of arithmetic operations. In these applications, the digital processors must be tightly integrated with analog instrumentation (e.g., radar equipment), and data input/output must be synchronized with analog instrumentation, controlled to within fractions of a microsecond. The scalable multiprocessor is a cluster of identical commercial-off-the-shelf generic DSP (digital-signal-processing) computers plus generic interface circuits, including analog-to-digital converters, all controlled by software. The processors are computers interconnected by high-speed serial links. Performance can be increased by adding hardware modules and correspondingly modifying the software. Work is distributed among the processors in a parallel or pipeline fashion by means of a flexible master/slave control and timing scheme. Each processor operates under its own local clock; synchronization is achieved by broadcasting master time signals to all the processors, which compute offsets between the master clock and their local clocks.

EMD-WVD time-frequency distribution for analysis of multi-component signals

NASA Astrophysics Data System (ADS)

Chai, Yunzi; Zhang, Xudong

2016-10-01

Time-frequency distribution (TFD) is two-dimensional function that indicates the time-varying frequency content of one-dimensional signals. And The Wigner-Ville distribution (WVD) is an important and effective time-frequency analysis method. The WVD can efficiently show the characteristic of a mono-component signal. However, a major drawback is the extra cross-terms when multi-component signals are analyzed by WVD. In order to eliminating the cross-terms, we decompose signals into single frequency components - Intrinsic Mode Function (IMF) - by using the Empirical Mode decomposition (EMD) first, then use WVD to analyze each single IMF. In this paper, we define this new time-frequency distribution as EMD-WVD. And the experiment results show that the proposed time-frequency method can solve the cross-terms problem effectively and improve the accuracy of WVD time-frequency analysis.

In-situ measurement of concentrated solar flux and distribution at the aperture of a central solar receiver

NASA Astrophysics Data System (ADS)

Ferriere, Alain; Volut, Mikael; Perez, Antoine; Volut, Yann

2016-05-01

A flux mapping system has been designed, implemented and experimented at the top of the Themis solar tower in France. This system features a moving bar associated to a CCD video camera and a flux gauge mounted onto the bar used as reference measurement for calibration purpose. Images and flux signal are acquired separately. The paper describes the equipment and focus on the data processing to issue the distribution of flux density and concentration at the aperture of the solar receiver. Finally, the solar power entering into the receiver is estimated by integration of flux density. The processing is largely automated in the form of a dedicated software with fast execution. A special attention is paid to the accuracy of the results, to the robustness of the algorithm and to the velocity of the processing.

Using independent component analysis for electrical impedance tomography

NASA Astrophysics Data System (ADS)

Yan, Peimin; Mo, Yulong

2004-05-01

Independent component analysis (ICA) is a way to resolve signals into independent components based on the statistical characteristics of the signals. It is a method for factoring probability densities of measured signals into a set of densities that are as statistically independent as possible under the assumptions of a linear model. Electrical impedance tomography (EIT) is used to detect variations of the electric conductivity of the human body. Because there are variations of the conductivity distributions inside the body, EIT presents multi-channel data. In order to get all information contained in different location of tissue it is necessary to image the individual conductivity distribution. In this paper we consider to apply ICA to EIT on the signal subspace (individual conductivity distribution). Using ICA the signal subspace will then be decomposed into statistically independent components. The individual conductivity distribution can be reconstructed by the sensitivity theorem in this paper. Compute simulations show that the full information contained in the multi-conductivity distribution will be obtained by this method.

Analysis of signal-dependent sensor noise on JPEG 2000-compressed Sentinel-2 multi-spectral images

NASA Astrophysics Data System (ADS)

Uss, M.; Vozel, B.; Lukin, V.; Chehdi, K.

2017-10-01

The processing chain of Sentinel-2 MultiSpectral Instrument (MSI) data involves filtering and compression stages that modify MSI sensor noise. As a result, noise in Sentinel-2 Level-1C data distributed to users becomes processed. We demonstrate that processed noise variance model is bivariate: noise variance depends on image intensity (caused by signal-dependency of photon counting detectors) and signal-to-noise ratio (SNR; caused by filtering/compression). To provide information on processed noise parameters, which is missing in Sentinel-2 metadata, we propose to use blind noise parameter estimation approach. Existing methods are restricted to univariate noise model. Therefore, we propose extension of existing vcNI+fBm blind noise parameter estimation method to multivariate noise model, mvcNI+fBm, and apply it to each band of Sentinel-2A data. Obtained results clearly demonstrate that noise variance is affected by filtering/compression for SNR less than about 15. Processed noise variance is reduced by a factor of 2 - 5 in homogeneous areas as compared to noise variance for high SNR values. Estimate of noise variance model parameters are provided for each Sentinel-2A band. Sentinel-2A MSI Level-1C noise models obtained in this paper could be useful for end users and researchers working in a variety of remote sensing applications.

In Vitro Comparison of Adipokine Export Signals.

PubMed

Sharafi, Parisa; Kocaefe, Y Çetin

2016-01-01

Mammalian cells are widely used for recombinant protein production in research and biotechnology. Utilization of export signals significantly facilitates production and purification processes. 35 years after the discovery of the mammalian export machinery, there still are obscurities regarding the efficiency of the export signals. The aim of this study was the comparative evaluation of the efficiency of selected export signals using adipocytes as a cell model. Adipocytes have a large capacity for protein secretion including several enzymes, adipokines, and other signaling molecules, providing a valid system for a quantitative evaluation. Constructs that expressed N-terminal fusion export signals were generated to express Enhanced Green Fluorescence Protein (EGFP) as a reporter for quantitative and qualitative evaluation. Furthermore, fluorescent microscopy was used to trace the intracellular traffic of the reporter. The export efficiency of six selected proteins secreted from adipocytes was evaluated. Quantitative comparison of intracellular and exported fractions of the recombinant constructs demonstrated a similar efficiency among the studied sequences with minor variations. The export signal of Retinol Binding Protein (RBP4) exhibited the highest efficiency. This study presents the first quantitative data showing variations among export signals, in adipocytes which will help optimization of recombinant protein distribution.

Observations of Near-Bed Deposition and Resuspension Processes at the Fluvial-Tidal Transition Using High Resolution Adcp, Adv, and Lisst

NASA Astrophysics Data System (ADS)

Haught, D. R.; Stumpner, P.

2012-12-01

Processes that determine deposition and resuspension of sediment in fluvial and tidal systems are complicated and difficult to predict because of turbulence-sediment interaction. In fluvial systems net sediment deposition rates near the bed are determined by shear stresses that occur when turbulence interacts with the bed and the entrained sediment above. In tidal systems, processes are driven primarily by the confounding factors of slack water and reversing flow. In this study we investigate near-bed sediment fluxes, settling velocities and sediment size distributions during a change from a fluvial signal to a tidal signal. In order to examine these processes a high resolution, high frequency ADCP, ADV, water quality sonde and LISST data were collocated at the fluvial-tidal transition in the Sacramento River at Freeport, CA. Data were collected at 15-30 minute increments for a month`. Data were dissevered into fluvial and tidal components. Acoustic backscatterence was used as a surrogate to sediment concentration and sediment flux () was calculated from the turbulence properties. Settling velocities were computed from the diffusion-advection equation assuming equilibrium of settling and re-suspension fluxes. Particle density was back-calculated from median particle diameter and calculated settling velocities (Reynolds number<0.5) using Stokes' law. Preliminary results suggest that during peak fluvial discharge that the diffusion-advection gives poor estimates of settling velocities as inferred from particle densities above 3500 kg/m3. During the transition from fluvial to tidal signal and throughout the tidal signal particle densities range from 2650 kg/m3 to 1000 kg/m3, suggesting that settling velocities were accurately estimated. Thus the equilibrium assumption appears poor during high fluvial discharge and reasonable during low fluvial discharge when tidal signal is dominant.

Structural Changes in Senescing Oilseed Rape Leaves at Tissue and Subcellular Levels Monitored by Nuclear Magnetic Resonance Relaxometry through Water Status

PubMed Central

Musse, Maja; De Franceschi, Loriane; Cambert, Mireille; Sorin, Clément; Le Caherec, Françoise; Burel, Agnès; Bouchereau, Alain; Mariette, François; Leport, Laurent

2013-01-01

Nitrogen use efficiency is relatively low in oilseed rape (Brassica napus) due to weak nitrogen remobilization during leaf senescence. Monitoring the kinetics of water distribution associated with the reorganization of cell structures, therefore, would be valuable to improve the characterization of nutrient recycling in leaf tissues and the associated senescence processes. In this study, nuclear magnetic resonance (NMR) relaxometry was used to describe water distribution and status at the cellular level in different leaf ranks of well-watered plants. It was shown to be able to detect slight variations in the evolution of senescence. The NMR results were linked to physiological characterization of the leaves and to light and electron micrographs. A relationship between cell hydration and leaf senescence was revealed and associated with changes in the NMR signal. The relative intensities and the transverse relaxation times of the NMR signal components associated with vacuole water were positively correlated with senescence, describing water uptake and vacuole and cell enlargement. Moreover, the relative intensity of the NMR signal that we assigned to the chloroplast water decreased during the senescence process, in agreement with the decrease in relative chloroplast volume estimated from micrographs. The results are discussed on the basis of water flux occurring at the cellular level during senescence. One of the main applications of this study would be for plant phenotyping, especially for plants under environmental stress such as nitrogen starvation. PMID:23903438

Prospects of Detecting HI using Redshifted 21-cm Radiation at z˜3

NASA Astrophysics Data System (ADS)

Gehlot, Bharat Kumar; Bagla, J. S.

2017-03-01

Distribution of cold gas in the post-reionization era provides an important link between distribution of galaxies and the process of star formation. Redshifted 21-cm radiation from the hyperfine transition of neutral hydrogen allows us to probe the neutral component of cold gas, most of which is to be found in the interstellar medium of galaxies. Existing and upcoming radio telescopes can probe the large scale distribution of neutral hydrogen via HI intensity mapping. In this paper, we use an estimate of the HI power spectrum derived using an ansatz to compute the expected signal from the large scale HI distribution at z˜3. We find that the scale dependence of bias at small scales makes a significant difference to the expected signal even at large angular scales. We compare the predicted signal strength with the sensitivity of radio telescopes that can observe such radiation and calculate the observation time required for detecting neutral hydrogen at these redshifts. We find that OWFA (Ooty Wide Field Array) offers the best possibility to detect neutral hydrogen at z˜3 before the SKA (Square Kilometer Array) becomes operational. We find that the OWFA should be able to make a 3 σ or a more significant detection in 2000 hours of observations at several angular scales. Calculations done using the Fisher matrix approach indicate that a 5 σ detection of the binned HI power spectrum via measurement of the amplitude of the HI power spectrum is possible in 1000 h (Sarkar et al. 2017).

Performance of 20:1 multiplexer for large area charge readouts in directional dark matter TPC detectors

NASA Astrophysics Data System (ADS)

Ezeribe, A. C.; Robinson, M.; Robinson, N.; Scarff, A.; Spooner, N. J. C.; Yuriev, L.

2018-02-01

More target mass is required in current TPC based directional dark matter detectors for improved detector sensitivity. This can be achieved by scaling up the detector volumes, but this results in the need for more analogue signal channels. A possible solution to reducing the overall cost of the charge readout electronics is to multiplex the signal readout channels. Here, we present a multiplexer system in expanded mode based on LMH6574 chips produced by Texas Instruments, originally designed for video processing. The setup has a capability of reducing the number of readouts in such TPC detectors by a factor of 20. Results indicate that the important charge distribution asymmetry along an ionization track is retained after multiplexed signals are demultiplexed.

Effect of signal jitter on the spectrum of rotor impulsive noise

NASA Technical Reports Server (NTRS)

Brooks, Thomas F.

1987-01-01

The effect of randomness or jitter of the acoustic waveform on the spectrum of rotor impulsive noise is studied because of its importance for data interpretation. An acoustic waveform train is modelled representing rotor impulsive noise. The amplitude, shape, and period between occurrences of individual pulses are allowed to be randomized assuming normal probability distributions. Results, in terms of the standard deviations of the variable quantities, are given for the autospectrum as well as special processed spectra designed to separate harmonic and broadband rotor noise components. Consideration is given to the effect of accuracy in triggering or keying to a rotor one per revolution signal. An example is given showing the resultant spectral smearing at the high frequencies due to the pulse signal period variability.

Effect of signal jitter on the spectrum of rotor impulsive noise

NASA Technical Reports Server (NTRS)

Brooks, Thomas F.

1988-01-01

The effect of randomness or jitter of the acoustic waveform on the spectrum of rotor impulsive noise is studied because of its importance for data interpretation. An acoustic waveform train is modeled representing rotor impulsive noise. The amplitude, shape, and period between occurrences of individual pulses are allowed to be randomized assuming normal probability distributions. Results, in terms of the standard deviations of the variable quantities, are given for the autospectrum as well as special processed spectra designed to separate harmonic and broadband rotor noise components. Consideration is given to the effect of accuracy in triggering or keying to a rotor one per revolution signal. An example is given showing the resultant spectral smearing at the high frequencies due to the pulse signal period variability.

Novel characterization method of impedance cardiography signals using time-frequency distributions.

PubMed

Escrivá Muñoz, Jesús; Pan, Y; Ge, S; Jensen, E W; Vallverdú, M

2018-03-16

The purpose of this document is to describe a methodology to select the most adequate time-frequency distribution (TFD) kernel for the characterization of impedance cardiography signals (ICG). The predominant ICG beat was extracted from a patient and was synthetized using time-frequency variant Fourier approximations. These synthetized signals were used to optimize several TFD kernels according to a performance maximization. The optimized kernels were tested for noise resistance on a clinical database. The resulting optimized TFD kernels are presented with their performance calculated using newly proposed methods. The procedure explained in this work showcases a new method to select an appropriate kernel for ICG signals and compares the performance of different time-frequency kernels found in the literature for the case of ICG signals. We conclude that, for ICG signals, the performance (P) of the spectrogram with either Hanning or Hamming windows (P = 0.780) and the extended modified beta distribution (P = 0.765) provided similar results, higher than the rest of analyzed kernels. Graphical abstract Flowchart for the optimization of time-frequency distribution kernels for impedance cardiography signals.

High-latitude distributions of plasma waves and spatial irregularities from DE 2 alternating current electric field observations

NASA Technical Reports Server (NTRS)

Heppner, J. P.; Liebrecht, M. C.; Maynard, N. C.; Pfaff, R. F.

1993-01-01

The high-latitude spatial distributions of average signal intensities in 12 frequency channels between 4 Hz and 512 kHz as measured by the ac electric field spectrometers on the DE-2 spacecraft are analyzed for 18 mo of measurements. In MLT-INL (magnetic local time-invariant latitude) there are three distinct distributions that can be identified with 4-512 Hz signals from spatial irregularities and Alfven waves, 256-Hz to 4.1-kHz signals from ELF hiss, and 4.1-64 kHz signals from VLF auroral hiss, respectively. Overlap between ELF hiss and spatial irregularity signals occurs in the 256-512 Hz band. VLF hiss signals extend downward in frequency into the 1.0-4.1 kHz band and upward into the frequency range 128-512 kHz. The distinctly different spatial distribution patterns for the three bands, 4-256 Hz, 512-1204 Hz, and 4.1-64 kHz, indicate a lack of any causal relationships between VLF hiss, ELF hiss, and lower-frequency signals from spatial irregularities and Alfven waves.

SU-E-T-113: Dose Distribution Using Respiratory Signals and Machine Parameters During Treatment

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

Imae, T; Haga, A; Saotome, N

Purpose: Volumetric modulated arc therapy (VMAT) is a rotational intensity-modulated radiotherapy (IMRT) technique capable of acquiring projection images during treatment. Treatment plans for lung tumors using stereotactic body radiotherapy (SBRT) are calculated with planning computed tomography (CT) images only exhale phase. Purpose of this study is to evaluate dose distribution by reconstructing from only the data such as respiratory signals and machine parameters acquired during treatment. Methods: Phantom and three patients with lung tumor underwent CT scans for treatment planning. They were treated by VMAT while acquiring projection images to derive their respiratory signals and machine parameters including positions ofmore » multi leaf collimators, dose rates and integrated monitor units. The respiratory signals were divided into 4 and 10 phases and machine parameters were correlated with the divided respiratory signals based on the gantry angle. Dose distributions of each respiratory phase were calculated from plans which were reconstructed from the respiratory signals and the machine parameters during treatment. The doses at isocenter, maximum point and the centroid of target were evaluated. Results and Discussion: Dose distributions during treatment were calculated using the machine parameters and the respiratory signals detected from projection images. Maximum dose difference between plan and in treatment distribution was −1.8±0.4% at centroid of target and dose differences of evaluated points between 4 and 10 phases were no significant. Conclusion: The present method successfully evaluated dose distribution using respiratory signals and machine parameters during treatment. This method is feasible to verify the actual dose for moving target.« less

Laser-induced acoustic imaging of underground objects

NASA Astrophysics Data System (ADS)

Li, Wen; DiMarzio, Charles A.; McKnight, Stephen W.; Sauermann, Gerhard O.; Miller, Eric L.

1999-02-01

This paper introduces a new demining technique based on the photo-acoustic interaction, together with results from photo- acoustic experiments. We have buried different types of targets (metal, rubber and plastic) in different media (sand, soil and water) and imaged them by measuring reflection of acoustic waves generated by irradiation with a CO2 laser. Research has been focused on the signal acquisition and signal processing. A deconvolution method using Wiener filters is utilized in data processing. Using a uniform spatial distribution of laser pulses at the ground's surface, we obtained 3D images of buried objects. The images give us a clear representation of the shapes of the underground objects. The quality of the images depends on the mismatch of acoustic impedance of the buried objects, the bandwidth and center frequency of the acoustic sensors and the selection of filter functions.

Instantaneous three-dimensional visualization of concentration distributions in turbulent flows with crossed-plane laser-induced fluorescence imaging

NASA Astrophysics Data System (ADS)

Hoffmann, A.; Zimmermann, F.; Scharr, H.; Krömker, S.; Schulz, C.

2005-01-01

A laser-based technique for measuring instantaneous three-dimensional species concentration distributions in turbulent flows is presented. The laser beam from a single laser is formed into two crossed light sheets that illuminate the area of interest. The laser-induced fluorescence (LIF) signal emitted from excited species within both planes is detected with a single camera via a mirror arrangement. Image processing enables the reconstruction of the three-dimensional data set in close proximity to the cutting line of the two light sheets. Three-dimensional intensity gradients are computed and compared to the two-dimensional projections obtained from the two directly observed planes. Volume visualization by digital image processing gives unique insight into the three-dimensional structures within the turbulent processes. We apply this technique to measurements of toluene-LIF in a turbulent, non-reactive mixing process of toluene and air and to hydroxyl (OH) LIF in a turbulent methane-air flame upon excitation at 248 nm with a tunable KrF excimer laser.

An enhanced multi-channel bacterial foraging optimization algorithm for MIMO communication system

NASA Astrophysics Data System (ADS)

Palanimuthu, Senthilkumar Jayalakshmi; Muthial, Chandrasekaran

2017-04-01

Channel estimation and optimisation are the main challenging tasks in Multi Input Multi Output (MIMO) wireless communication systems. In this work, a Multi-Channel Bacterial Foraging Optimization Algorithm approach is proposed for the selection of antenna in a transmission area. The main advantage of this method is, it reduces the loss of bandwidth during data transmission effectively. Here, we considered the channel estimation and optimisation for improving the transmission speed and reducing the unused bandwidth. Initially, the message is given to the input of the communication system. Then, the symbol mapping process is performed for converting the message into signals. It will be encoded based on the space-time encoding technique. Here, the single signal is divided into multiple signals and it will be given to the input of space-time precoder. Hence, the multiplexing is applied to transmission channel estimation. In this paper, the Rayleigh channel is selected based on the bandwidth range. This is the Gaussian distribution type channel. Then, the demultiplexing is applied on the obtained signal that is the reverse function of multiplexing, which splits the combined signal arriving from a medium into the original information signal. Furthermore, the long-term evolution technique is used for scheduling the time to channels during transmission. Here, the hidden Markov model technique is employed to predict the status information of the channel. Finally, the signals are decoded and the reconstructed signal is obtained after performing the scheduling process. The experimental results evaluate the performance of the proposed MIMO communication system in terms of bit error rate, mean squared error, average throughput, outage capacity and signal to interference noise ratio.

Motivational salience signal in the basal forebrain is coupled with faster and more precise decision speed.

PubMed

Avila, Irene; Lin, Shih-Chieh

2014-03-01

The survival of animals depends critically on prioritizing responses to motivationally salient stimuli. While it is generally believed that motivational salience increases decision speed, the quantitative relationship between motivational salience and decision speed, measured by reaction time (RT), remains unclear. Here we show that the neural correlate of motivational salience in the basal forebrain (BF), defined independently of RT, is coupled with faster and also more precise decision speed. In rats performing a reward-biased simple RT task, motivational salience was encoded by BF bursting response that occurred before RT. We found that faster RTs were tightly coupled with stronger BF motivational salience signals. Furthermore, the fraction of RT variability reflecting the contribution of intrinsic noise in the decision-making process was actively suppressed in faster RT distributions with stronger BF motivational salience signals. Artificially augmenting the BF motivational salience signal via electrical stimulation led to faster and more precise RTs and supports a causal relationship. Together, these results not only describe for the first time, to our knowledge, the quantitative relationship between motivational salience and faster decision speed, they also reveal the quantitative coupling relationship between motivational salience and more precise RT. Our results further establish the existence of an early and previously unrecognized step in the decision-making process that determines both the RT speed and variability of the entire decision-making process and suggest that this novel decision step is dictated largely by the BF motivational salience signal. Finally, our study raises the hypothesis that the dysregulation of decision speed in conditions such as depression, schizophrenia, and cognitive aging may result from the functional impairment of the motivational salience signal encoded by the poorly understood noncholinergic BF neurons.

Motivational Salience Signal in the Basal Forebrain Is Coupled with Faster and More Precise Decision Speed

PubMed Central

Avila, Irene; Lin, Shih-Chieh

2014-01-01

The survival of animals depends critically on prioritizing responses to motivationally salient stimuli. While it is generally believed that motivational salience increases decision speed, the quantitative relationship between motivational salience and decision speed, measured by reaction time (RT), remains unclear. Here we show that the neural correlate of motivational salience in the basal forebrain (BF), defined independently of RT, is coupled with faster and also more precise decision speed. In rats performing a reward-biased simple RT task, motivational salience was encoded by BF bursting response that occurred before RT. We found that faster RTs were tightly coupled with stronger BF motivational salience signals. Furthermore, the fraction of RT variability reflecting the contribution of intrinsic noise in the decision-making process was actively suppressed in faster RT distributions with stronger BF motivational salience signals. Artificially augmenting the BF motivational salience signal via electrical stimulation led to faster and more precise RTs and supports a causal relationship. Together, these results not only describe for the first time, to our knowledge, the quantitative relationship between motivational salience and faster decision speed, they also reveal the quantitative coupling relationship between motivational salience and more precise RT. Our results further establish the existence of an early and previously unrecognized step in the decision-making process that determines both the RT speed and variability of the entire decision-making process and suggest that this novel decision step is dictated largely by the BF motivational salience signal. Finally, our study raises the hypothesis that the dysregulation of decision speed in conditions such as depression, schizophrenia, and cognitive aging may result from the functional impairment of the motivational salience signal encoded by the poorly understood noncholinergic BF neurons. PMID:24642480

Elimination of interference component in Wigner-Ville distribution for the signal with 1/f spectral characteristic.

PubMed

Chan, H L; Lin, J L; Huang, H H; Wu, C P

1997-09-01

A new technique for interference-term suppression in Wigner-Ville distribution (WVD) is proposed for the signal with 1/f spectrum shape. The spectral characteristic of the signal is altered by f alpha filtering before time-frequency analysis and compensated after analysis. With the utilization of the proposed technique in smoothed pseudo Wigner-Ville distribution, an excellent suppression of interference component can be achieved.

Different amplitude and time distribution of the sound of light and classical music

NASA Astrophysics Data System (ADS)

Diodati, P.; Piazza, S.

2000-08-01

Several pieces of different musical kinds were studied measuring $N(A)$, the output amplitude of a peak detector driven by the electric signal arriving to the loudspeaker. Fixed a suitable threshold $\\bar{A}$, we considered $N(A)$, the number of times that $A(t)>\\bar{A}$, each of them we named event and $N(t)$, the distribution of times $t$ between two consecutive events. Some $N(A)$ and $N(t)$ distributions are displayed in the reported logarithmic plots, showing that jazz, pop, rock and other popular rhythms have noise-distribution, while classical pieces of music are characterized by more complex statistics. We pointed out the extraordinary case of the aria ``\\textit{La calunnia \\`{e} un venticello}'', where the words describe an avalanche or seismic process, calumny, and the rossinian music shows $N(A)$ and $N(t)$ distribution typical of earthquakes.

Distributed condition monitoring techniques of optical fiber composite power cable in smart grid

NASA Astrophysics Data System (ADS)

Sun, Zhihui; Liu, Yuan; Wang, Chang; Liu, Tongyu

2011-11-01

Optical fiber composite power cable such as optical phase conductor (OPPC) is significant for the development of smart grid. This paper discusses the distributed cable condition monitoring techniques of the OPPC, which adopts embedded single-mode fiber as the sensing medium. By applying optical time domain reflection and laser Raman scattering, high-resolution spatial positioning and high-precision distributed temperature measurement is executed. And the OPPC cable condition parameters including temperature and its location, current carrying capacity, and location of fracture and loss can be monitored online. OPPC cable distributed condition monitoring experimental system is set up, and the main parts including pulsed fiber laser, weak Raman signal reception, high speed acquisition and cumulative average processing, temperature demodulation and current carrying capacity analysis are introduced. The distributed cable condition monitoring techniques of the OPPC is significant for power transmission management and security.

GTSO: Global Trace Synchronization and Ordering Mechanism for Wireless Sensor Network Monitoring Platforms

PubMed Central

Bonastre, Alberto; Ors, Rafael

2017-01-01

Monitoring is one of the best ways to evaluate the behavior of computer systems. When the monitored system is a distributed system—such as a wireless sensor network (WSN)—the monitoring operation must also be distributed, providing a distributed trace for further analysis. The temporal sequence of occurrence of the events registered by the distributed monitoring platform (DMP) must be correctly established to provide cause-effect relationships between them, so the logs obtained in different monitor nodes must be synchronized. Many of synchronization mechanisms applied to DMPs consist in adjusting the internal clocks of the nodes to the same value as a reference time. However, these mechanisms can create an incoherent event sequence. This article presents a new method to achieve global synchronization of the traces obtained in a DMP. It is based on periodic synchronization signals that are received by the monitor nodes and logged along with the recorded events. This mechanism processes all traces and generates a global post-synchronized trace by scaling all times registered proportionally according with the synchronization signals. It is intended to be a simple but efficient offline mechanism. Its application in a WSN-DMP demonstrates that it guarantees a correct ordering of the events, avoiding the aforementioned issues. PMID:29295494

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

Choi, K.; Itow, Y.; Rott, C., E-mail: koun@stelab.nagoya-u.ac.jp, E-mail: rott@skku.edu, E-mail: itow@stelab.nagoya-u.ac.jp

Dark matter could be captured in the Sun and self-annihilate, giving rise to an observable neutrino flux. Indirect searches for dark matter looking for this signal with neutrino telescopes have resulted in tight constraints on the interaction cross-section of dark matter with ordinary matter. We investigate how robust limits are against astro-physical uncertainties. We study the effect of the velocity distribution of dark matter in our Galaxy on capture rates in the Sun. We investigate four sources of uncertainties: orbital speed of the Sun, escape velocity of dark matter from the halo, dark matter velocity distribution functions and existence ofmore » a dark disc. We find that even extreme cases currently discussed do not decrease the sensitivity of indirect detection significantly because the capture is achieved over a broad range of the velocity distribution by integration over the velocity distribution. The effect of the uncertainty in the high-velocity tail of dark matter halo is very marginal as the capture process is rather inefficient at this region. The difference in capture rate in the Sun for various scenarios is compared to the expected change in event rates for direct detection. The possibility of co-rotating structure with the Sun can largely boost the signal and hence makes the interpretation of indirect detection conservative compared to direct detection.« less

A nonlinear circuit architecture for magnetoencephalographic signal analysis.

PubMed

Bucolo, M; Fortuna, L; Frasca, M; La Rosa, M; Virzì, M C; Shannahoff-Khalsa, D

2004-01-01

The objective of this paper was to face the complex spatio-temporal dynamics shown by Magnetoencephalography (MEG) data by applying a nonlinear distributed approach for the Blind Sources Separation. The effort was to characterize and differ-entiate the phases of a yogic respiratory exercise used in the treatment of obsessive compulsive disorders. The patient performed a precise respiratory protocol, at one breath per minute for 31 minutes, with 10 minutes resting phase before and after. The two steps of classical Independent Component Approach have been performed by using a Cellular Neural Network with two sets of templates. The choice of the couple of suitable templates has been carried out using genetic algorithm optimization techniques. Performing BSS with a nonlinear distributed approach, the outputs of the CNN have been compared to the ICA ones. In all the protocol phases, the main components founded with CNN have similar trends compared with that ones obtained with ICA. Moreover, using this distributed approach, a spatial location has been associated to each component. To underline the spatio-temporal and the nonlinearly of the neural process a distributed nonlinear architecture has been proposed. This strategy has been designed in order to overcome the hypothesis of linear combination among the sources signals, that is characteristic of the ICA approach, taking advantage of the spatial information.

GTSO: Global Trace Synchronization and Ordering Mechanism for Wireless Sensor Network Monitoring Platforms.

PubMed

Navia, Marlon; Campelo, José Carlos; Bonastre, Alberto; Ors, Rafael

2017-12-23

Monitoring is one of the best ways to evaluate the behavior of computer systems. When the monitored system is a distributed system-such as a wireless sensor network (WSN)-the monitoring operation must also be distributed, providing a distributed trace for further analysis. The temporal sequence of occurrence of the events registered by the distributed monitoring platform (DMP) must be correctly established to provide cause-effect relationships between them, so the logs obtained in different monitor nodes must be synchronized. Many of synchronization mechanisms applied to DMPs consist in adjusting the internal clocks of the nodes to the same value as a reference time. However, these mechanisms can create an incoherent event sequence. This article presents a new method to achieve global synchronization of the traces obtained in a DMP. It is based on periodic synchronization signals that are received by the monitor nodes and logged along with the recorded events. This mechanism processes all traces and generates a global post-synchronized trace by scaling all times registered proportionally according with the synchronization signals. It is intended to be a simple but efficient offline mechanism. Its application in a WSN-DMP demonstrates that it guarantees a correct ordering of the events, avoiding the aforementioned issues.

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.

Sampling in the light of Wigner distribution.

PubMed

Stern, Adrian; Javidi, Bahram

2004-03-01

We propose a new method for analysis of the sampling and reconstruction conditions of real and complex signals by use of the Wigner domain. It is shown that the Wigner domain may provide a better understanding of the sampling process than the traditional Fourier domain. For example, it explains how certain non-bandlimited complex functions can be sampled and perfectly reconstructed. On the basis of observations in the Wigner domain, we derive a generalization to the Nyquist sampling criterion. By using this criterion, we demonstrate simple preprocessing operations that can adapt a signal that does not fulfill the Nyquist sampling criterion. The preprocessing operations demonstrated can be easily implemented by optical means.

3D-modelling of radon-induced cellular radiobiological effects in bronchial airway bifurcations: direct versus bystander effects.

PubMed

Szőke, István; Farkas, Arpád; Balásházy, Imre; Hofmann, Werner; Madas, Balázs G; Szőke, Réka

2012-06-01

The primary objective of this paper was to investigate the distribution of radiation doses and the related biological responses in cells of a central airway bifurcation of the human lung of a hypothetical worker of the New Mexico uranium mines during approximately 12 hours of exposure to short-lived radon progenies. State-of-the-art computational modelling techniques were applied to simulate the relevant biophysical and biological processes in a central human airway bifurcation. The non-uniform deposition pattern of inhaled radon daughters caused a non-uniform distribution of energy deposition among cells, and of related cell inactivation and cell transformation probabilities. When damage propagation via bystander signalling was assessed, it produced more cell killing and cell transformation events than did direct effects. If bystander signalling was considered, variations of the average probabilities of cell killing and cell transformation were supra-linear over time. Our results are very sensitive to the radiobiological parameters, derived from in vitro experiments (e.g., range of bystander signalling), applied in this work and suggest that these parameters may not be directly applicable to realistic three-dimensional (3D) epithelium models.

Spatiotemporal Dependency of Age-Related Changes in Brain Signal Variability

PubMed Central

McIntosh, A. R.; Vakorin, V.; Kovacevic, N.; Wang, H.; Diaconescu, A.; Protzner, A. B.

2014-01-01

Recent theoretical and empirical work has focused on the variability of network dynamics in maturation. Such variability seems to reflect the spontaneous formation and dissolution of different functional networks. We sought to extend these observations into healthy aging. Two different data sets, one EEG (total n = 48, ages 18–72) and one magnetoencephalography (n = 31, ages 20–75) were analyzed for such spatiotemporal dependency using multiscale entropy (MSE) from regional brain sources. In both data sets, the changes in MSE were timescale dependent, with higher entropy at fine scales and lower at more coarse scales with greater age. The signals were parsed further into local entropy, related to information processed within a regional source, and distributed entropy (information shared between two sources, i.e., functional connectivity). Local entropy increased for most regions, whereas the dominant change in distributed entropy was age-related reductions across hemispheres. These data further the understanding of changes in brain signal variability across the lifespan, suggesting an inverted U-shaped curve, but with an important qualifier. Unlike earlier in maturation, where the changes are more widespread, changes in adulthood show strong spatiotemporal dependence. PMID:23395850

Poisson-Gaussian Noise Reduction Using the Hidden Markov Model in Contourlet Domain for Fluorescence Microscopy Images

PubMed Central

Yang, Sejung; Lee, Byung-Uk

2015-01-01

In certain image acquisitions processes, like in fluorescence microscopy or astronomy, only a limited number of photons can be collected due to various physical constraints. The resulting images suffer from signal dependent noise, which can be modeled as a Poisson distribution, and a low signal-to-noise ratio. However, the majority of research on noise reduction algorithms focuses on signal independent Gaussian noise. In this paper, we model noise as a combination of Poisson and Gaussian probability distributions to construct a more accurate model and adopt the contourlet transform which provides a sparse representation of the directional components in images. We also apply hidden Markov models with a framework that neatly describes the spatial and interscale dependencies which are the properties of transformation coefficients of natural images. In this paper, an effective denoising algorithm for Poisson-Gaussian noise is proposed using the contourlet transform, hidden Markov models and noise estimation in the transform domain. We supplement the algorithm by cycle spinning and Wiener filtering for further improvements. We finally show experimental results with simulations and fluorescence microscopy images which demonstrate the improved performance of the proposed approach. PMID:26352138

A General theory of Signal Integration for Fault-Tolerant Dynamic Distributed Sensor Networks

DTIC Science & Technology

1993-10-01

related to a) the architecture and fault- tolerance of the distributed sensor network, b) the proper synchronisation of sensor signals, c) the...Computational complexities of the problem of distributed detection. 5) Issues related to recording of events and synchronization in distributed sensor...Intervals for Synchronization in Real Time Distributed Systems", Submitted to Electronic Encyclopedia. 3. V. G. Hegde and S. S. Iyengar "Efficient

NeuroPigPen: A Scalable Toolkit for Processing Electrophysiological Signal Data in Neuroscience Applications Using Apache Pig

PubMed Central

Sahoo, Satya S.; Wei, Annan; Valdez, Joshua; Wang, Li; Zonjy, Bilal; Tatsuoka, Curtis; Loparo, Kenneth A.; Lhatoo, Samden D.

2016-01-01

The recent advances in neurological imaging and sensing technologies have led to rapid increase in the volume, rate of data generation, and variety of neuroscience data. This “neuroscience Big data” represents a significant opportunity for the biomedical research community to design experiments using data with greater timescale, large number of attributes, and statistically significant data size. The results from these new data-driven research techniques can advance our understanding of complex neurological disorders, help model long-term effects of brain injuries, and provide new insights into dynamics of brain networks. However, many existing neuroinformatics data processing and analysis tools were not built to manage large volume of data, which makes it difficult for researchers to effectively leverage this available data to advance their research. We introduce a new toolkit called NeuroPigPen that was developed using Apache Hadoop and Pig data flow language to address the challenges posed by large-scale electrophysiological signal data. NeuroPigPen is a modular toolkit that can process large volumes of electrophysiological signal data, such as Electroencephalogram (EEG), Electrocardiogram (ECG), and blood oxygen levels (SpO2), using a new distributed storage model called Cloudwave Signal Format (CSF) that supports easy partitioning and storage of signal data on commodity hardware. NeuroPigPen was developed with three design principles: (a) Scalability—the ability to efficiently process increasing volumes of data; (b) Adaptability—the toolkit can be deployed across different computing configurations; and (c) Ease of programming—the toolkit can be easily used to compose multi-step data processing pipelines using high-level programming constructs. The NeuroPigPen toolkit was evaluated using 750 GB of electrophysiological signal data over a variety of Hadoop cluster configurations ranging from 3 to 30 Data nodes. The evaluation results demonstrate that the toolkit is highly scalable and adaptable, which makes it suitable for use in neuroscience applications as a scalable data processing toolkit. As part of the ongoing extension of NeuroPigPen, we are developing new modules to support statistical functions to analyze signal data for brain connectivity research. In addition, the toolkit is being extended to allow integration with scientific workflow systems. NeuroPigPen is released under BSD license at: https://sites.google.com/a/case.edu/neuropigpen/. PMID:27375472

NeuroPigPen: A Scalable Toolkit for Processing Electrophysiological Signal Data in Neuroscience Applications Using Apache Pig.

PubMed

Sahoo, Satya S; Wei, Annan; Valdez, Joshua; Wang, Li; Zonjy, Bilal; Tatsuoka, Curtis; Loparo, Kenneth A; Lhatoo, Samden D

2016-01-01

The recent advances in neurological imaging and sensing technologies have led to rapid increase in the volume, rate of data generation, and variety of neuroscience data. This "neuroscience Big data" represents a significant opportunity for the biomedical research community to design experiments using data with greater timescale, large number of attributes, and statistically significant data size. The results from these new data-driven research techniques can advance our understanding of complex neurological disorders, help model long-term effects of brain injuries, and provide new insights into dynamics of brain networks. However, many existing neuroinformatics data processing and analysis tools were not built to manage large volume of data, which makes it difficult for researchers to effectively leverage this available data to advance their research. We introduce a new toolkit called NeuroPigPen that was developed using Apache Hadoop and Pig data flow language to address the challenges posed by large-scale electrophysiological signal data. NeuroPigPen is a modular toolkit that can process large volumes of electrophysiological signal data, such as Electroencephalogram (EEG), Electrocardiogram (ECG), and blood oxygen levels (SpO2), using a new distributed storage model called Cloudwave Signal Format (CSF) that supports easy partitioning and storage of signal data on commodity hardware. NeuroPigPen was developed with three design principles: (a) Scalability-the ability to efficiently process increasing volumes of data; (b) Adaptability-the toolkit can be deployed across different computing configurations; and (c) Ease of programming-the toolkit can be easily used to compose multi-step data processing pipelines using high-level programming constructs. The NeuroPigPen toolkit was evaluated using 750 GB of electrophysiological signal data over a variety of Hadoop cluster configurations ranging from 3 to 30 Data nodes. The evaluation results demonstrate that the toolkit is highly scalable and adaptable, which makes it suitable for use in neuroscience applications as a scalable data processing toolkit. As part of the ongoing extension of NeuroPigPen, we are developing new modules to support statistical functions to analyze signal data for brain connectivity research. In addition, the toolkit is being extended to allow integration with scientific workflow systems. NeuroPigPen is released under BSD license at: https://sites.google.com/a/case.edu/neuropigpen/.

Localization of Acoustic Transients in Shallow Water Environments

DTIC Science & Technology

1992-12-01

effect of the source signal uncertainty (in localizer performance . The localization process consists of two parts. First, a time domain propagation...for public release; distribution is unlimited 4. PERFORMING ORGANIZATION REPORT NUMBER(S) 5. MONITORING ORGANIZATION REPORT NUMBER(S) E OF PERFORMING ...SOURCE OF FUNDING NUMBERS PROGRAM PROJECT TASK WORK UNIT ELEMENT NO. NO. NO. ACCESSION NO. 11. TITLE (Include Security Classification) LOCALIZATION OF

Guided-Wave TeO2 Acousto-Optic Devices

DTIC Science & Technology

1991-01-12

In this research program, Guided-wave TeO2 Acousto - Optic Devices, the properties of surface acoustic waves on tellurium dioxide single crystal...surfaces has been studied for its potential applications as acousto - optic signal processing devices. Personal computer based numerical method has been...interaction with laser beams. Use of the acousto - optic probe, the surface acoustic wave velocity and field distribution have been obtained and compared

Multi-Beam Radio Frequency (RF) Aperture Arrays Using Multiplierless Approximate Fast Fourier Transform (FFT)

DTIC Science & Technology

2017-08-01

filtering, correlation and radio- astronomy . In this report approximate transforms that closely follow the DFT have been studied and found. The approximate...communications, data networks, sensor networks, cognitive radio, radar and beamforming, imaging, filtering, correlation and radio- astronomy . FFTs efficiently...public release; distribution is unlimited. 4.3 Digital Hardware and Design Architectures Collaboration for Astronomy Signal Processing and Electronics

Surveillance system and method having an adaptive sequential probability fault detection test

NASA Technical Reports Server (NTRS)

Herzog, James P. (Inventor); Bickford, Randall L. (Inventor)

2005-01-01

System and method providing surveillance of an asset such as a process and/or apparatus by providing training and surveillance procedures that numerically fit a probability density function to an observed residual error signal distribution that is correlative to normal asset operation and then utilizes the fitted probability density function in a dynamic statistical hypothesis test for providing improved asset surveillance.

Parallel and Distributed Systems for Probabilistic Reasoning

DTIC Science & Technology

2012-12-01

work at CMU I had the opportunity to work with Andreas Krause on Gaussian process models for signal quality estimation in wireless sensor networks ...we reviewed the natural parallelization of the belief propagation algorithm using the synchronous schedule and demonstrated both theoretically and...problem is that the power-law sparsity structure, commonly found in graphs derived from natural phenomena (e.g., social networks and the web

Surveillance system and method having an adaptive sequential probability fault detection test

NASA Technical Reports Server (NTRS)

Bickford, Randall L. (Inventor); Herzog, James P. (Inventor)

2006-01-01

System and method providing surveillance of an asset such as a process and/or apparatus by providing training and surveillance procedures that numerically fit a probability density function to an observed residual error signal distribution that is correlative to normal asset operation and then utilizes the fitted probability density function in a dynamic statistical hypothesis test for providing improved asset surveillance.

Surveillance System and Method having an Adaptive Sequential Probability Fault Detection Test

NASA Technical Reports Server (NTRS)

Bickford, Randall L. (Inventor); Herzog, James P. (Inventor)

2008-01-01

System and method providing surveillance of an asset such as a process and/or apparatus by providing training and surveillance procedures that numerically fit a probability density function to an observed residual error signal distribution that is correlative to normal asset operation and then utilizes the fitted probability density function in a dynamic statistical hypothesis test for providing improved asset surveillance.

Compressed digital holography: from micro towards macro

NASA Astrophysics Data System (ADS)

Schretter, Colas; Bettens, Stijn; Blinder, David; Pesquet-Popescu, Béatrice; Cagnazzo, Marco; Dufaux, Frédéric; Schelkens, Peter

2016-09-01

signal processing methods from software-driven computer engineering and applied mathematics. The compressed sensing theory in particular established a practical framework for reconstructing the scene content using few linear combinations of complex measurements and a sparse prior for regularizing the solution. Compressed sensing found direct applications in digital holography for microscopy. Indeed, the wave propagation phenomenon in free space mixes in a natural way the spatial distribution of point sources from the 3-dimensional scene. As the 3-dimensional scene is mapped to a 2-dimensional hologram, the hologram samples form a compressed representation of the scene as well. This overview paper discusses contributions in the field of compressed digital holography at the micro scale. Then, an outreach on future extensions towards the real-size macro scale is discussed. Thanks to advances in sensor technologies, increasing computing power and the recent improvements in sparse digital signal processing, holographic modalities are on the verge of practical high-quality visualization at a macroscopic scale where much higher resolution holograms must be acquired and processed on the computer.

Dynein-mediated trafficking negatively regulates LET-23 EGFR signaling

PubMed Central

Skorobogata, Olga; Meng, Jassy; Gauthier, Kimberley; Rocheleau, Christian E.

2016-01-01

Epidermal growth factor receptor (EGFR) signaling is essential for animal development, and increased signaling underlies many human cancers. Identifying the genes and cellular processes that regulate EGFR signaling in vivo will help to elucidate how this pathway can become inappropriately activated. Caenorhabditis elegans vulva development provides an in vivo model to genetically dissect EGFR signaling. Here we identified a mutation in dhc-1, the heavy chain of the cytoplasmic dynein minus end–directed microtubule motor, in a genetic screen for regulators of EGFR signaling. Despite the many cellular functions of dynein, DHC-1 is a strong negative regulator of EGFR signaling during vulva induction. DHC-1 is required in the signal-receiving cell and genetically functions upstream or in parallel to LET-23 EGFR. LET-23 EGFR accumulates in cytoplasmic foci in dhc-1 mutants, consistent with mammalian cell studies in which dynein is shown to regulate late endosome trafficking of EGFR with the Rab7 GTPase. However, we found different distributions of LET-23 EGFR foci in rab-7 versus dhc-1 mutants, suggesting that dynein functions at an earlier step of LET-23 EGFR trafficking to the lysosome than RAB-7. Our results demonstrate an in vivo role for dynein in limiting LET-23 EGFR signaling via endosomal trafficking. PMID:27654944

High-resolution distributed temperature sensing with the multiphoton-timing technique

NASA Astrophysics Data System (ADS)

Höbel, M.; Ricka, J.; Wüthrich, M.; Binkert, Th.

1995-06-01

We report on a multiphoton-timing distributed temperature sensor (DTS) based on the concept of distributed anti-Stokes Raman thermometry. The sensor combines the advantage of very high spatial resolution (40 cm) with moderate measurement times. In 5 min it is possible to determine the temperature of as many as 4000 points along an optical fiber with an accuracy Delta T less than 2 deg C. The new feature of the DTS system is the combination of a fast single-photon avalanche diode with specially designed real-time signal-processing electronics. We discuss various parameters that affect the operation of analog and photon-timing DTS systems. Particular emphasis is put on the consequences of the nonideal behavior of sensor components and the corresponding correction procedures.

Network complexity as a measure of information processing across resting-state networks: evidence from the Human Connectome Project

PubMed Central

McDonough, Ian M.; Nashiro, Kaoru

2014-01-01

An emerging field of research focused on fluctuations in brain signals has provided evidence that the complexity of those signals, as measured by entropy, conveys important information about network dynamics (e.g., local and distributed processing). While much research has focused on how neural complexity differs in populations with different age groups or clinical disorders, substantially less research has focused on the basic understanding of neural complexity in populations with young and healthy brain states. The present study used resting-state fMRI data from the Human Connectome Project (Van Essen et al., 2013) to test the extent that neural complexity in the BOLD signal, as measured by multiscale entropy (1) would differ from random noise, (2) would differ between four major resting-state networks previously associated with higher-order cognition, and (3) would be associated with the strength and extent of functional connectivity—a complementary method of estimating information processing. We found that complexity in the BOLD signal exhibited different patterns of complexity from white, pink, and red noise and that neural complexity was differentially expressed between resting-state networks, including the default mode, cingulo-opercular, left and right frontoparietal networks. Lastly, neural complexity across all networks was negatively associated with functional connectivity at fine scales, but was positively associated with functional connectivity at coarse scales. The present study is the first to characterize neural complexity in BOLD signals at a high temporal resolution and across different networks and might help clarify the inconsistencies between neural complexity and functional connectivity, thus informing the mechanisms underlying neural complexity. PMID:24959130

Limits, discovery and cut optimization for a Poisson process with uncertainty in background and signal efficiency: TRolke 2.0

NASA Astrophysics Data System (ADS)

Lundberg, J.; Conrad, J.; Rolke, W.; Lopez, A.

2010-03-01

A C++ class was written for the calculation of frequentist confidence intervals using the profile likelihood method. Seven combinations of Binomial, Gaussian, Poissonian and Binomial uncertainties are implemented. The package provides routines for the calculation of upper and lower limits, sensitivity and related properties. It also supports hypothesis tests which take uncertainties into account. It can be used in compiled C++ code, in Python or interactively via the ROOT analysis framework. Program summaryProgram title: TRolke version 2.0 Catalogue identifier: AEFT_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEFT_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: MIT license No. of lines in distributed program, including test data, etc.: 3431 No. of bytes in distributed program, including test data, etc.: 21 789 Distribution format: tar.gz Programming language: ISO C++. Computer: Unix, GNU/Linux, Mac. Operating system: Linux 2.6 (Scientific Linux 4 and 5, Ubuntu 8.10), Darwin 9.0 (Mac-OS X 10.5.8). RAM:˜20 MB Classification: 14.13. External routines: ROOT ( http://root.cern.ch/drupal/) Nature of problem: The problem is to calculate a frequentist confidence interval on the parameter of a Poisson process with statistical or systematic uncertainties in signal efficiency or background. Solution method: Profile likelihood method, Analytical Running time:<10 seconds per extracted limit.

Detection and imaging of moving objects with SAR by a joint space-time-frequency processing

NASA Astrophysics Data System (ADS)

Barbarossa, Sergio; Farina, Alfonso

This paper proposes a joint spacetime-frequency processing scheme for the detection and imaging of moving targets by Synthetic Aperture Radars (SAR). The method is based on the availability of an array antenna. The signals received by the array elements are combined, in a spacetime processor, to cancel the clutter. Then, they are analyzed in the time-frequency domain, by computing their Wigner-Ville Distribution (WVD), in order to estimate the instantaneous frequency, to be used for the successive phase compensation, necessary to produce a high resolution image.

A Bayesian model for visual space perception

NASA Technical Reports Server (NTRS)

Curry, R. E.

1972-01-01

A model for visual space perception is proposed that contains desirable features in the theories of Gibson and Brunswik. This model is a Bayesian processor of proximal stimuli which contains three important elements: an internal model of the Markov process describing the knowledge of the distal world, the a priori distribution of the state of the Markov process, and an internal model relating state to proximal stimuli. The universality of the model is discussed and it is compared with signal detection theory models. Experimental results of Kinchla are used as a special case.

Application of evolutionary games to modeling carcinogenesis.

PubMed

Swierniak, Andrzej; Krzeslak, Michal

2013-06-01

We review a quite large volume of literature concerning mathematical modelling of processes related to carcinogenesis and the growth of cancer cell populations based on the theory of evolutionary games. This review, although partly idiosyncratic, covers such major areas of cancer-related phenomena as production of cytotoxins, avoidance of apoptosis, production of growth factors, motility and invasion, and intra- and extracellular signaling. We discuss the results of other authors and append to them some additional results of our own simulations dealing with the possible dynamics and/or spatial distribution of the processes discussed.

Distributed Computer Systems for the Republic of Turkish Navy.

DTIC Science & Technology

1985-12-01

and the entire medium spectrum is consumed by the signal. Baseband LAN’s are typically accessed via a carrier sensed multi-access collision detect...Process IPrcoess 2 Cocr~un i cat i Ots B uffer Buffer 6.:,e~2er 1. t -s cessage c~.ur2:s I.essage okul.ks "r, Prcesse eroes pac: et 5packet S et t4Qet...control. a. Routing Routing is the decision process which determines the path a message follows from its source to its destina- tion. Some routing

Technical solutions for simultaneous MEG and SEEG recordings: towards routine clinical use.

PubMed

Badier, J M; Dubarry, A S; Gavaret, M; Chen, S; Trébuchon, A S; Marquis, P; Régis, J; Bartolomei, F; Bénar, C G; Carron, R

2017-09-21

The simultaneous recording of intracerebral EEG (stereotaxic EEG, SEEG) and magnetoencephalography (MEG) is a promising strategy that provides both local and global views on brain pathological activity. Yet, acquiring simultaneous signals poses difficult technical issues that hamper their use in clinical routine. Our objective was thus to develop a set of solutions for recording a high number of SEEG channels while preserving signal quality. We recorded data in a patient with drug resistant epilepsy during presurgical evaluation. We used dedicated insertion screws and optically insulated amplifiers. We recorded 137 SEEG contacts on 10 depth electrodes (5-15 contacts each) and 248 MEG channels (magnetometers). Signal quality was assessed by comparing the distribution of RMS values in different frequency bands to a reference set of MEG acquisitions. The quality of signals was excellent for both MEG and SEEG; for MEG, it was comparable to that of MEG signals without concurrent SEEG. Discharges involving several structures on SEEG were visible on MEG, whereas discharges limited in space were not seen at the surface. SEEG can now be recorded simultaneously with whole-head MEG in routine. This opens new avenues, both methodologically for understanding signals and improving signal processing methods, and clinically for future combined analyses.

Carcinogenesis and Reactive Oxygen Species Signaling: Interaction of the NADPH Oxidase NOX1-5 and Superoxide Dismutase 1-3 Signal Transduction Pathways.

PubMed

Parascandolo, Alessia; Laukkanen, Mikko O

2018-04-05

Reduction/oxidation (redox) balance could be defined as an even distribution of reduction and oxidation complementary processes and their reaction end products. There is a consensus that aberrant levels of reactive oxygen species (ROS), commonly observed in cancer, stimulate primary cell immortalization and progression of carcinogenesis. However, the mechanism how different ROS regulate redox balance is not completely understood. Recent Advances: In the current review, we have summarized the main signaling cascades inducing NADPH oxidase NOX1-5 and superoxide dismutase (SOD) 1-3 expression and their connection to cell proliferation, immortalization, transformation, and CD34 + cell differentiation in thyroid, colon, lung, breast, and hematological cancers. Interestingly, many of the signaling pathways activating redox enzymes or mediating the effect of ROS are common, such as pathways initiated from G protein-coupled receptors and tyrosine kinase receptors involving protein kinase A, phospholipase C, calcium, and small GTPase signaling molecules. The clarification of interaction of signal transduction pathways could explain how cells regulate redox balance and may even provide means to inhibit the accumulation of harmful levels of ROS in human pathologies. Antioxid. Redox Signal. 00, 000-000.

Ripple distribution for nonlinear fiber-optic channels.

PubMed

Sorokina, Mariia; Sygletos, Stylianos; Turitsyn, Sergei

2017-02-06

We demonstrate data rates above the threshold imposed by nonlinearity on conventional optical signals by applying novel probability distribution, which we call ripple distribution, adapted to the properties of the fiber channel. Our results offer a new direction for signal coding, modulation and practical nonlinear distortions compensation algorithms.

Distributed traffic signal control using fuzzy logic

NASA Technical Reports Server (NTRS)

Chiu, Stephen

1992-01-01

We present a distributed approach to traffic signal control, where the signal timing parameters at a given intersection are adjusted as functions of the local traffic condition and of the signal timing parameters at adjacent intersections. Thus, the signal timing parameters evolve dynamically using only local information to improve traffic flow. This distributed approach provides for a fault-tolerant, highly responsive traffic management system. The signal timing at an intersection is defined by three parameters: cycle time, phase split, and offset. We use fuzzy decision rules to adjust these three parameters based only on local information. The amount of change in the timing parameters during each cycle is limited to a small fraction of the current parameters to ensure smooth transition. We show the effectiveness of this method through simulation of the traffic flow in a network of controlled intersections.

Probability distribution functions for intermittent scrape-off layer plasma fluctuations

NASA Astrophysics Data System (ADS)

Theodorsen, A.; Garcia, O. E.

2018-03-01

A stochastic model for intermittent fluctuations in the scrape-off layer of magnetically confined plasmas has been constructed based on a super-position of uncorrelated pulses arriving according to a Poisson process. In the most common applications of the model, the pulse amplitudes are assumed exponentially distributed, supported by conditional averaging of large-amplitude fluctuations in experimental measurement data. This basic assumption has two potential limitations. First, statistical analysis of measurement data using conditional averaging only reveals the tail of the amplitude distribution to be exponentially distributed. Second, exponentially distributed amplitudes leads to a positive definite signal which cannot capture fluctuations in for example electric potential and radial velocity. Assuming pulse amplitudes which are not positive definite often make finding a closed form for the probability density function (PDF) difficult, even if the characteristic function remains relatively simple. Thus estimating model parameters requires an approach based on the characteristic function, not the PDF. In this contribution, the effect of changing the amplitude distribution on the moments, PDF and characteristic function of the process is investigated and a parameter estimation method using the empirical characteristic function is presented and tested on synthetically generated data. This proves valuable for describing intermittent fluctuations of all plasma parameters in the boundary region of magnetized plasmas.

On the inequivalence of the CH and CHSH inequalities due to finite statistics

NASA Astrophysics Data System (ADS)

Renou, M. O.; Rosset, D.; Martin, A.; Gisin, N.

2017-06-01

Different variants of a Bell inequality, such as CHSH and CH, are known to be equivalent when evaluated on nonsignaling outcome probability distributions. However, in experimental setups, the outcome probability distributions are estimated using a finite number of samples. Therefore the nonsignaling conditions are only approximately satisfied and the robustness of the violation depends on the chosen inequality variant. We explain that phenomenon using the decomposition of the space of outcome probability distributions under the action of the symmetry group of the scenario, and propose a method to optimize the statistical robustness of a Bell inequality. In the process, we describe the finite group composed of relabeling of parties, measurement settings and outcomes, and identify correspondences between the irreducible representations of this group and properties of outcome probability distributions such as normalization, signaling or having uniform marginals.

Distribution and specificity of S-cone ("blue cone") signals in subcortical visual pathways.

PubMed

Martin, Paul R; Lee, Barry B

2014-03-01

We review here the distribution of S-cone signals and properties of S-cone recipient receptive fields in subcortical pathways. Nearly everything we know about S-cone signals in the subcortical visual system comes from the study of visual systems in cats and primates (monkeys); in this review, we concentrate on results from macaque and marmoset monkeys. We discuss segregation of S-cone recipient (blue-on and blue-off) receptive fields in the dorsal lateral geniculate nucleus and describe their receptive field properties. We treat in some detail the question of detecting weak S-cone signals as an introduction for newcomers to the field. Finally, we briefly consider the question on how S-cone signals are distributed among nongeniculate targets.

Anatomical location of LPA1 activation and LPA phospholipid precursors in rodent and human brain.

PubMed

González de San Román, Estibaliz; Manuel, Iván; Giralt, María Teresa; Chun, Jerold; Estivill-Torrús, Guillermo; Rodríguez de Fonseca, Fernando; Santín, Luis Javier; Ferrer, Isidro; Rodríguez-Puertas, Rafael

2015-08-01

Lysophosphatidic acid (LPA) is a signaling molecule that binds to six known G protein-coupled receptors: LPA1 -LPA6 . LPA evokes several responses in the CNS, including cortical development and folding, growth of the axonal cone and its retraction process. Those cell processes involve survival, migration, adhesion proliferation, differentiation, and myelination. The anatomical localization of LPA1 is incompletely understood, particularly with regard to LPA binding. Therefore, we have used functional [(35) S]GTPγS autoradiography to verify the anatomical distribution of LPA1 binding sites in adult rodent and human brain. The greatest activity was observed in myelinated areas of the white matter such as corpus callosum, internal capsule and cerebellum. MaLPA1 -null mice (a variant of LPA1 -null) lack [(35) S]GTPγS basal binding in white matter areas, where the LPA1 receptor is expressed at high levels, suggesting a relevant role of the activity of this receptor in the most myelinated brain areas. In addition, phospholipid precursors of LPA were localized by MALDI-IMS in both rodent and human brain slices identifying numerous species of phosphatides and phosphatidylcholines. Both phosphatides and phosphatidylcholines species represent potential LPA precursors. The anatomical distribution of these precursors in rodent and human brain may indicate a metabolic relationship between LPA and LPA1 receptors. Lysophosphatidic acid (LPA) is a signaling molecule that binds to six known G protein-coupled receptors (GPCR), LPA1 to LPA6 . LPA evokes several responses in the central nervous system (CNS), including cortical development and folding, growth of the axonal cone and its retraction process. We used functional [(35) S]GTPγS autoradiography to verify the anatomical distribution of LPA1 -binding sites in adult rodent and human brain. The distribution of LPA1 receptors in rat, mouse and human brains show the highest activity in white matter myelinated areas. The basal and LPA-evoked activities are abolished in MaLPA1 -null mice. The phospholipid precursors of LPA are localized by MALDI-IMS. The anatomical distribution of LPA precursors in rodent and human brain suggests a relationship with functional LPA1 receptors. © 2015 International Society for Neurochemistry.

The decay process of rotating unstable systems through the passage time distribution

NASA Astrophysics Data System (ADS)

Jiménez-Aquino, J. I.; Cortés, Emilio; Aquino, N.

2001-05-01

In this work we propose a general scheme to characterize, through the passage time distribution, the decay process of rotational unstable systems in the presence of external forces of large amplitude. The formalism starts with a matricial Langevin type equation formulated in the context of two dynamical representations given, respectively, by the vectors x and y, both related by a time dependent rotation matrix. The transformation preserves the norm of the vector and decouples the set of dynamical equations in the transformed space y. We study the dynamical characterization of the systems of two variables and show that the statistical properties of the passage time distribution are essentially equivalent in both dynamics. The theory is applied to the laser system studied in Dellunde et al. (Opt. Commun. 102 (1993) 277), where the effect of large injected signals on the transient dynamics of the laser has been studied in terms of complex electric field. The analytical results are compared with numerical simulation.

An Autonomous Distributed Fault-Tolerant Local Positioning System

NASA Technical Reports Server (NTRS)

Malekpour, Mahyar R.

2017-01-01

We describe a fault-tolerant, GPS-independent (Global Positioning System) distributed autonomous positioning system for static/mobile objects and present solutions for providing highly-accurate geo-location data for the static/mobile objects in dynamic environments. The reliability and accuracy of a positioning system fundamentally depends on two factors; its timeliness in broadcasting signals and the knowledge of its geometry, i.e., locations and distances of the beacons. Existing distributed positioning systems either synchronize to a common external source like GPS or establish their own time synchrony using a scheme similar to a master-slave by designating a particular beacon as the master and other beacons synchronize to it, resulting in a single point of failure. Another drawback of existing positioning systems is their lack of addressing various fault manifestations, in particular, communication link failures, which, as in wireless networks, are increasingly dominating the process failures and are typically transient and mobile, in the sense that they typically affect different messages to/from different processes over time.

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

DTIC Science & Technology

1993-03-01

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

Ellipsoidal cell flow system

DOEpatents

Salzman, Gary C.; Mullaney, Paul F.

1976-01-01

The disclosure relates to a system incorporating an ellipsoidal flow chamber having light reflective walls for low level light detection in practicing cellular analysis. The system increases signal-to-noise ratio by a factor of ten over prior art systems. In operation, laser light passes through the primary focus of the ellipsoid. A controlled flow of cells simultaneously passes through this focus so that the laser light impinges on the cells and is modulated by the cells. The reflective walls of the ellipsoid reflect the cell-modulated light to the secondary focus of the ellipsoid. A tapered light guide at the secondary focus picks up a substantial portion of modulated reflective light and directs it onto a light detector to produce a signal. The signal is processed to obtain the intensity distribution of the modulated light and hence sought after characteristics of the cells. In addition, cells may be dyed so as to fluoresce in response to the laser light and their fluorescence may be processed as cell-modulated light above described. A light discriminating filter would be used to distinguish reflected modulated laser light from reflected fluorescent light.

An Open-Source Hardware and Software System for Acquisition and Real-Time Processing of Electrophysiology during High Field MRI

PubMed Central

Purdon, Patrick L.; Millan, Hernan; Fuller, Peter L.; Bonmassar, Giorgio

2008-01-01

Simultaneous recording of electrophysiology and functional magnetic resonance imaging (fMRI) is a technique of growing importance in neuroscience. Rapidly evolving clinical and scientific requirements have created a need for hardware and software that can be customized for specific applications. Hardware may require customization to enable a variety of recording types (e.g., electroencephalogram, local field potentials, or multi-unit activity) while meeting the stringent and costly requirements of MRI safety and compatibility. Real-time signal processing tools are an enabling technology for studies of learning, attention, sleep, epilepsy, neurofeedback, and neuropharmacology, yet real-time signal processing tools are difficult to develop. We describe an open source system for simultaneous electrophysiology and fMRI featuring low-noise (< 0.6 uV p-p input noise), electromagnetic compatibility for MRI (tested up to 7 Tesla), and user-programmable real-time signal processing. The hardware distribution provides the complete specifications required to build an MRI-compatible electrophysiological data acquisition system, including circuit schematics, print circuit board (PCB) layouts, Gerber files for PCB fabrication and robotic assembly, a bill of materials with part numbers, data sheets, and vendor information, and test procedures. The software facilitates rapid implementation of real-time signal processing algorithms. This system has used in human EEG/fMRI studies at 3 and 7 Tesla examining the auditory system, visual system, sleep physiology, and anesthesia, as well as in intracranial electrophysiological studies of the non-human primate visual system during 3 Tesla fMRI, and in human hyperbaric physiology studies at depths of up to 300 feet below sea level. PMID:18761038

An open-source hardware and software system for acquisition and real-time processing of electrophysiology during high field MRI.

PubMed

Purdon, Patrick L; Millan, Hernan; Fuller, Peter L; Bonmassar, Giorgio

2008-11-15

Simultaneous recording of electrophysiology and functional magnetic resonance imaging (fMRI) is a technique of growing importance in neuroscience. Rapidly evolving clinical and scientific requirements have created a need for hardware and software that can be customized for specific applications. Hardware may require customization to enable a variety of recording types (e.g., electroencephalogram, local field potentials, or multi-unit activity) while meeting the stringent and costly requirements of MRI safety and compatibility. Real-time signal processing tools are an enabling technology for studies of learning, attention, sleep, epilepsy, neurofeedback, and neuropharmacology, yet real-time signal processing tools are difficult to develop. We describe an open-source system for simultaneous electrophysiology and fMRI featuring low-noise (<0.6microV p-p input noise), electromagnetic compatibility for MRI (tested up to 7T), and user-programmable real-time signal processing. The hardware distribution provides the complete specifications required to build an MRI-compatible electrophysiological data acquisition system, including circuit schematics, print circuit board (PCB) layouts, Gerber files for PCB fabrication and robotic assembly, a bill of materials with part numbers, data sheets, and vendor information, and test procedures. The software facilitates rapid implementation of real-time signal processing algorithms. This system has been used in human EEG/fMRI studies at 3 and 7T examining the auditory system, visual system, sleep physiology, and anesthesia, as well as in intracranial electrophysiological studies of the non-human primate visual system during 3T fMRI, and in human hyperbaric physiology studies at depths of up to 300 feet below sea level.

Toward high fidelity spectral sensing and RF signal processing in silicon photonic and nano-opto-mechanical platforms

NASA Astrophysics Data System (ADS)

Siddiqui, Aleem; Reinke, Charles; Shin, Heedeuk; Jarecki, Robert L.; Starbuck, Andrew L.; Rakich, Peter

2017-05-01

The performance of electronic systems for radio-frequency (RF) spectrum analysis is critical for agile radar and communications systems, ISR (intelligence, surveillance, and reconnaissance) operations in challenging electromagnetic (EM) environments, and EM-environment situational awareness. While considerable progress has been made in size, weight, and power (SWaP) and performance metrics in conventional RF technology platforms, fundamental limits make continued improvements increasingly difficult. Alternatively, we propose employing cascaded transduction processes in a chip-scale nano-optomechanical system (NOMS) to achieve a spectral sensor with exceptional signal-linearity, high dynamic range, narrow spectral resolution and ultra-fast sweep times. By leveraging the optimal capabilities of photons and phonons, the system we pursue in this work has performance metrics scalable well beyond the fundamental limitations inherent to all electronic systems. In our device architecture, information processing is performed on wide-bandwidth RF-modulated optical signals by photon-mediated phononic transduction of the modulation to the acoustical-domain for narrow-band filtering, and then back to the optical-domain by phonon-mediated phase modulation (the reverse process). Here, we rely on photonics to efficiently distribute signals for parallel processing, and on phononics for effective and flexible RF-frequency manipulation. This technology is used to create RF-filters that are insensitive to the optical wavelength, with wide center frequency bandwidth selectivity (1-100GHz), ultra-narrow filter bandwidth (1-100MHz), and high dynamic range (70dB), which we will present. Additionally, using this filter as a building block, we will discuss current results and progress toward demonstrating a multichannel-filter with a bandwidth of < 10MHz per channel, while minimizing cumulative optical/acoustic/optical transduced insertion-loss to ideally < 10dB. These proposed metric represent significant improvements over RF-platforms.

Spatial Distribution of Cellular Function: The Partitioning of Proteins between Mitochondria and the Nucleus in MCF7 Breast Cancer Cells

PubMed Central

Qattan, Amal T.; Radulovic, Marko; Crawford, Mark; Godovac-Zimmermann, Jasminka

2014-01-01

Concurrent proteomics analysis of the nuclei and mitochondria of MCF7 breast cancer cells identified 985 proteins (40% of all detected proteins) present in both organelles. Numerous proteins from all five complexes involved in oxidative phosphorylation (e.g., NDUFA5, NDUFB10, NDUFS1, NDUF2, SDHA, UQRB, UQRC2, UQCRH, COX5A, COX5B, MT-CO2, ATP5A1, ATP5B, ATP5H, etc.), from the TCA-cycle (DLST, IDH2, IDH3A, OGDH, SUCLAG2, etc.), and from glycolysis (ALDOA, ENO1, FBP1, GPI, PGK1, TALDO1, etc.) were distributed to both the nucleus and mitochondria. In contrast, proteins involved in nuclear/mitochondrial RNA processing/translation and Ras/Rab signaling showed different partitioning patterns. The identity of the OxPhos, TCA-cycle, and glycolysis proteins distributed to both the nucleus and mitochondria provides evidence for spatio-functional integration of these processes over the two different subcellular organelles. We suggest that there are unrecognized aspects of functional coordination between the nucleus and mitochondria, that integration of core functional processes via wide subcellular distribution of constituent proteins is a common characteristic of cells, and that subcellular spatial integration of function may be a vital aspect of cancer. PMID:23051583

A method for acetylcholinesterase staining of brain sections previously processed for receptor autoradiography.

PubMed

Lim, M M; Hammock, E A D; Young, L J

2004-02-01

Receptor autoradiography using selective radiolabeled ligands allows visualization of brain receptor distribution and density on film. The resolution of specific brain regions on the film often can be difficult to discern owing to the general spread of the radioactive label and the lack of neuroanatomical landmarks on film. Receptor binding is a chemically harsh protocol that can render the tissue virtually unstainable by Nissl and other conventional stains used to delineate neuroanatomical boundaries of brain regions. We describe a method for acetylcholinesterase (AChE) staining of slides previously processed for receptor binding. AChE staining is a useful tool for delineating major brain nuclei and tracts. AChE staining on sections that have been processed for receptor autoradiography provides a direct comparison of brain regions for more precise neuroanatomical description. We report a detailed thiocholine protocol that is a modification of the Koelle-Friedenwald method to amplify the AChE signal in brain sections previously processed for autoradiography. We also describe several temporal and experimental factors that can affect the density and clarity of the AChE signal when using this protocol.

Probabilistic co-adaptive brain-computer interfacing

NASA Astrophysics Data System (ADS)

Bryan, Matthew J.; Martin, Stefan A.; Cheung, Willy; Rao, Rajesh P. N.

2013-12-01

Objective. Brain-computer interfaces (BCIs) are confronted with two fundamental challenges: (a) the uncertainty associated with decoding noisy brain signals, and (b) the need for co-adaptation between the brain and the interface so as to cooperatively achieve a common goal in a task. We seek to mitigate these challenges. Approach. We introduce a new approach to brain-computer interfacing based on partially observable Markov decision processes (POMDPs). POMDPs provide a principled approach to handling uncertainty and achieving co-adaptation in the following manner: (1) Bayesian inference is used to compute posterior probability distributions (‘beliefs’) over brain and environment state, and (2) actions are selected based on entire belief distributions in order to maximize total expected reward; by employing methods from reinforcement learning, the POMDP’s reward function can be updated over time to allow for co-adaptive behaviour. Main results. We illustrate our approach using a simple non-invasive BCI which optimizes the speed-accuracy trade-off for individual subjects based on the signal-to-noise characteristics of their brain signals. We additionally demonstrate that the POMDP BCI can automatically detect changes in the user’s control strategy and can co-adaptively switch control strategies on-the-fly to maximize expected reward. Significance. Our results suggest that the framework of POMDPs offers a promising approach for designing BCIs that can handle uncertainty in neural signals and co-adapt with the user on an ongoing basis. The fact that the POMDP BCI maintains a probability distribution over the user’s brain state allows a much more powerful form of decision making than traditional BCI approaches, which have typically been based on the output of classifiers or regression techniques. Furthermore, the co-adaptation of the system allows the BCI to make online improvements to its behaviour, adjusting itself automatically to the user’s changing circumstances.

Short-Circuit Fault Detection and Classification Using Empirical Wavelet Transform and Local Energy for Electric Transmission Line.

PubMed

Huang, Nantian; Qi, Jiajin; Li, Fuqing; Yang, Dongfeng; Cai, Guowei; Huang, Guilin; Zheng, Jian; Li, Zhenxin

2017-09-16

In order to improve the classification accuracy of recognizing short-circuit faults in electric transmission lines, a novel detection and diagnosis method based on empirical wavelet transform (EWT) and local energy (LE) is proposed. First, EWT is used to deal with the original short-circuit fault signals from photoelectric voltage transformers, before the amplitude modulated-frequency modulated (AM-FM) mode with a compactly supported Fourier spectrum is extracted. Subsequently, the fault occurrence time is detected according to the modulus maxima of intrinsic mode function (IMF₂) from three-phase voltage signals processed by EWT. After this process, the feature vectors are constructed by calculating the LE of the fundamental frequency based on the three-phase voltage signals of one period after the fault occurred. Finally, the classifier based on support vector machine (SVM) which was constructed with the LE feature vectors is used to classify 10 types of short-circuit fault signals. Compared with complementary ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and improved CEEMDAN methods, the new method using EWT has a better ability to present the frequency in time. The difference in the characteristics of the energy distribution in the time domain between different types of short-circuit faults can be presented by the feature vectors of LE. Together, simulation and real signals experiment demonstrate the validity and effectiveness of the new approach.

Short-Circuit Fault Detection and Classification Using Empirical Wavelet Transform and Local Energy for Electric Transmission Line

PubMed Central

Huang, Nantian; Qi, Jiajin; Li, Fuqing; Yang, Dongfeng; Cai, Guowei; Huang, Guilin; Zheng, Jian; Li, Zhenxin

2017-01-01

In order to improve the classification accuracy of recognizing short-circuit faults in electric transmission lines, a novel detection and diagnosis method based on empirical wavelet transform (EWT) and local energy (LE) is proposed. First, EWT is used to deal with the original short-circuit fault signals from photoelectric voltage transformers, before the amplitude modulated-frequency modulated (AM-FM) mode with a compactly supported Fourier spectrum is extracted. Subsequently, the fault occurrence time is detected according to the modulus maxima of intrinsic mode function (IMF2) from three-phase voltage signals processed by EWT. After this process, the feature vectors are constructed by calculating the LE of the fundamental frequency based on the three-phase voltage signals of one period after the fault occurred. Finally, the classifier based on support vector machine (SVM) which was constructed with the LE feature vectors is used to classify 10 types of short-circuit fault signals. Compared with complementary ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and improved CEEMDAN methods, the new method using EWT has a better ability to present the frequency in time. The difference in the characteristics of the energy distribution in the time domain between different types of short-circuit faults can be presented by the feature vectors of LE. Together, simulation and real signals experiment demonstrate the validity and effectiveness of the new approach. PMID:28926953

Halo-independent determination of the unmodulated WIMP signal in DAMA: the isotropic case

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

Gondolo, Paolo; Scopel, Stefano, E-mail: paolo.gondolo@utah.edu, E-mail: scopel@sogang.ac.kr

2017-09-01

We present a halo-independent determination of the unmodulated signal corresponding to the DAMA modulation if interpreted as due to dark matter weakly interacting massive particles (WIMPs). First we show how a modulated signal gives information on the WIMP velocity distribution function in the Galactic rest frame from which the unmodulated signal descends. Then we describe a mathematically-sound profile likelihood analysis in which the likelihood is profiled over a continuum of nuisance parameters (namely, the WIMP velocity distribution). As a first application of the method, which is very general and valid for any class of velocity distributions, we restrict the analysismore » to velocity distributions that are isotropic in the Galactic frame. In this way we obtain halo-independent maximum-likelihood estimates and confidence intervals for the DAMA unmodulated signal. We find that the estimated unmodulated signal is in line with expectations for a WIMP-induced modulation and is compatible with the DAMA background+signal rate. Specifically, for the isotropic case we find that the modulated amplitude ranges between a few percent and about 25% of the unmodulated amplitude, depending on the WIMP mass.« less

Instantaneous phase estimation to measure weak velocity variations: application to noise correlation on seismic data at the exploration scale

NASA Astrophysics Data System (ADS)

Corciulo, M.; Roux, P.; Campillo, M.; Dubucq, D.

2010-12-01

Passive imaging from noise cross-correlation is a consolidated analysis applied at continental and regional scale whereas its use at local scale for seismic exploration purposes is still uncertain. The development of passive imaging by cross-correlation analysis is based on the extraction of the Green’s function from seismic noise data. In a completely random field in time and space, the cross-correlation permits to retrieve the complete Green’s function whatever the complexity of the medium. At the exploration scale and at frequency above 2 Hz, the noise sources are not ideally distributed around the stations which strongly affect the extraction of the direct arrivals from the noise cross-correlation process. In order to overcome this problem, the coda waves extracted from noise correlation could be useful. Coda waves describe long and scattered paths sampling the medium in different ways such that they become sensitive to weak velocity variations without being dependent on the noise source distribution. Indeed, scatters in the medium behave as a set of secondary noise sources which randomize the spatial distribution of noise sources contributing to the coda waves in the correlation process. We developed a new technique to measure weak velocity changes based on the computation of the local phase variations (instantaneous phase variation or IPV) of the cross-correlated signals. This newly-developed technique takes advantage from the doublet and stretching techniques classically used to monitor weak velocity variation from coda waves. We apply IPV to data acquired in Northern America (Canada) on a 1-km side square seismic network laid out by 397 stations. Data used to study temporal variations are cross-correlated signals computed on 10-minutes ambient noise in the frequency band 2-5 Hz. As the data set was acquired over five days, about 660 files are processed to perform a complete temporal analysis for each stations pair. The IPV permits to estimate the phase shift all over the signal length without any assumption on the medium velocity. The instantaneous phase is computed using the Hilbert transform of the signal. For each stations pair, we measure the phase difference between successive correlation functions calculated for 10 minutes of ambient noise. We then fit the instantaneous phase shift using a first-order polynomial function. The measure of the velocity variation corresponds to the slope of this fit. Compared to other techniques, the advantage of IPV is a very fast procedure which efficiently provides the measure of velocity variation on large data sets. Both experimental results and numerical tests on synthetic signals will be presented to assess the reliability of the IPV technique, with comparison to the doublet and stretching methods.

Continental-shelf Scale Passive Ocean AcousticWaveguide Remote Sensing of Marine Mammals and other Submerged Objects including Detection, Localization, and Classification

NASA Astrophysics Data System (ADS)

Wang, Delin

In this thesis, we develop the basics of the Passive Ocean Acoustic Waveguide Remote Sensing (POAWRS) technique for the instantaneous continental-shelf scale detection, localization and species classification of marine mammal vocalizations. POAWRS uses a large-aperture, densely sampled coherent hydrophone array system with orders of magnitude higher array gain to enhance signal-to-noise ratios (SNR) by coherent beamforming, enabling detection of underwater acoustic signals either two orders of magnitude more distant in range or lower in SNR than a single hydrophone. The ability to employ coherent spatial processing of signals with the POAWRS technology significantly improves areal coverage, enabling detection of oceanic sound sources over instantaneous wide areas spanning 100 km or more in diameter. The POAWRS approach was applied to analyze marine mammal vocalizations from diverse species received on a 160-element Office Naval Research Five Octave Research Array (ONR-FORA) deployed during their feeding season in Fall 2006 in the Gulf of Maine. The species-dependent temporal-spatial distribution of marine mammal vocalizations and correlation to the prey fish distributions have been determined. Furthermore, the probability of detection regions, source level distributions and pulse compression gains of the vocalization signals from diverse marine mammal species have been estimated. We also develop an approach for enhancing the angular resolution and improving bearing estimates of acoustic signals received on a coherent hydrophone array with multiple-nested uniformly-spaced subapertures, such as the ONR-FORA, by nonuniform array beamforming. Finally we develop a low-cost non-oil-filled towable prototype hydrophone array that consists of eight hydrophone elements with real-time data acquisition and 100 m tow cable. The approach demonstrated here will be applied in the development of a full 160 element POAWRS-type low-cost coherent hydrophone array system in the future.

Frequency variations of the earth's obliquity and the 100-kyr ice-age cycles

NASA Technical Reports Server (NTRS)

Liu, Han-Shou

1992-01-01

Changes in the earth's climate are induced by variations in the earth's orbital parameters which modulate the seasonal distribution of solar radiation. Periodicities in the geological climate record with cycles of 100, 41, and 23 kyr have been linked with changes in obliquity, eccentricity, and precession of the equinoxes. The effect of variations of eccentricity during a 100 kyr period is weak relative to the signals from obliquity and precession variations and it may therefore be expected that the 100 kyr signal in the climate record would be of low intensity. However, this signal dominates the climate record and internal nonlinear processes within the climate system have previously been proposed to account for this fact. The author shows that variations in the frequency of the obliquity cycle can give rise to strong 100-kyr forcing of climate.

Fade durations in satellite-path mobile radio propagation

NASA Technical Reports Server (NTRS)

Schmier, Robert G.; Bostian, Charles W.

1986-01-01

Fades on satellite to land mobile radio links are caused by several factors, the most important of which are multipath propagation and vegetative shadowing. Designers of vehicular satellite communications systems require information about the statistics of fade durations in order to overcome or compensate for the fades. Except for a few limiting cases, only the mean fade duration can be determined analytically, and all other statistics must be obtained experimentally or via simulation. This report describes and presents results from a computer program developed at Virginia Tech to simulate satellite path propagation of a mobile station in a rural area. It generates rapidly-fading and slowly-fading signals by separate processes that yield correct cumulative signal distributions and then combines these to simulate the overall signal. This is then analyzed to yield the statistics of fade duration.