Photonics-based real-time ultra-high-range-resolution radar with broadband signal generation and processing.

PubMed

Zhang, Fangzheng; Guo, Qingshui; Pan, Shilong

2017-10-23

Real-time and high-resolution target detection is highly desirable in modern radar applications. Electronic techniques have encountered grave difficulties in the development of such radars, which strictly rely on a large instantaneous bandwidth. In this article, a photonics-based real-time high-range-resolution radar is proposed with optical generation and processing of broadband linear frequency modulation (LFM) signals. A broadband LFM signal is generated in the transmitter by photonic frequency quadrupling, and the received echo is de-chirped to a low frequency signal by photonic frequency mixing. The system can operate at a high frequency and a large bandwidth while enabling real-time processing by low-speed analog-to-digital conversion and digital signal processing. A conceptual radar is established. Real-time processing of an 8-GHz LFM signal is achieved with a sampling rate of 500 MSa/s. Accurate distance measurement is implemented with a maximum error of 4 mm within a range of ~3.5 meters. Detection of two targets is demonstrated with a range-resolution as high as 1.875 cm. We believe the proposed radar architecture is a reliable solution to overcome the limitations of current radar on operation bandwidth and processing speed, and it is hopefully to be used in future radars for real-time and high-resolution target detection and imaging.

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

Real-Time, General-Purpose, High-Speed Signal Processing Systems for Underwater Research. Proceedings of a Working Level Conference held at Supreme Allied Commander, Atlantic Anti-Submarine Warfare Research Center (SACLANTCEN) on 18-21 September 1979. Part 2. Sessions IV to VI.

DTIC Science & Technology

1979-12-01

ACTIVATED, SYSTEM OPERATION AND TESTING MASCOT PROVIDES: 1. SYSTEM BUILD SOFTWARE COMPILE-TIME CHECKS,a. 2. RUN-TIME SUPERVISOR KERNEL, 3, MONITOR AND...p AD-AOBI 851 SACLANT ASW RESEARCH CENTRE LA SPEZIA 11ITALY) F/B 1711 REAL-TIME, GENERAL-PURPOSE, HIGH-SPEED SIGNAL PROCESSING SYSTEM -- ETC (U) DEC 79...Table of Contents Table of Contents (Cont’d) Page Signal processing language and operating system (w) 23-1 to 23-12 by S. Weinstein A modular signal

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

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

Lager, D.; Azevedo, S.

1983-10-25

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

Interactive Digital Signal Processor

NASA Technical Reports Server (NTRS)

Mish, W. H.

1985-01-01

Interactive Digital Signal Processor, IDSP, consists of set of time series analysis "operators" based on various algorithms commonly used for digital signal analysis. Processing of digital signal time series to extract information usually achieved by applications of number of fairly standard operations. IDSP excellent teaching tool for demonstrating application for time series operators to artificially generated signals.

A methodology to condition distorted acoustic emission signals to identify fracture timing from human cadaver spine impact tests.

PubMed

Arun, Mike W J; Yoganandan, Narayan; Stemper, Brian D; Pintar, Frank A

2014-12-01

While studies have used acoustic sensors to determine fracture initiation time in biomechanical studies, a systematic procedure is not established to process acoustic signals. The objective of the study was to develop a methodology to condition distorted acoustic emission data using signal processing techniques to identify fracture initiation time. The methodology was developed from testing a human cadaver lumbar spine column. Acoustic sensors were glued to all vertebrae, high-rate impact loading was applied, load-time histories were recorded (load cell), and fracture was documented using CT. Compression fracture occurred to L1 while other vertebrae were intact. FFT of raw voltage-time traces were used to determine an optimum frequency range associated with high decibel levels. Signals were bandpass filtered in this range. Bursting pattern was found in the fractured vertebra while signals from other vertebrae were silent. Bursting time was associated with time of fracture initiation. Force at fracture was determined using this time and force-time data. The methodology is independent of selecting parameters a priori such as fixing a voltage level(s), bandpass frequency and/or using force-time signal, and allows determination of force based on time identified during signal processing. The methodology can be used for different body regions in cadaver experiments. Copyright © 2014 Elsevier Ltd. All rights reserved.

Application of homomorphic signal processing to stress wave factor analysis

NASA Technical Reports Server (NTRS)

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

1985-01-01

The stress wave factor (SWF) signal, which is the output of an ultrasonic testing system where the transmitting and receiving transducers are coupled to the same face of the test structure, is analyzed in the frequency domain. The SWF signal generated in an isotropic elastic plate is modelled as the superposition of successive reflections. The reflection which is generated by the stress waves which travel p times as a longitudinal (P) wave and s times as a shear (S) wave through the plate while reflecting back and forth between the bottom and top faces of the plate is designated as the reflection with p, s. Short-time portions of the SWF signal are considered for obtaining spectral information on individual reflections. If the significant reflections are not overlapped, the short-time Fourier analysis is used. A summary of the elevant points of homomorphic signal processing, which is also called cepstrum analysis, is given. Homomorphic signal processing is applied to short-time SWF signals to obtain estimates of the log spectra of individual reflections for cases in which the reflections are overlapped. Two typical SWF signals generated in aluminum plates (overlapping and non-overlapping reflections) are analyzed.

Practical Sub-Nyquist Sampling via Array-Based Compressed Sensing Receiver Architecture

DTIC Science & Technology

2016-07-10

different array ele- ments at different sub-Nyquist sampling rates. Signal processing inspired by the sparse fast Fourier transform allows for signal...reconstruction algorithms can be computationally demanding (REF). The related sparse Fourier transform algorithms aim to reduce the processing time nec- essary to...compute the DFT of frequency-sparse signals [7]. In particular, the sparse fast Fourier transform (sFFT) achieves processing time better than the

Investigation of optical current transformer signal processing method based on an improved Kalman algorithm

NASA Astrophysics Data System (ADS)

Shen, Yan; Ge, Jin-ming; Zhang, Guo-qing; Yu, Wen-bin; Liu, Rui-tong; Fan, Wei; Yang, Ying-xuan

2018-01-01

This paper explores the problem of signal processing in optical current transformers (OCTs). Based on the noise characteristics of OCTs, such as overlapping signals, noise frequency bands, low signal-to-noise ratios, and difficulties in acquiring statistical features of noise power, an improved standard Kalman filtering algorithm was proposed for direct current (DC) signal processing. The state-space model of the OCT DC measurement system is first established, and then mixed noise can be processed by adding mixed noise into measurement and state parameters. According to the minimum mean squared error criterion, state predictions and update equations of the improved Kalman algorithm could be deduced based on the established model. An improved central difference Kalman filter was proposed for alternating current (AC) signal processing, which improved the sampling strategy and noise processing of colored noise. Real-time estimation and correction of noise were achieved by designing AC and DC noise recursive filters. Experimental results show that the improved signal processing algorithms had a good filtering effect on the AC and DC signals with mixed noise of OCT. Furthermore, the proposed algorithm was able to achieve real-time correction of noise during the OCT filtering process.

Improving the signal analysis for in vivo photoacoustic flow cytometry

NASA Astrophysics Data System (ADS)

Niu, Zhenyu; Yang, Ping; Wei, Dan; Tang, Shuo; Wei, Xunbin

2015-03-01

At early stage of cancer, a small number of circulating tumor cells (CTCs) appear in the blood circulation. Thus, early detection of malignant circulating tumor cells has great significance for timely treatment to reduce the cancer death rate. We have developed an in vivo photoacoustic flow cytometry (PAFC) to monitor the metastatic process of CTCs and record the signals from target cells. Information of target cells which is helpful to the early therapy would be obtained through analyzing and processing the signals. The raw signal detected from target cells often contains some noise caused by electronic devices, such as background noise and thermal noise. We choose the Wavelet denoising method to effectively distinguish the target signal from background noise. Processing in time domain and frequency domain would be combined to analyze the signal after denoising. This algorithm contains time domain filter and frequency transformation. The frequency spectrum image of the signal contains distinctive features that can be used to analyze the property of target cells or particles. The PAFC technique can detect signals from circulating tumor cells or other particles. The processing methods have a great potential for analyzing signals accurately and rapidly.

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.

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.

Directional dual-tree complex wavelet packet transforms for processing quadrature signals.

PubMed

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

2016-03-01

Quadrature signals containing in-phase and quadrature-phase components are used in many signal processing applications in every field of science and engineering. Specifically, Doppler ultrasound systems used to evaluate cardiovascular disorders noninvasively also result in quadrature format signals. In order to obtain directional blood flow information, the quadrature outputs have to be preprocessed using methods such as asymmetrical and symmetrical phasing filter techniques. These resultant directional signals can be employed in order to detect asymptomatic embolic signals caused by small emboli, which are indicators of a possible future stroke, in the cerebral circulation. Various transform-based methods such as Fourier and wavelet were frequently used in processing embolic signals. However, most of the times, the Fourier and discrete wavelet transforms are not appropriate for the analysis of embolic signals due to their non-stationary time-frequency behavior. Alternatively, discrete wavelet packet transform can perform an adaptive decomposition of the time-frequency axis. In this study, directional discrete wavelet packet transforms, which have the ability to map directional information while processing quadrature signals and have less computational complexity than the existing wavelet packet-based methods, are introduced. The performances of proposed methods are examined in detail by using single-frequency, synthetic narrow-band, and embolic quadrature signals.

Real-time Nyquist signaling with dynamic precision and flexible non-integer oversampling.

PubMed

Schmogrow, R; Meyer, M; Schindler, P C; Nebendahl, B; Dreschmann, M; Meyer, J; Josten, A; Hillerkuss, D; Ben-Ezra, S; Becker, J; Koos, C; Freude, W; Leuthold, J

2014-01-13

We demonstrate two efficient processing techniques for Nyquist signals, namely computation of signals using dynamic precision as well as arbitrary rational oversampling factors. With these techniques along with massively parallel processing it becomes possible to generate and receive high data rate Nyquist signals with flexible symbol rates and bandwidths, a feature which is highly desirable for novel flexgrid networks. We achieved maximum bit rates of 252 Gbit/s in real-time.

Applied digital signal processing systems for vortex flowmeter with digital signal processing.

PubMed

Xu, Ke-Jun; Zhu, Zhi-Hai; Zhou, Yang; Wang, Xiao-Fen; Liu, San-Shan; Huang, Yun-Zhi; Chen, Zhi-Yuan

2009-02-01

The spectral analysis is combined with digital filter to process the vortex sensor signal for reducing the effect of disturbance at low frequency from pipe vibrations and increasing the turndown ratio. Using digital signal processing chip, two kinds of digital signal processing systems are developed to implement these algorithms. One is an integrative system, and the other is a separated system. A limiting amplifier is designed in the input analog condition circuit to adapt large amplitude variation of sensor signal. Some technique measures are taken to improve the accuracy of the output pulse, speed up the response time of the meter, and reduce the fluctuation of the output signal. The experimental results demonstrate the validity of the digital signal processing systems.

Development of wireless brain computer interface with embedded multitask scheduling and its application on real-time driver's drowsiness detection and warning.

PubMed

Lin, Chin-Teng; Chen, Yu-Chieh; Huang, Teng-Yi; Chiu, Tien-Ting; Ko, Li-Wei; Liang, Sheng-Fu; Hsieh, Hung-Yi; Hsu, Shang-Hwa; Duann, Jeng-Ren

2008-05-01

Biomedical signal monitoring systems have been rapidly advanced with electronic and information technologies in recent years. However, most of the existing physiological signal monitoring systems can only record the signals without the capability of automatic analysis. In this paper, we proposed a novel brain-computer interface (BCI) system that can acquire and analyze electroencephalogram (EEG) signals in real-time to monitor human physiological as well as cognitive states, and, in turn, provide warning signals to the users when needed. The BCI system consists of a four-channel biosignal acquisition/amplification module, a wireless transmission module, a dual-core signal processing unit, and a host system for display and storage. The embedded dual-core processing system with multitask scheduling capability was proposed to acquire and process the input EEG signals in real time. In addition, the wireless transmission module, which eliminates the inconvenience of wiring, can be switched between radio frequency (RF) and Bluetooth according to the transmission distance. Finally, the real-time EEG-based drowsiness monitoring and warning algorithms were implemented and integrated into the system to close the loop of the BCI system. The practical online testing demonstrates the feasibility of using the proposed system with the ability of real-time processing, automatic analysis, and online warning feedback in real-world operation and living environments.

[Real-time detection and processing of medical signals under windows using Lcard analog interfaces].

PubMed

Kuz'min, A A; Belozerov, A E; Pronin, T V

2008-01-01

Multipurpose modular software for an analog interface based on Lcard 761 is considered. Algorithms for pipeline processing of medical signals under Windows with dynamic control of computational resources are suggested. The software consists of user-friendly completable modifiable modules. The module hierarchy is based on object-oriented heritage principles, which make it possible to construct various real-time systems for long-term detection, processing, and imaging of multichannel medical signals.

SIG. Signal Processing, Analysis, & Display

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

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

1992-01-22

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

SIG. Signal Processing, Analysis, & Display

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

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

1992-01-22

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

Research on photodiode detector-based spatial transient light detection and processing system

NASA Astrophysics Data System (ADS)

Liu, Meiying; Wang, Hu; Liu, Yang; Zhao, Hui; Nan, Meng

2016-10-01

In order to realize real-time signal identification and processing of spatial transient light, the features and the energy of the captured target light signal are first described and quantitatively calculated. Considering that the transient light signal has random occurrence, a short duration and an evident beginning and ending, a photodiode detector based spatial transient light detection and processing system is proposed and designed in this paper. This system has a large field of view and is used to realize non-imaging energy detection of random, transient and weak point target under complex background of spatial environment. Weak signal extraction under strong background is difficult. In this paper, considering that the background signal changes slowly and the target signal changes quickly, filter is adopted for signal's background subtraction. A variable speed sampling is realized by the way of sampling data points with a gradually increased interval. The two dilemmas that real-time processing of large amount of data and power consumption required by the large amount of data needed to be stored are solved. The test results with self-made simulative signal demonstrate the effectiveness of the design scheme. The practical system could be operated reliably. The detection and processing of the target signal under the strong sunlight background was realized. The results indicate that the system can realize real-time detection of target signal's characteristic waveform and monitor the system working parameters. The prototype design could be used in a variety of engineering applications.

BPSK Demodulation Using Digital Signal Processing

NASA Technical Reports Server (NTRS)

Garcia, Thomas R.

1996-01-01

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

Signal Processing, Analysis, & Display

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

Lager, Darrell; Azevado, Stephen

1986-06-01

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

SIG. Signal Processing, Analysis, & Display

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

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

1992-01-22

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

Acousto-Optic Interaction in Surface Acoustic Waves and Its Application to Real Time Signal Processing.

DTIC Science & Technology

1977-12-30

ACOUSTO - OPTIC INTERACTION IN SURFACE ACOUSTIC WAVES AND ITS APP--ETC(U) DEC 77 0 SCHUMER, P DAS NOOOIJ -75-C-0772 NCLASSIFIED MA-ONR-30 Nt.EE E’h...CHART NAT*NAL BUREAU OF STANDARDS 1-63- ACOUSTO - OPTIC INTERACTION IN SURFACE ACOUSTIC WAVES AND ITS APPLICATION TO REAL TIME SIGNAL PROCESSING By 00 D... Acousto - optics , Integrated optics, Optical Signal Processing. 20. AbSKTRACT (Continue an reverse side it neceary and idewnt& by block mum ber) The

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.

A high-efficiency real-time digital signal averager for time-of-flight mass spectrometry.

PubMed

Wang, Yinan; Xu, Hui; Li, Qingjiang; Li, Nan; Huang, Zhengxu; Zhou, Zhen; Liu, Husheng; Sun, Zhaolin; Xu, Xin; Yu, Hongqi; Liu, Haijun; Li, David D-U; Wang, Xi; Dong, Xiuzhen; Gao, Wei

2013-05-30

Analog-to-digital converter (ADC)-based acquisition systems are widely applied in time-of-flight mass spectrometers (TOFMS) due to their ability to record the signal intensity of all ions within the same pulse. However, the acquisition system raises the requirement for data throughput, along with increasing the conversion rate and resolution of the ADC. It is therefore of considerable interest to develop a high-performance real-time acquisition system, which can relieve the limitation of data throughput. We present in this work a high-efficiency real-time digital signal averager, consisting of a signal conditioner, a data conversion module and a signal processing module. Two optimization strategies are implemented using field programmable gate arrays (FPGAs) to enhance the efficiency of the real-time processing. A pipeline procedure is used to reduce the time consumption of the accumulation strategy. To realize continuous data transfer, a high-efficiency transmission strategy is developed, based on a ping-pong procedure. The digital signal averager features good responsiveness, analog bandwidth and dynamic performance. The optimal effective number of bits reaches 6.7 bits. For a 32 µs record length, the averager can realize 100% efficiency with an extraction frequency below 31.23 kHz by modifying the number of accumulation steps. In unit time, the averager yields superior signal-to-noise ratio (SNR) compared with data accumulation in a computer. The digital signal averager is combined with a vacuum ultraviolet single-photon ionization time-of-flight mass spectrometer (VUV-SPI-TOFMS). The efficiency of the real-time processing is tested by analyzing the volatile organic compounds (VOCs) from ordinary printed materials. In these experiments, 22 kinds of compounds are detected, and the dynamic range exceeds 3 orders of magnitude. Copyright © 2013 John Wiley & Sons, Ltd.

Real-time radar signal processing using GPGPU (general-purpose graphic processing unit)

NASA Astrophysics Data System (ADS)

Kong, Fanxing; Zhang, Yan Rockee; Cai, Jingxiao; Palmer, Robert D.

2016-05-01

This study introduces a practical approach to develop real-time signal processing chain for general phased array radar on NVIDIA GPUs(Graphical Processing Units) using CUDA (Compute Unified Device Architecture) libraries such as cuBlas and cuFFT, which are adopted from open source libraries and optimized for the NVIDIA GPUs. The processed results are rigorously verified against those from the CPUs. Performance benchmarked in computation time with various input data cube sizes are compared across GPUs and CPUs. Through the analysis, it will be demonstrated that GPGPUs (General Purpose GPU) real-time processing of the array radar data is possible with relatively low-cost commercial GPUs.

Broadband true time delay for microwave signal processing, using slow light based on stimulated Brillouin scattering in optical fibers.

PubMed

Chin, Sanghoon; Thévenaz, Luc; Sancho, Juan; Sales, Salvador; Capmany, José; Berger, Perrine; Bourderionnet, Jérôme; Dolfi, Daniel

2010-10-11

We experimentally demonstrate a novel technique to process broadband microwave signals, using all-optically tunable true time delay in optical fibers. The configuration to achieve true time delay basically consists of two main stages: photonic RF phase shifter and slow light, based on stimulated Brillouin scattering in fibers. Dispersion properties of fibers are controlled, separately at optical carrier frequency and in the vicinity of microwave signal bandwidth. This way time delay induced within the signal bandwidth can be manipulated to correctly act as true time delay with a proper phase compensation introduced to the optical carrier. We completely analyzed the generated true time delay as a promising solution to feed phased array antenna for radar systems and to develop dynamically reconfigurable microwave photonic filters.

A Versatile Multichannel Digital Signal Processing Module for Microcalorimeter Arrays

NASA Astrophysics Data System (ADS)

Tan, H.; Collins, J. W.; Walby, M.; Hennig, W.; Warburton, W. K.; Grudberg, P.

2012-06-01

Different techniques have been developed for reading out microcalorimeter sensor arrays: individual outputs for small arrays, and time-division or frequency-division or code-division multiplexing for large arrays. Typically, raw waveform data are first read out from the arrays using one of these techniques and then stored on computer hard drives for offline optimum filtering, leading not only to requirements for large storage space but also limitations on achievable count rate. Thus, a read-out module that is capable of processing microcalorimeter signals in real time will be highly desirable. We have developed multichannel digital signal processing electronics that are capable of on-board, real time processing of microcalorimeter sensor signals from multiplexed or individual pixel arrays. It is a 3U PXI module consisting of a standardized core processor board and a set of daughter boards. Each daughter board is designed to interface a specific type of microcalorimeter array to the core processor. The combination of the standardized core plus this set of easily designed and modified daughter boards results in a versatile data acquisition module that not only can easily expand to future detector systems, but is also low cost. In this paper, we first present the core processor/daughter board architecture, and then report the performance of an 8-channel daughter board, which digitizes individual pixel outputs at 1 MSPS with 16-bit precision. We will also introduce a time-division multiplexing type daughter board, which takes in time-division multiplexing signals through fiber-optic cables and then processes the digital signals to generate energy spectra in real time.

A Study on Signal Group Processing of AUTOSAR COM Module

NASA Astrophysics Data System (ADS)

Lee, Jeong-Hwan; Hwang, Hyun Yong; Han, Tae Man; Ahn, Yong Hak

2013-06-01

In vehicle, there are many ECU(Electronic Control Unit)s, and ECUs are connected to networks such as CAN, LIN, FlexRay, and so on. AUTOSAR COM(Communication) which is a software platform of AUTOSAR(AUTomotive Open System ARchitecture) in the international industry standards of automotive electronic software processes signals and signal groups for data communications between ECUs. Real-time and reliability are very important for data communications in the vehicle. Therefore, in this paper, we analyze functions of signals and signal groups used in COM, and represent that functions of signal group are more efficient than signals in real-time data synchronization and network resource usage between the sender and receiver.

Design of signal reception and processing system of embedded ultrasonic endoscope

NASA Astrophysics Data System (ADS)

Li, Ming; Yu, Feng; Zhang, Ruiqiang; Li, Yan; Chen, Xiaodong; Yu, Daoyin

2009-11-01

Embedded Ultrasonic Endoscope, based on embedded microprocessor and embedded real-time operating system, sends a micro ultrasonic probe into coelom through the biopsy channel of the Electronic Endoscope to get the fault histology features of digestive organs by rotary scanning, and acquires the pictures of the alimentary canal mucosal surface. At the same time, ultrasonic signals are processed by signal reception and processing system, forming images of the full histology of the digestive organs. Signal Reception and Processing System is an important component of Embedded Ultrasonic Endoscope. However, the traditional design, using multi-level amplifiers and special digital processing circuits to implement signal reception and processing, is no longer satisfying the standards of high-performance, miniaturization and low power requirements that embedded system requires, and as a result of the high noise that multi-level amplifier brought, the extraction of small signal becomes hard. Therefore, this paper presents a method of signal reception and processing based on double variable gain amplifier and FPGA, increasing the flexibility and dynamic range of the Signal Reception and Processing System, improving system noise level, and reducing power consumption. Finally, we set up the embedded experiment system, using a transducer with the center frequency of 8MHz to scan membrane samples, and display the image of ultrasonic echo reflected by each layer of membrane, with a frame rate of 5Hz, verifying the correctness of the system.

Motor imaginary-based brain-machine interface design using programmable logic controllers for the disabled.

PubMed

Jeyabalan, Vickneswaran; Samraj, Andrews; Loo, Chu Kiong

2010-10-01

Aiming at the implementation of brain-machine interfaces (BMI) for the aid of disabled people, this paper presents a system design for real-time communication between the BMI and programmable logic controllers (PLCs) to control an electrical actuator that could be used in devices to help the disabled. Motor imaginary signals extracted from the brain’s motor cortex using an electroencephalogram (EEG) were used as a control signal. The EEG signals were pre-processed by means of adaptive recursive band-pass filtrations (ARBF) and classified using simplified fuzzy adaptive resonance theory mapping (ARTMAP) in which the classified signals are then translated into control signals used for machine control via the PLC. A real-time test system was designed using MATLAB for signal processing, KEP-Ware V4 OLE for process control (OPC), a wireless local area network router, an Omron Sysmac CPM1 PLC and a 5 V/0.3A motor. This paper explains the signal processing techniques, the PLC's hardware configuration, OPC configuration and real-time data exchange between MATLAB and PLC using the MATLAB OPC toolbox. The test results indicate that the function of exchanging real-time data can be attained between the BMI and PLC through OPC server and proves that it is an effective and feasible method to be applied to devices such as wheelchairs or electronic equipment.

Industrial realization of a direct Fourier transform in automated experimental data processing systems

NASA Technical Reports Server (NTRS)

Lyubashevskiy, G. S.

1973-01-01

Fourier processing of automatic signals transforms direct current voltage into a numerical form through bandpass filtration in time-pulse multiplying devices. It is shown that the ratio of the interference energy to the useful signal energy is inversely proportional to the square of the product of the depth of the width modulation and the ratio of the time constant averaging to the cross-multiplied signals.

Jitter model and signal processing techniques for pulse width modulation optical recording

NASA Technical Reports Server (NTRS)

Liu, Max M.-K.

1991-01-01

A jitter model and signal processing techniques are discussed for data recovery in Pulse Width Modulation (PWM) optical recording. In PWM, information is stored through modulating sizes of sequential marks alternating in magnetic polarization or in material structure. Jitter, defined as the deviation from the original mark size in the time domain, will result in error detection if it is excessively large. A new approach is taken in data recovery by first using a high speed counter clock to convert time marks to amplitude marks, and signal processing techniques are used to minimize jitter according to the jitter model. The signal processing techniques include motor speed and intersymbol interference equalization, differential and additive detection, and differential and additive modulation.

PAU/GNSS-R: Implementation, Performance and First Results of a Real-Time Delay-Doppler Map Reflectometer Using Global Navigation Satellite System Signals

PubMed Central

Marchan-Hernandez, Juan Fernando; Camps, Adriano; Rodriguez-Alvarez, Nereida; Bosch-Lluis, Xavier; Ramos-Perez, Isaac; Valencia, Enric

2008-01-01

Signals from Global Navigation Satellite Systems (GNSS) were originally conceived for position and speed determination, but they can be used as signals of opportunity as well. The reflection process over a given surface modifies the properties of the scattered signal, and therefore, by processing the reflected signal, relevant geophysical data regarding the surface under study (land, sea, ice…) can be retrieved. In essence, a GNSS-R receiver is a multi-channel GNSS receiver that computes the received power from a given satellite at a number of different delay and Doppler bins of the incoming signal. The first approaches to build such a receiver consisted of sampling and storing the scattered signal for later post-processing. However, a real-time approach to the problem is desirable to obtain immediately useful geophysical variables and reduce the amount of data. The use of FPGA technology makes this possible, while at the same time the system can be easily reconfigured. The signal tracking and processing constraints made necessary to fully design several new blocks. The uniqueness of the implemented system described in this work is the capability to compute in real-time Delay-Doppler maps (DDMs) either for four simultaneous satellites or just one, but with a larger number of bins. The first tests have been conducted from a cliff over the sea and demonstrate the successful performance of the instrument to compute DDMs in real-time from the measured reflected GNSS/R signals. The processing of these measurements shall yield quantitative relationships between the sea state (mainly driven by the surface wind and the swell) and the overall DDM shape. The ultimate goal is to use the DDM shape to correct the sea state influence on the L-band brightness temperature to improve the retrieval of the sea surface salinity (SSS). PMID:27879862

Optical signal processing techniques and applications of optical phase modulation in high-speed communication systems

NASA Astrophysics Data System (ADS)

Deng, Ning

In recent years, optical phase modulation has attracted much research attention in the field of fiber optic communications. Compared with the traditional optical intensity-modulated signal, one of the main merits of the optical phase-modulated signal is the better transmission performance. For optical phase modulation, in spite of the comprehensive study of its transmission performance, only a little research has been carried out in terms of its functions, applications and signal processing for future optical networks. These issues are systematically investigated in this thesis. The research findings suggest that optical phase modulation and its signal processing can greatly facilitate flexible network functions and high bandwidth which can be enjoyed by end users. In the thesis, the most important physical-layer technology, signal processing and multiplexing, are investigated with optical phase-modulated signals. Novel and advantageous signal processing and multiplexing approaches are proposed and studied. Experimental investigations are also reported and discussed in the thesis. Optical time-division multiplexing and demultiplexing. With the ever-increasing demand on communication bandwidth, optical time division multiplexing (OTDM) is an effective approach to upgrade the capacity of each wavelength channel in current optical systems. OTDM multiplexing can be simply realized, however, the demultiplexing requires relatively complicated signal processing and stringent timing control, and thus hinders its practicability. To tackle this problem, in this thesis a new OTDM scheme with hybrid DPSK and OOK signals is proposed. Experimental investigation shows this scheme can greatly enhance the demultiplexing timing misalignment and improve the demultiplexing performance, and thus make OTDM more practical and cost effective. All-optical signal processing. In current and future optical communication systems and networks, the data rate per wavelength has been approaching the speed limitation of electronics. Thus, all-optical signal processing techniques are highly desirable to support the necessary optical switching functionalities in future ultrahigh-speed optical packet-switching networks. To cope with the wide use of optical phase-modulated signals, in the thesis, an all-optical logic for DPSK or PSK input signals is developed, for the first time. Based on four-wave mixing in semiconductor optical amplifier, the structure of the logic gate is simple, compact, and capable of supporting ultrafast operation. In addition to the general logic processing, a simple label recognition scheme, as a specific signal processing function, is proposed for phase-modulated label signals. The proposed scheme can recognize any incoming label pattern according to the local pattern, and is potentially capable of handling variable-length label patterns. Optical access network with multicast overlay and centralized light sources. In the arena of optical access networks, wavelength division multiplexing passive optical network (WDM-PON) is a promising technology to deliver high-speed data traffic. However, most of proposed WDM-PONs only support conventional point-to-point service, and cannot meet the requirement of increasing demand on broadcast and multicast service. In this thesis, a simple network upgrade is proposed based on the traditional PON architecture to support both point-to-point and multicast service. In addition, the two service signals are modulated on the same lightwave carrier. The upstream signal is also remodulated on the same carrier at the optical network unit, which can significantly relax the requirement on wavelength management at the network unit.

Introduction to Radar Signal and Data Processing: The Opportunity

DTIC Science & Technology

2006-09-01

SpA) Director of Analysis of Integrated Systems Group Via Tiburtina Km. 12.400 00131 Rome ITALY e.mail: afarina@selex-si.com Key words: radar...signal processing, data processing, adaptivity, space-time adaptive processing, knowledge based systems , CFAR. 1. SUMMARY This paper introduces to...the lecture series dedicated to the knowledge-based radar signal and data processing. Knowledge-based expert system (KBS) is in the realm of

Moving in time: Bayesian causal inference explains movement coordination to auditory beats

PubMed Central

Elliott, Mark T.; Wing, Alan M.; Welchman, Andrew E.

2014-01-01

Many everyday skilled actions depend on moving in time with signals that are embedded in complex auditory streams (e.g. musical performance, dancing or simply holding a conversation). Such behaviour is apparently effortless; however, it is not known how humans combine auditory signals to support movement production and coordination. Here, we test how participants synchronize their movements when there are potentially conflicting auditory targets to guide their actions. Participants tapped their fingers in time with two simultaneously presented metronomes of equal tempo, but differing in phase and temporal regularity. Synchronization therefore depended on integrating the two timing cues into a single-event estimate or treating the cues as independent and thereby selecting one signal over the other. We show that a Bayesian inference process explains the situations in which participants choose to integrate or separate signals, and predicts motor timing errors. Simulations of this causal inference process demonstrate that this model provides a better description of the data than other plausible models. Our findings suggest that humans exploit a Bayesian inference process to control movement timing in situations where the origin of auditory signals needs to be resolved. PMID:24850915

Multichannel heterodyning for wideband interferometry, correlation and signal processing

DOEpatents

Erskine, David J.

1999-01-01

A method of signal processing a high bandwidth signal by coherently subdividing it into many narrow bandwidth channels which are individually processed at lower frequencies in a parallel manner. Autocorrelation and correlations can be performed using reference frequencies which may drift slowly with time, reducing cost of device. Coordinated adjustment of channel phases alters temporal and spectral behavior of net signal process more precisely than a channel used individually. This is a method of implementing precision long coherent delays, interferometers, and filters for high bandwidth optical or microwave signals using low bandwidth electronics. High bandwidth signals can be recorded, mathematically manipulated, and synthesized.

Multichannel heterodyning for wideband interferometry, correlation and signal processing

DOEpatents

Erskine, D.J.

1999-08-24

A method is disclosed of signal processing a high bandwidth signal by coherently subdividing it into many narrow bandwidth channels which are individually processed at lower frequencies in a parallel manner. Autocorrelation and correlations can be performed using reference frequencies which may drift slowly with time, reducing cost of device. Coordinated adjustment of channel phases alters temporal and spectral behavior of net signal process more precisely than a channel used individually. This is a method of implementing precision long coherent delays, interferometers, and filters for high bandwidth optical or microwave signals using low bandwidth electronics. High bandwidth signals can be recorded, mathematically manipulated, and synthesized. 50 figs.

The mathematical theory of signal processing and compression-designs

NASA Astrophysics Data System (ADS)

Feria, Erlan H.

2006-05-01

The mathematical theory of signal processing, named processor coding, will be shown to inherently arise as the computational time dual of Shannon's mathematical theory of communication which is also known as source coding. Source coding is concerned with signal source memory space compression while processor coding deals with signal processor computational time compression. Their combination is named compression-designs and referred as Conde in short. A compelling and pedagogically appealing diagram will be discussed highlighting Conde's remarkable successful application to real-world knowledge-aided (KA) airborne moving target indicator (AMTI) radar.

A cloud masking algorithm for EARLINET lidar systems

NASA Astrophysics Data System (ADS)

Binietoglou, Ioannis; Baars, Holger; D'Amico, Giuseppe; Nicolae, Doina

2015-04-01

Cloud masking is an important first step in any aerosol lidar processing chain as most data processing algorithms can only be applied on cloud free observations. Up to now, the selection of a cloud-free time interval for data processing is typically performed manually, and this is one of the outstanding problems for automatic processing of lidar data in networks such as EARLINET. In this contribution we present initial developments of a cloud masking algorithm that permits the selection of the appropriate time intervals for lidar data processing based on uncalibrated lidar signals. The algorithm is based on a signal normalization procedure using the range of observed values of lidar returns, designed to work with different lidar systems with minimal user input. This normalization procedure can be applied to measurement periods of only few hours, even if no suitable cloud-free interval exists, and thus can be used even when only a short period of lidar measurements is available. Clouds are detected based on a combination of criteria including the magnitude of the normalized lidar signal and time-space edge detection performed using the Sobel operator. In this way the algorithm avoids misclassification of strong aerosol layers as clouds. Cloud detection is performed using the highest available time and vertical resolution of the lidar signals, allowing the effective detection of low-level clouds (e.g. cumulus humilis). Special attention is given to suppress false cloud detection due to signal noise that can affect the algorithm's performance, especially during day-time. In this contribution we present the details of algorithm, the effect of lidar characteristics (space-time resolution, available wavelengths, signal-to-noise ratio) to detection performance, and highlight the current strengths and limitations of the algorithm using lidar scenes from different lidar systems in different locations across Europe.

Fast, multi-channel real-time processing of signals with microsecond latency using graphics processing units.

PubMed

Rath, N; Kato, S; Levesque, J P; Mauel, M E; Navratil, G A; Peng, Q

2014-04-01

Fast, digital signal processing (DSP) has many applications. Typical hardware options for performing DSP are field-programmable gate arrays (FPGAs), application-specific integrated DSP chips, or general purpose personal computer systems. This paper presents a novel DSP platform that has been developed for feedback control on the HBT-EP tokamak device. The system runs all signal processing exclusively on a Graphics Processing Unit (GPU) to achieve real-time performance with latencies below 8 μs. Signals are transferred into and out of the GPU using PCI Express peer-to-peer direct-memory-access transfers without involvement of the central processing unit or host memory. Tests were performed on the feedback control system of the HBT-EP tokamak using forty 16-bit floating point inputs and outputs each and a sampling rate of up to 250 kHz. Signals were digitized by a D-TACQ ACQ196 module, processing done on an NVIDIA GTX 580 GPU programmed in CUDA, and analog output was generated by D-TACQ AO32CPCI modules.

Signal processor for processing ultrasonic receiver signals

DOEpatents

Fasching, George E.

1980-01-01

A signal processor is provided which uses an analog integrating circuit in conjunction with a set of digital counters controlled by a precision clock for sampling timing to provide an improved presentation of an ultrasonic transmitter/receiver signal. The signal is sampled relative to the transmitter trigger signal timing at precise times, the selected number of samples are integrated and the integrated samples are transferred and held for recording on a strip chart recorder or converted to digital form for storage. By integrating multiple samples taken at precisely the same time with respect to the trigger for the ultrasonic transmitter, random noise, which is contained in the ultrasonic receiver signal, is reduced relative to the desired useful signal.

Modeling aging effects on two-choice tasks: response signal and response time data.

PubMed

Ratcliff, Roger

2008-12-01

In the response signal paradigm, a test stimulus is presented, and then at one of a number of experimenter-determined times, a signal to respond is presented. Response signal, standard response time (RT), and accuracy data were collected from 19 college-age and 19 60- to 75-year-old participants in a numerosity discrimination task. The data were fit with 2 versions of the diffusion model. Response signal data were modeled by assuming a mixture of processes, those that have terminated before the signal and those that have not terminated; in the latter case, decisions are based on either partial information or guessing. The effects of aging on performance in the regular RT task were explained the same way in the models, with a 70- to 100-ms increase in the nondecision component of processing, more conservative decision criteria, and more variability across trials in drift and the nondecision component of processing, but little difference in drift rate (evidence). In the response signal task, the primary reason for a slower rise in the response signal functions for older participants was variability in the nondecision component of processing. Overall, the results were consistent with earlier fits of the diffusion model to the standard RT task for college-age participants and to the data from aging studies using this task in the standard RT procedure. Copyright (c) 2009 APA, all rights reserved.

Modeling Aging Effects on Two-Choice Tasks: Response Signal and Response Time Data

PubMed Central

Ratcliff, Roger

2009-01-01

In the response signal paradigm, a test stimulus is presented, and then at one of a number of experimenter-determined times, a signal to respond is presented. Response signal, standard response time (RT), and accuracy data were collected from 19 college-age and 19 60- to 75-year-old participants in a numerosity discrimination task. The data were fit with 2 versions of the diffusion model. Response signal data were modeled by assuming a mixture of processes, those that have terminated before the signal and those that have not terminated; in the latter case, decisions are based on either partial information or guessing. The effects of aging on performance in the regular RT task were explained the same way in the models, with a 70- to 100-ms increase in the nondecision component of processing, more conservative decision criteria, and more variability across trials in drift and the nondecision component of processing, but little difference in drift rate (evidence). In the response signal task, the primary reason for a slower rise in the response signal functions for older participants was variability in the nondecision component of processing. Overall, the results were consistent with earlier fits of the diffusion model to the standard RT task for college-age participants and to the data from aging studies using this task in the standard RT procedure. PMID:19140659

A real time ECG signal processing application for arrhythmia detection on portable devices

NASA Astrophysics Data System (ADS)

Georganis, A.; Doulgeraki, N.; Asvestas, P.

2017-11-01

Arrhythmia describes the disorders of normal heart rate, which, depending on the case, can even be fatal for a patient with severe history of heart disease. The purpose of this work is to develop an application for heart signal visualization, processing and analysis in Android portable devices e.g. Mobile phones, tablets, etc. The application is able to retrieve the signal initially from a file and at a later stage this signal is processed and analysed within the device so that it can be classified according to the features of the arrhythmia. In the processing and analysing stage, different algorithms are included among them the Moving Average and Pan Tompkins algorithm as well as the use of wavelets, in order to extract features and characteristics. At the final stage, testing is performed by simulating our application in real-time records, using the TCP network protocol for communicating the mobile with a simulated signal source. The classification of ECG beat to be processed is performed by neural networks.

Wigner-Ville distribution and Gabor transform in Doppler ultrasound signal processing.

PubMed

Ghofrani, S; Ayatollahi, A; Shamsollahi, M B

2003-01-01

Time-frequency distributions have been used extensively for nonstationary signal analysis, they describe how the frequency content of a signal is changing in time. The Wigner-Ville distribution (WVD) is the best known. The draw back of WVD is cross-term artifacts. An alternative to the WVD is Gabor transform (GT), a signal decomposition method, which displays the time-frequency energy of a signal on a joint t-f plane without generating considerable cross-terms. In this paper the WVD and GT of ultrasound echo signals are computed analytically.

Optical signal processing of spatially distributed sensor data in smart structures

NASA Technical Reports Server (NTRS)

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

1989-01-01

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

Verification of Non-Invasive Blood Glucose Measurement Method Based on Pulse Wave Signal Detected by FBG Sensor System.

PubMed

Kurasawa, Shintaro; Koyama, Shouhei; Ishizawa, Hiroaki; Fujimoto, Keisaku; Chino, Shun

2017-11-23

This paper describes and verifies a non-invasive blood glucose measurement method using a fiber Bragg grating (FBG) sensor system. The FBG sensor is installed on the radial artery, and the strain (pulse wave) that is propagated from the heartbeat is measured. The measured pulse wave signal was used as a collection of feature vectors for multivariate analysis aiming to determine the blood glucose level. The time axis of the pulse wave signal was normalized by two signal processing methods: the shortest-time-cut process and 1-s-normalization process. The measurement accuracy of the calculated blood glucose level was compared with the accuracy of these signal processing methods. It was impossible to calculate a blood glucose level exceeding 200 mg/dL in the calibration curve that was constructed by the shortest-time-cut process. In the 1-s-normalization process, the measurement accuracy of the blood glucose level was improved, and a blood glucose level exceeding 200 mg/dL could be calculated. By verifying the loading vector of each calibration curve to calculate the blood glucose level with a high measurement accuracy, we found the gradient of the peak of the pulse wave at the acceleration plethysmogram greatly affected.

Real-time holographic surveillance system

DOEpatents

Collins, H. Dale; McMakin, Douglas L.; Hall, Thomas E.; Gribble, R. Parks

1995-01-01

A holographic surveillance system including means for generating electromagnetic waves; means for transmitting the electromagnetic waves toward a target at a plurality of predetermined positions in space; means for receiving and converting electromagnetic waves reflected from the target to electrical signals at a plurality of predetermined positions in space; means for processing the electrical signals to obtain signals corresponding to a holographic reconstruction of the target; and means for displaying the processed information to determine nature of the target. The means for processing the electrical signals includes means for converting analog signals to digital signals followed by a computer means to apply a backward wave algorithm.

Acoustic Signal Processing in Photorefractive Optical Systems.

NASA Astrophysics Data System (ADS)

Zhou, Gan

This thesis discusses applications of the photorefractive effect in the context of acoustic signal processing. The devices and systems presented here illustrate the ideas and optical principles involved in holographic processing of acoustic information. The interest in optical processing stems from the similarities between holographic optical systems and contemporary models for massively parallel computation, in particular, neural networks. An initial step in acoustic processing is the transformation of acoustic signals into relevant optical forms. A fiber-optic transducer with photorefractive readout transforms acoustic signals into optical images corresponding to their short-time spectrum. The device analyzes complex sound signals and interfaces them with conventional optical correlators. The transducer consists of 130 multimode optical fibers sampling the spectral range of 100 Hz to 5 kHz logarithmically. A physical model of the human cochlea can help us understand some characteristics of human acoustic transduction and signal representation. We construct a life-sized cochlear model using elastic membranes coupled with two fluid-filled chambers, and use a photorefractive novelty filter to investigate its response. The detection sensitivity is determined to be 0.3 angstroms per root Hz at 2 kHz. Qualitative agreement is found between the model response and physiological data. Delay lines map time-domain signals into space -domain and permit holographic processing of temporal information. A parallel optical delay line using dynamic beam coupling in a rotating photorefractive crystal is presented. We experimentally demonstrate a 64 channel device with 0.5 seconds of time-delay and 167 Hz bandwidth. Acoustic signal recognition is described in a photorefractive system implementing the time-delay neural network model. The system consists of a photorefractive optical delay-line and a holographic correlator programmed in a LiNbO_3 crystal. We demonstrate the recognition of synthesized chirps as well as spoken words. A photorefractive ring resonator containing an optical delay line can learn temporal information through self-organization. We experimentally investigate a system that learns by itself and picks out the most-frequently -presented signals from the input. We also give results demonstrating the separation of two orthogonal temporal signals into two competing ring resonators.

Implementation and optimization of ultrasound signal processing algorithms on mobile GPU

NASA Astrophysics Data System (ADS)

Kong, Woo Kyu; Lee, Wooyoul; Kim, Kyu Cheol; Yoo, Yangmo; Song, Tai-Kyong

2014-03-01

A general-purpose graphics processing unit (GPGPU) has been used for improving computing power in medical ultrasound imaging systems. Recently, a mobile GPU becomes powerful to deal with 3D games and videos at high frame rates on Full HD or HD resolution displays. This paper proposes the method to implement ultrasound signal processing on a mobile GPU available in the high-end smartphone (Galaxy S4, Samsung Electronics, Seoul, Korea) with programmable shaders on the OpenGL ES 2.0 platform. To maximize the performance of the mobile GPU, the optimization of shader design and load sharing between vertex and fragment shader was performed. The beamformed data were captured from a tissue mimicking phantom (Model 539 Multipurpose Phantom, ATS Laboratories, Inc., Bridgeport, CT, USA) by using a commercial ultrasound imaging system equipped with a research package (Ultrasonix Touch, Ultrasonix, Richmond, BC, Canada). The real-time performance is evaluated by frame rates while varying the range of signal processing blocks. The implementation method of ultrasound signal processing on OpenGL ES 2.0 was verified by analyzing PSNR with MATLAB gold standard that has the same signal path. CNR was also analyzed to verify the method. From the evaluations, the proposed mobile GPU-based processing method has no significant difference with the processing using MATLAB (i.e., PSNR<52.51 dB). The comparable results of CNR were obtained from both processing methods (i.e., 11.31). From the mobile GPU implementation, the frame rates of 57.6 Hz were achieved. The total execution time was 17.4 ms that was faster than the acquisition time (i.e., 34.4 ms). These results indicate that the mobile GPU-based processing method can support real-time ultrasound B-mode processing on the smartphone.

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.

High-resolution correlation

NASA Astrophysics Data System (ADS)

Nelson, D. J.

2007-09-01

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

Parallel optimization of signal detection in active magnetospheric signal injection experiments

NASA Astrophysics Data System (ADS)

Gowanlock, Michael; Li, Justin D.; Rude, Cody M.; Pankratius, Victor

2018-05-01

Signal detection and extraction requires substantial manual parameter tuning at different stages in the processing pipeline. Time-series data depends on domain-specific signal properties, necessitating unique parameter selection for a given problem. The large potential search space makes this parameter selection process time-consuming and subject to variability. We introduce a technique to search and prune such parameter search spaces in parallel and select parameters for time series filters using breadth- and depth-first search strategies to increase the likelihood of detecting signals of interest in the field of magnetospheric physics. We focus on studying geomagnetic activity in the extremely and very low frequency ranges (ELF/VLF) using ELF/VLF transmissions from Siple Station, Antarctica, received at Québec, Canada. Our technique successfully detects amplified transmissions and achieves substantial speedup performance gains as compared to an exhaustive parameter search. We present examples where our algorithmic approach reduces the search from hundreds of seconds down to less than 1 s, with a ranked signal detection in the top 99th percentile, thus making it valuable for real-time monitoring. We also present empirical performance models quantifying the trade-off between the quality of signal recovered and the algorithm response time required for signal extraction. In the future, improved signal extraction in scenarios like the Siple experiment will enable better real-time diagnostics of conditions of the Earth's magnetosphere for monitoring space weather activity.

Digital signal processing in the radio science stability analyzer

NASA Technical Reports Server (NTRS)

Greenhall, C. A.

1995-01-01

The Telecommunications Division has built a stability analyzer for testing Deep Space Network installations during flight radio science experiments. The low-frequency part of the analyzer operates by digitizing wave signals with bandwidths between 80 Hz and 45 kHz. Processed outputs include spectra of signal, phase, amplitude, and differential phase; time series of the same quantities; and Allan deviation of phase and differential phase. This article documents the digital signal-processing methods programmed into the analyzer.

Frequency-feature based antistrong-disturbance signal processing method and system for vortex flowmeter with single sensor

NASA Astrophysics Data System (ADS)

Xu, Ke-Jun; Luo, Qing-Lin; Wang, Gang; Liu, San-Shan; Kang, Yi-Bo

2010-07-01

Digital signal processing methods have been applied to vortex flowmeter for extracting the useful information from noisy output of the vortex flow sensor. But these approaches are unavailable when the power of the mechanical vibration noise is larger than that of the vortex flow signal. In order to solve this problem, an antistrong-disturbance signal processing method is proposed based on frequency features of the vortex flow signal and mechanical vibration noise for the vortex flowmeter with single sensor. The frequency bandwidth of the vortex flow signal is different from that of the mechanical vibration noise. The autocorrelation function can represent bandwidth features of the signal and noise. The output of the vortex flow sensor is processed by the spectrum analysis, filtered by bandpass filters, and calculated by autocorrelation function at the fixed delaying time and at τ =0 to obtain ratios. The frequency corresponding to the minimal ratio is regarded as the vortex flow frequency. With an ultralow-power microcontroller, a digital signal processing system is developed to implement the antistrong-disturbance algorithm, and at the same time to ensure low-power and two-wire mode for meeting the requirement of process instrumentation. The water flow-rate calibration and vibration test experiments are conducted, and the experimental results show that both the algorithm and system are effective.

Frequency-feature based antistrong-disturbance signal processing method and system for vortex flowmeter with single sensor.

PubMed

Xu, Ke-Jun; Luo, Qing-Lin; Wang, Gang; Liu, San-Shan; Kang, Yi-Bo

2010-07-01

Digital signal processing methods have been applied to vortex flowmeter for extracting the useful information from noisy output of the vortex flow sensor. But these approaches are unavailable when the power of the mechanical vibration noise is larger than that of the vortex flow signal. In order to solve this problem, an antistrong-disturbance signal processing method is proposed based on frequency features of the vortex flow signal and mechanical vibration noise for the vortex flowmeter with single sensor. The frequency bandwidth of the vortex flow signal is different from that of the mechanical vibration noise. The autocorrelation function can represent bandwidth features of the signal and noise. The output of the vortex flow sensor is processed by the spectrum analysis, filtered by bandpass filters, and calculated by autocorrelation function at the fixed delaying time and at tau=0 to obtain ratios. The frequency corresponding to the minimal ratio is regarded as the vortex flow frequency. With an ultralow-power microcontroller, a digital signal processing system is developed to implement the antistrong-disturbance algorithm, and at the same time to ensure low-power and two-wire mode for meeting the requirement of process instrumentation. The water flow-rate calibration and vibration test experiments are conducted, and the experimental results show that both the algorithm and system are effective.

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

NASA Astrophysics Data System (ADS)

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

2005-05-01

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

Noise-assisted data processing with empirical mode decomposition in biomedical signals.

PubMed

Karagiannis, Alexandros; Constantinou, Philip

2011-01-01

In this paper, a methodology is described in order to investigate the performance of empirical mode decomposition (EMD) in biomedical signals, and especially in the case of electrocardiogram (ECG). Synthetic ECG signals corrupted with white Gaussian noise are employed and time series of various lengths are processed with EMD in order to extract the intrinsic mode functions (IMFs). A statistical significance test is implemented for the identification of IMFs with high-level noise components and their exclusion from denoising procedures. Simulation campaign results reveal that a decrease of processing time is accomplished with the introduction of preprocessing stage, prior to the application of EMD in biomedical time series. Furthermore, the variation in the number of IMFs according to the type of the preprocessing stage is studied as a function of SNR and time-series length. The application of the methodology in MIT-BIH ECG records is also presented in order to verify the findings in real ECG signals.

Massively Parallel Signal Processing using the Graphics Processing Unit for Real-Time Brain-Computer Interface Feature Extraction.

PubMed

Wilson, J Adam; Williams, Justin C

2009-01-01

The clock speeds of modern computer processors have nearly plateaued in the past 5 years. Consequently, neural prosthetic systems that rely on processing large quantities of data in a short period of time face a bottleneck, in that it may not be possible to process all of the data recorded from an electrode array with high channel counts and bandwidth, such as electrocorticographic grids or other implantable systems. Therefore, in this study a method of using the processing capabilities of a graphics card [graphics processing unit (GPU)] was developed for real-time neural signal processing of a brain-computer interface (BCI). The NVIDIA CUDA system was used to offload processing to the GPU, which is capable of running many operations in parallel, potentially greatly increasing the speed of existing algorithms. The BCI system records many channels of data, which are processed and translated into a control signal, such as the movement of a computer cursor. This signal processing chain involves computing a matrix-matrix multiplication (i.e., a spatial filter), followed by calculating the power spectral density on every channel using an auto-regressive method, and finally classifying appropriate features for control. In this study, the first two computationally intensive steps were implemented on the GPU, and the speed was compared to both the current implementation and a central processing unit-based implementation that uses multi-threading. Significant performance gains were obtained with GPU processing: the current implementation processed 1000 channels of 250 ms in 933 ms, while the new GPU method took only 27 ms, an improvement of nearly 35 times.

Design of an FMCW radar baseband signal processing system for automotive application.

PubMed

Lin, Jau-Jr; Li, Yuan-Ping; Hsu, Wei-Chiang; Lee, Ta-Sung

2016-01-01

For a typical FMCW automotive radar system, a new design of baseband signal processing architecture and algorithms is proposed to overcome the ghost targets and overlapping problems in the multi-target detection scenario. To satisfy the short measurement time constraint without increasing the RF front-end loading, a three-segment waveform with different slopes is utilized. By introducing a new pairing mechanism and a spatial filter design algorithm, the proposed detection architecture not only provides high accuracy and reliability, but also requires low pairing time and computational loading. This proposed baseband signal processing architecture and algorithms balance the performance and complexity, and are suitable to be implemented in a real automotive radar system. Field measurement results demonstrate that the proposed automotive radar signal processing system can perform well in a realistic application scenario.

Fractal Signals & Space-Time Cartoons

NASA Astrophysics Data System (ADS)

Oetama, H. C. Jakob; Maksoed, W. H.

2016-03-01

In ``Theory of Scale Relativity'', 1991- L. Nottale states whereas ``scale relativity is a geometrical & fractal space-time theory''. It took in comparisons to ``a unified, wavelet based framework for efficiently synthetizing, analyzing ∖7 processing several broad classes of fractal signals''-Gregory W. Wornell:``Signal Processing with Fractals'', 1995. Furthers, in Fig 1.1. a simple waveform from statistically scale-invariant random process [ibid.,h 3 ]. Accompanying RLE Technical Report 566 ``Synthesis, Analysis & Processing of Fractal Signals'' as well as from Wornell, Oct 1991 herewith intended to deducts =a Δt + (1 - β Δ t) ...in Petersen, et.al: ``Scale invariant properties of public debt growth'',2010 h. 38006p2 to [1/{1- (2 α (λ) /3 π) ln (λ/r)}depicts in Laurent Nottale,1991, h 24. Acknowledgment devotes to theLates HE. Mr. BrigadierGeneral-TNI[rtd].Prof. Ir. HANDOJO.

Application of Mathematical Signal Processing Techniques to Mission Systems. (l’Application des techniques mathematiques du traitement du signal aux systemes de conduite des missions)

DTIC Science & Technology

1999-11-01

represents the linear time invariant (LTI) response of the combined analysis /synthesis system while the second repre- sents the aliasing introduced into...effectively to implement voice scrambling systems based on time - frequency permutation . The most general form of such a system is shown in Fig. 22 where...92201 NEUILLY-SUR-SEINE CEDEX, FRANCE RTO LECTURE SERIES 216 Application of Mathematical Signal Processing Techniques to Mission Systems (1

SPROC: A multiple-processor DSP IC

NASA Technical Reports Server (NTRS)

Davis, R.

1991-01-01

A large, single-chip, multiple-processor, digital signal processing (DSP) integrated circuit (IC) fabricated in HP-Cmos34 is presented. The innovative architecture is best suited for analog and real-time systems characterized by both parallel signal data flows and concurrent logic processing. The IC is supported by a powerful development system that transforms graphical signal flow graphs into production-ready systems in minutes. Automatic compiler partitioning of tasks among four on-chip processors gives the IC the signal processing power of several conventional DSP chips.

Frequency domain laser velocimeter signal processor: A new signal processing scheme

NASA Technical Reports Server (NTRS)

Meyers, James F.; Clemmons, James I., Jr.

1987-01-01

A new scheme for processing signals from laser velocimeter systems is described. The technique utilizes the capabilities of advanced digital electronics to yield a smart instrument that is able to configure itself, based on the characteristics of the input signals, for optimum measurement accuracy. The signal processor is composed of a high-speed 2-bit transient recorder for signal capture and a combination of adaptive digital filters with energy and/or zero crossing detection signal processing. The system is designed to accept signals with frequencies up to 100 MHz with standard deviations up to 20 percent of the average signal frequency. Results from comparative simulation studies indicate measurement accuracies 2.5 times better than with a high-speed burst counter, from signals with as few as 150 photons per burst.

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

This algorithm processes high-rate 3-phase signals to identify the start time of each signal and estimate its envelope as data features. The start time and magnitude of each signal during the steady state is also extracted. The features can be used to detect abnormal signals. This algorithm is developed to analyze Exxeno's 3-phase voltage and current data recorded from refrigeration systems to detect device failure or degradation.

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.

Visualizing time: how linguistic metaphors are incorporated into displaying instruments in the process of interpreting time-varying signals

NASA Astrophysics Data System (ADS)

Garcia-Belmonte, Germà

2017-06-01

Spatial visualization is a well-established topic of education research that has allowed improving science and engineering students' skills on spatial relations. Connections have been established between visualization as a comprehension tool and instruction in several scientific fields. Learning about dynamic processes mainly relies upon static spatial representations or images. Visualization of time is inherently problematic because time can be conceptualized in terms of two opposite conceptual metaphors based on spatial relations as inferred from conventional linguistic patterns. The situation is particularly demanding when time-varying signals are recorded using displaying electronic instruments, and the image should be properly interpreted. This work deals with the interplay between linguistic metaphors, visual thinking and scientific instrument mediation in the process of interpreting time-varying signals displayed by electronic instruments. The analysis draws on a simplified version of a communication system as example of practical signal recording and image visualization in a physics and engineering laboratory experience. Instrumentation delivers meaningful signal representations because it is designed to incorporate a specific and culturally favored time view. It is suggested that difficulties in interpreting time-varying signals are linked with the existing dual perception of conflicting time metaphors. The activation of specific space-time conceptual mapping might allow for a proper signal interpretation. Instruments play then a central role as visualization mediators by yielding an image that matches specific perception abilities and practical purposes. Here I have identified two ways of understanding time as used in different trajectories through which students are located. Interestingly specific displaying instruments belonging to different cultural traditions incorporate contrasting time views. One of them sees time in terms of a dynamic metaphor consisting of a static observer looking at passing events. This is a general and widespread practice common in the contemporary mass culture, which lies behind the process of making sense to moving images usually visualized by means of movie shots. In contrast scientific culture favored another way of time conceptualization (static time metaphor) that historically fostered the construction of graphs and the incorporation of time-dependent functions, as represented on the Cartesian plane, into displaying instruments. Both types of cultures, scientific and mass, are considered highly technological in the sense that complex instruments, apparatus or machines participate in their visual practices.

Frequency-time coherence for all-optical sampling without optical pulse source

PubMed Central

Preußler, Stefan; Raoof Mehrpoor, Gilda; Schneider, Thomas

2016-01-01

Sampling is the first step to convert an analogue optical signal into a digital electrical signal. The latter can be further processed and analysed by well-known electrical signal processing methods. Optical pulse sources like mode-locked lasers are commonly incorporated for all-optical sampling, but have several drawbacks. A novel approach for a simple all-optical sampling is to utilise the frequency-time coherence of each signal. The method is based on only using two coupled modulators driven with an electrical sine wave. Since no optical source is required, a simple integration in appropriate platforms, such as Silicon Photonics might be possible. The presented method grants all-optical sampling with electrically tunable bandwidth, repetition rate and time shift. PMID:27687495

Real time automatic detection of bearing fault in induction machine using kurtogram analysis.

PubMed

Tafinine, Farid; Mokrani, Karim

2012-11-01

A proposed signal processing technique for incipient real time bearing fault detection based on kurtogram analysis is presented in this paper. The kurtogram is a fourth-order spectral analysis tool introduced for detecting and characterizing non-stationarities in a signal. This technique starts from investigating the resonance signatures over selected frequency bands to extract the representative features. The traditional spectral analysis is not appropriate for non-stationary vibration signal and for real time diagnosis. The performance of the proposed technique is examined by a series of experimental tests corresponding to different bearing conditions. Test results show that this signal processing technique is an effective bearing fault automatic detection method and gives a good basis for an integrated induction machine condition monitor.

Separation of Intercepted Multi-Radar Signals Based on Parameterized Time-Frequency Analysis

NASA Astrophysics Data System (ADS)

Lu, W. L.; Xie, J. W.; Wang, H. M.; Sheng, C.

2016-09-01

Modern radars use complex waveforms to obtain high detection performance and low probabilities of interception and identification. Signals intercepted from multiple radars overlap considerably in both the time and frequency domains and are difficult to separate with primary time parameters. Time-frequency analysis (TFA), as a key signal-processing tool, can provide better insight into the signal than conventional methods. In particular, among the various types of TFA, parameterized time-frequency analysis (PTFA) has shown great potential to investigate the time-frequency features of such non-stationary signals. In this paper, we propose a procedure for PTFA to separate overlapped radar signals; it includes five steps: initiation, parameterized time-frequency analysis, demodulating the signal of interest, adaptive filtering and recovering the signal. The effectiveness of the method was verified with simulated data and an intercepted radar signal received in a microwave laboratory. The results show that the proposed method has good performance and has potential in electronic reconnaissance applications, such as electronic intelligence, electronic warfare support measures, and radar warning.

Demodulation processes in auditory perception

NASA Astrophysics Data System (ADS)

Feth, Lawrence L.

1994-08-01

The long range goal of this project is the understanding of human auditory processing of information conveyed by complex, time-varying signals such as speech, music or important environmental sounds. Our work is guided by the assumption that human auditory communication is a 'modulation - demodulation' process. That is, we assume that sound sources produce a complex stream of sound pressure waves with information encoded as variations ( modulations) of the signal amplitude and frequency. The listeners task then is one of demodulation. Much of past. psychoacoustics work has been based in what we characterize as 'spectrum picture processing.' Complex sounds are Fourier analyzed to produce an amplitude-by-frequency 'picture' and the perception process is modeled as if the listener were analyzing the spectral picture. This approach leads to studies such as 'profile analysis' and the power-spectrum model of masking. Our approach leads us to investigate time-varying, complex sounds. We refer to them as dynamic signals and we have developed auditory signal processing models to help guide our experimental work.

Real-time holographic surveillance system

DOEpatents

Collins, H.D.; McMakin, D.L.; Hall, T.E.; Gribble, R.P.

1995-10-03

A holographic surveillance system is disclosed including means for generating electromagnetic waves; means for transmitting the electromagnetic waves toward a target at a plurality of predetermined positions in space; means for receiving and converting electromagnetic waves reflected from the target to electrical signals at a plurality of predetermined positions in space; means for processing the electrical signals to obtain signals corresponding to a holographic reconstruction of the target; and means for displaying the processed information to determine nature of the target. The means for processing the electrical signals includes means for converting analog signals to digital signals followed by a computer means to apply a backward wave algorithm. 21 figs.

Digital communications study

NASA Technical Reports Server (NTRS)

Boorstyn, R. R.

1973-01-01

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

System for monitoring non-coincident, nonstationary process signals

DOEpatents

Gross, Kenneth C.; Wegerich, Stephan W.

2005-01-04

An improved system for monitoring non-coincident, non-stationary, process signals. The mean, variance, and length of a reference signal is defined by an automated system, followed by the identification of the leading and falling edges of a monitored signal and the length of the monitored signal. The monitored signal is compared to the reference signal, and the monitored signal is resampled in accordance with the reference signal. The reference signal is then correlated with the resampled monitored signal such that the reference signal and the resampled monitored signal are coincident in time with each other. The resampled monitored signal is then compared to the reference signal to determine whether the resampled monitored signal is within a set of predesignated operating conditions.

Time Reversal Mirrors and Cross Correlation Functions in Acoustic Wave Propagation

NASA Astrophysics Data System (ADS)

Fishman, Louis; Jonsson, B. Lars G.; de Hoop, Maarten V.

2009-03-01

In time reversal acoustics (TRA), a signal is recorded by an array of transducers, time reversed, and then retransmitted into the configuration. The retransmitted signal propagates back through the same medium and retrofocuses on the source that generated the signal. If the transducer array is a single, planar (flat) surface, then this configuration is referred to as a planar, one-sided, time reversal mirror (TRM). In signal processing, for example, in active-source seismic interferometry, the measurement of the wave field at two distinct receivers, generated by a common source, is considered. Cross correlating these two observations and integrating the result over the sources yield the cross correlation function (CCF). Adopting the TRM experiments as the basic starting point and identifying the kinematically correct correspondences, it is established that the associated CCF signal processing constructions follow in a specific, infinite recording time limit. This perspective also provides for a natural rationale for selecting the Green's function components in the TRM and CCF expressions. For a planar, one-sided, TRM experiment and the corresponding CCF signal processing construction, in a three-dimensional homogeneous medium, the exact expressions are explicitly calculated, and the connecting limiting relationship verified. Finally, the TRM and CCF results are understood in terms of the underlying, governing, two-way wave equation, its corresponding time reversal invariance (TRI) symmetry, and the absence of TRI symmetry in the associated one-way wave equations, highlighting the role played by the evanescent modal contributions.

New instantaneous frequency estimation method based on the use of image processing techniques

NASA Astrophysics Data System (ADS)

Borda, Monica; Nafornita, Ioan; Isar, Alexandru

2003-05-01

The aim of this paper is to present a new method for the estimation of the instantaneous frequency of a frequency modulated signal, corrupted by additive noise. This method represents an example of fusion of two theories: the time-frequency representations and the mathematical morphology. Any time-frequency representation of a useful signal is concentrated around its instantaneous frequency law and realizes the diffusion of the noise that perturbs the useful signal in the time - frequency plane. In this paper a new time-frequency representation, useful for the estimation of the instantaneous frequency, is proposed. This time-frequency representation is the product of two others time-frequency representations: the Wigner - Ville time-frequency representation and a new one obtained by filtering with a hard thresholding filter the Gabor representation of the signal to be processed. Using the image of this new time-frequency representation the instantaneous frequency of the useful signal can be extracted with the aid of some mathematical morphology operators: the conversion in binary form, the dilation and the skeleton. The simulations of the proposed method have proved its qualities. It is better than other estimation methods, like those based on the use of adaptive notch filters.

A Resume of Stochastic, Time-Varying, Linear System Theory with Application to Active-Sonar Signal-Processing Problems

DTIC Science & Technology

1981-06-15

relationships 5 3. Normalized energy in ambiguity function for i = 0 14 k ilI SACLANTCEN SR-50 A RESUME OF STOCHASTIC, TIME-VARYING, LINEAR SYSTEM THEORY WITH...the order in which systems are concatenated is unimportant. These results are exactly analogous to the results of time-invariant linear system theory in...REFERENCES 1. MEIER, L. A rdsum6 of deterministic time-varying linear system theory with application to active sonar signal processing problems, SACLANTCEN

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.

Research on signal processing method for total organic carbon of water quality online monitor

NASA Astrophysics Data System (ADS)

Ma, R.; Xie, Z. X.; Chu, D. Z.; Zhang, S. W.; Cao, X.; Wu, N.

2017-08-01

At present, there is no rapid, stable and effective approach of total organic carbon (TOC) measurement in the Marine environmental online monitoring field. Therefore, this paper proposes an online TOC monitor of chemiluminescence signal processing method. The weak optical signal detected by photomultiplier tube can be enhanced and converted by a series of signal processing module: phase-locked amplifier module, fourth-order band pass filter module and AD conversion module. After a long time of comparison test & measurement, compared with the traditional method, on the premise of sufficient accuracy, this chemiluminescence signal processing method can offer greatly improved measuring speed and high practicability for online monitoring.

Analysis of cutting force signals by wavelet packet transform for surface roughness monitoring in CNC turning

NASA Astrophysics Data System (ADS)

García Plaza, E.; Núñez López, P. J.

2018-01-01

On-line monitoring of surface finish in machining processes has proven to be a substantial advancement over traditional post-process quality control techniques by reducing inspection times and costs and by avoiding the manufacture of defective products. This study applied techniques for processing cutting force signals based on the wavelet packet transform (WPT) method for the monitoring of surface finish in computer numerical control (CNC) turning operations. The behaviour of 40 mother wavelets was analysed using three techniques: global packet analysis (G-WPT), and the application of two packet reduction criteria: maximum energy (E-WPT) and maximum entropy (SE-WPT). The optimum signal decomposition level (Lj) was determined to eliminate noise and to obtain information correlated to surface finish. The results obtained with the G-WPT method provided an in-depth analysis of cutting force signals, and frequency ranges and signal characteristics were correlated to surface finish with excellent results in the accuracy and reliability of the predictive models. The radial and tangential cutting force components at low frequency provided most of the information for the monitoring of surface finish. The E-WPT and SE-WPT packet reduction criteria substantially reduced signal processing time, but at the expense of discarding packets with relevant information, which impoverished the results. The G-WPT method was observed to be an ideal procedure for processing cutting force signals applied to the real-time monitoring of surface finish, and was estimated to be highly accurate and reliable at a low analytical-computational cost.

Automated infrasound signal detection algorithms implemented in MatSeis - Infra Tool.

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

Hart, Darren

2004-07-01

MatSeis's infrasound analysis tool, Infra Tool, uses frequency slowness processing to deconstruct the array data into three outputs per processing step: correlation, azimuth and slowness. Until now, an experienced analyst trained to recognize a pattern observed in outputs from signal processing manually accomplished infrasound signal detection. Our goal was to automate the process of infrasound signal detection. The critical aspect of infrasound signal detection is to identify consecutive processing steps where the azimuth is constant (flat) while the time-lag correlation of the windowed waveform is above background value. These two statements describe the arrival of a correlated set of wavefrontsmore » at an array. The Hough Transform and Inverse Slope methods are used to determine the representative slope for a specified number of azimuth data points. The representative slope is then used in conjunction with associated correlation value and azimuth data variance to determine if and when an infrasound signal was detected. A format for an infrasound signal detection output file is also proposed. The detection output file will list the processed array element names, followed by detection characteristics for each method. Each detection is supplied with a listing of frequency slowness processing characteristics: human time (YYYY/MM/DD HH:MM:SS.SSS), epochal time, correlation, fstat, azimuth (deg) and trace velocity (km/s). As an example, a ground truth event was processed using the four-element DLIAR infrasound array located in New Mexico. The event is known as the Watusi chemical explosion, which occurred on 2002/09/28 at 21:25:17 with an explosive yield of 38,000 lb TNT equivalent. Knowing the source and array location, the array-to-event distance was computed to be approximately 890 km. This test determined the station-to-event azimuth (281.8 and 282.1 degrees) to within 1.6 and 1.4 degrees for the Inverse Slope and Hough Transform detection algorithms, respectively, and the detection window closely correlated to the theoretical stratospheric arrival time. Further testing will be required for tuning of detection threshold parameters for different types of infrasound events.« less

A microcomputer based frequency-domain processor for laser Doppler anemometry

NASA Technical Reports Server (NTRS)

Horne, W. Clifton; Adair, Desmond

1988-01-01

A prototype multi-channel laser Doppler anemometry (LDA) processor was assembled using a wideband transient recorder and a microcomputer with an array processor for fast Fourier transform (FFT) computations. The prototype instrument was used to acquire, process, and record signals from a three-component wind tunnel LDA system subject to various conditions of noise and flow turbulence. The recorded data was used to evaluate the effectiveness of burst acceptance criteria, processing algorithms, and selection of processing parameters such as record length. The recorded signals were also used to obtain comparative estimates of signal-to-noise ratio between time-domain and frequency-domain signal detection schemes. These comparisons show that the FFT processing scheme allows accurate processing of signals for which the signal-to-noise ratio is 10 to 15 dB less than is practical using counter processors.

Investigation of FPGA-Based Real-Time Adaptive Digital Pulse Shaping for High-Count-Rate Applications

NASA Astrophysics Data System (ADS)

Saxena, Shefali; Hawari, Ayman I.

2017-07-01

Digital signal processing techniques have been widely used in radiation spectrometry to provide improved stability and performance with compact physical size over the traditional analog signal processing. In this paper, field-programmable gate array (FPGA)-based adaptive digital pulse shaping techniques are investigated for real-time signal processing. National Instruments (NI) NI 5761 14-bit, 250-MS/s adaptor module is used for digitizing high-purity germanium (HPGe) detector's preamplifier pulses. Digital pulse processing algorithms are implemented on the NI PXIe-7975R reconfigurable FPGA (Kintex-7) using the LabVIEW FPGA module. Based on the time separation between successive input pulses, the adaptive shaping algorithm selects the optimum shaping parameters (rise time and flattop time of trapezoid-shaping filter) for each incoming signal. A digital Sallen-Key low-pass filter is implemented to enhance signal-to-noise ratio and reduce baseline drifting in trapezoid shaping. A recursive trapezoid-shaping filter algorithm is employed for pole-zero compensation of exponentially decayed (with two-decay constants) preamplifier pulses of an HPGe detector. It allows extraction of pulse height information at the beginning of each pulse, thereby reducing the pulse pileup and increasing throughput. The algorithms for RC-CR2 timing filter, baseline restoration, pile-up rejection, and pulse height determination are digitally implemented for radiation spectroscopy. Traditionally, at high-count-rate conditions, a shorter shaping time is preferred to achieve high throughput, which deteriorates energy resolution. In this paper, experimental results are presented for varying count-rate and pulse shaping conditions. Using adaptive shaping, increased throughput is accepted while preserving the energy resolution observed using the longer shaping times.

Stratigraphy of the Anthropocene.

PubMed

Zalasiewicz, Jan; Williams, Mark; Fortey, Richard; Smith, Alan; Barry, Tiffany L; Coe, Angela L; Bown, Paul R; Rawson, Peter F; Gale, Andrew; Gibbard, Philip; Gregory, F John; Hounslow, Mark W; Kerr, Andrew C; Pearson, Paul; Knox, Robert; Powell, John; Waters, Colin; Marshall, John; Oates, Michael; Stone, Philip

2011-03-13

The Anthropocene, an informal term used to signal the impact of collective human activity on biological, physical and chemical processes on the Earth system, is assessed using stratigraphic criteria. It is complex in time, space and process, and may be considered in terms of the scale, relative timing, duration and novelty of its various phenomena. The lithostratigraphic signal includes both direct components, such as urban constructions and man-made deposits, and indirect ones, such as sediment flux changes. Already widespread, these are producing a significant 'event layer', locally with considerable long-term preservation potential. Chemostratigraphic signals include new organic compounds, but are likely to be dominated by the effects of CO(2) release, particularly via acidification in the marine realm, and man-made radionuclides. The sequence stratigraphic signal is negligible to date, but may become geologically significant over centennial/millennial time scales. The rapidly growing biostratigraphic signal includes geologically novel aspects (the scale of globally transferred species) and geologically will have permanent effects.

Analysis of acoustic emission signals and monitoring of machining processes

PubMed

Govekar; Gradisek; Grabec

2000-03-01

Monitoring of a machining process on the basis of sensor signals requires a selection of informative inputs in order to reliably characterize and model the process. In this article, a system for selection of informative characteristics from signals of multiple sensors is presented. For signal analysis, methods of spectral analysis and methods of nonlinear time series analysis are used. With the aim of modeling relationships between signal characteristics and the corresponding process state, an adaptive empirical modeler is applied. The application of the system is demonstrated by characterization of different parameters defining the states of a turning machining process, such as: chip form, tool wear, and onset of chatter vibration. The results show that, in spite of the complexity of the turning process, the state of the process can be well characterized by just a few proper characteristics extracted from a representative sensor signal. The process characterization can be further improved by joining characteristics from multiple sensors and by application of chaotic characteristics.

Signal processing of anthropometric data

NASA Astrophysics Data System (ADS)

Zimmermann, W. J.

1983-09-01

The Anthropometric Measurements Laboratory has accumulated a large body of data from a number of previous experiments. The data is very noisy, therefore it requires the application of some signal processing schemes. Moreover, it was not regarded as time series measurements but as positional information; hence, the data is stored as coordinate points as defined by the motion of the human body. The accumulated data defines two groups or classes. Some of the data was collected from an experiment designed to measure the flexibility of the limbs, referred to as radial movement. The remaining data was collected from experiments designed to determine the surface of the reach envelope. An interactive signal processing package was designed and implemented. Since the data does not include time this package does not include a time series element. Presently the results is restricted to processing data obtained from those experiments designed to measure flexibility.

Signal processing of anthropometric data

NASA Technical Reports Server (NTRS)

Zimmermann, W. J.

1983-01-01

The Anthropometric Measurements Laboratory has accumulated a large body of data from a number of previous experiments. The data is very noisy, therefore it requires the application of some signal processing schemes. Moreover, it was not regarded as time series measurements but as positional information; hence, the data is stored as coordinate points as defined by the motion of the human body. The accumulated data defines two groups or classes. Some of the data was collected from an experiment designed to measure the flexibility of the limbs, referred to as radial movement. The remaining data was collected from experiments designed to determine the surface of the reach envelope. An interactive signal processing package was designed and implemented. Since the data does not include time this package does not include a time series element. Presently the results is restricted to processing data obtained from those experiments designed to measure flexibility.

Signal processing methodologies for an acoustic fetal heart rate monitor

NASA Technical Reports Server (NTRS)

Pretlow, Robert A., III; Stoughton, John W.

1992-01-01

Research and development is presented of real time signal processing methodologies for the detection of fetal heart tones within a noise-contaminated signal from a passive acoustic sensor. A linear predictor algorithm is utilized for detection of the heart tone event and additional processing derives heart rate. The linear predictor is adaptively 'trained' in a least mean square error sense on generic fetal heart tones recorded from patients. A real time monitor system is described which outputs to a strip chart recorder for plotting the time history of the fetal heart rate. The system is validated in the context of the fetal nonstress test. Comparisons are made with ultrasonic nonstress tests on a series of patients. Comparative data provides favorable indications of the feasibility of the acoustic monitor for clinical use.

Adaptation of vestibular signals for self-motion perception

PubMed Central

St George, Rebecca J; Day, Brian L; Fitzpatrick, Richard C

2011-01-01

A fundamental concern of the brain is to establish the spatial relationship between self and the world to allow purposeful action. Response adaptation to unvarying sensory stimuli is a common feature of neural processing, both peripherally and centrally. For the semicircular canals, peripheral adaptation of the canal-cupula system to constant angular-velocity stimuli dominates the picture and masks central adaptation. Here we ask whether galvanic vestibular stimulation circumvents peripheral adaptation and, if so, does it reveal central adaptive processes. Transmastoidal bipolar galvanic stimulation and platform rotation (20 deg s−1) were applied separately and held constant for 2 min while perceived rotation was measured by verbal report. During real rotation, the perception of turn decayed from the onset of constant velocity with a mean time constant of 15.8 s. During galvanic-evoked virtual rotation, the perception of rotation initially rose but then declined towards zero over a period of ∼100 s. For both stimuli, oppositely directed perceptions of similar amplitude were reported when stimulation ceased indicating signal adaptation at some level. From these data the time constants of three independent processes were estimated: (i) the peripheral canal-cupula adaptation with time constant 7.3 s, (ii) the central ‘velocity-storage’ process that extends the afferent signal with time constant 7.7 s, and (iii) a long-term adaptation with time constant 75.9 s. The first two agree with previous data based on constant-velocity stimuli. The third component decayed with the profile of a real constant angular acceleration stimulus, showing that the galvanic stimulus signal bypasses the peripheral transformation so that the brainstem sees the galvanic signal as angular acceleration. An adaptive process involving both peripheral and central processes is indicated. Signals evoked by most natural movements will decay peripherally before adaptation can exert an appreciable effect, making a specific vestibular behavioural role unlikely. This adaptation appears to be a general property of the internal coding of self-motion that receives information from multiple sensory sources and filters out the unvarying components regardless of their origin. In this instance of a pure vestibular sensation, it defines the afferent signal that represents the stationary or zero-rotation state. PMID:20937715

Digital signal processing algorithms for automatic voice recognition

NASA Technical Reports Server (NTRS)

Botros, Nazeih M.

1987-01-01

The current digital signal analysis algorithms are investigated that are implemented in automatic voice recognition algorithms. Automatic voice recognition means, the capability of a computer to recognize and interact with verbal commands. The digital signal is focused on, rather than the linguistic, analysis of speech signal. Several digital signal processing algorithms are available for voice recognition. Some of these algorithms are: Linear Predictive Coding (LPC), Short-time Fourier Analysis, and Cepstrum Analysis. Among these algorithms, the LPC is the most widely used. This algorithm has short execution time and do not require large memory storage. However, it has several limitations due to the assumptions used to develop it. The other 2 algorithms are frequency domain algorithms with not many assumptions, but they are not widely implemented or investigated. However, with the recent advances in the digital technology, namely signal processors, these 2 frequency domain algorithms may be investigated in order to implement them in voice recognition. This research is concerned with real time, microprocessor based recognition algorithms.

Generation of optical OFDM signals using 21.4 GS/s real time digital signal processing.

PubMed

Benlachtar, Yannis; Watts, Philip M; Bouziane, Rachid; Milder, Peter; Rangaraj, Deepak; Cartolano, Anthony; Koutsoyannis, Robert; Hoe, James C; Püschel, Markus; Glick, Madeleine; Killey, Robert I

2009-09-28

We demonstrate a field programmable gate array (FPGA) based optical orthogonal frequency division multiplexing (OFDM) transmitter implementing real time digital signal processing at a sample rate of 21.4 GS/s. The QPSK-OFDM signal is generated using an 8 bit, 128 point inverse fast Fourier transform (IFFT) core, performing one transform per clock cycle at a clock speed of 167.2 MHz and can be deployed with either a direct-detection or a coherent receiver. The hardware design and the main digital signal processing functions are described, and we show that the main performance limitation is due to the low (4-bit) resolution of the digital-to-analog converter (DAC) and the 8-bit resolution of the IFFT core used. We analyze the back-to-back performance of the transmitter generating an 8.36 Gb/s optical single sideband (SSB) OFDM signal using digital up-conversion, suitable for direct-detection. Additionally, we use the device to transmit 8.36 Gb/s SSB OFDM signals over 200 km of uncompensated standard single mode fiber achieving an overall BER<10(-3).

High-Speed, capacitance-based tip clearance sensing

NASA Astrophysics Data System (ADS)

Haase, W. C.; Haase, Z. S.

This paper discusses recent advances in tip clearance measurement systems for turbine engines using capacitive probes. Real time measurements of individual blade pulses are generated using wideband signal processing providing 3 dB bandwidths of typically 5 MHz. Subsequent mixed-signal processing circuitry provide real-time measurements of maximum, minimum, and average clearance with latencies of one blade-to-blade time interval. Both guarded and unguarded probe configurations are possible with the system. Calibration techniques provide high accuracy measurements.

Real-Time Data Display

NASA Technical Reports Server (NTRS)

Pedings, Marc

2007-01-01

RT-Display is a MATLAB-based data acquisition environment designed to use a variety of commercial off-the-shelf (COTS) hardware to digitize analog signals to a standard data format usable by other post-acquisition data analysis tools. This software presents the acquired data in real time using a variety of signal-processing algorithms. The acquired data is stored in a standard Operator Interactive Signal Processing Software (OISPS) data-formatted file. RT-Display is primarily configured to use the Agilent VXI (or equivalent) data acquisition boards used in such systems as MIDDAS (Multi-channel Integrated Dynamic Data Acquisition System). The software is generalized and deployable in almost any testing environment, without limitations or proprietary configuration for a specific test program or project. With the Agilent hardware configured and in place, users can start the program and, in one step, immediately begin digitizing multiple channels of data. Once the acquisition is completed, data is converted into a common binary format that also can be translated to specific formats used by external analysis software, such as OISPS and PC-Signal (product of AI Signal Research Inc.). RT-Display at the time of this reporting was certified on Agilent hardware capable of acquisition up to 196,608 samples per second. Data signals are presented to the user on-screen simultaneously for 16 channels. Each channel can be viewed individually, with a maximum capability of 160 signal channels (depending on hardware configuration). Current signal presentations include: time data, fast Fourier transforms (FFT), and power spectral density plots (PSD). Additional processing algorithms can be easily incorporated into this environment.

Method of detecting system function by measuring frequency response

DOEpatents

Morrison, John L.; Morrison, William H.

2008-07-01

Real time battery impedance spectrum is acquired using one time record, Compensated Synchronous Detection (CSD). This parallel method enables battery diagnostics. The excitation current to a test battery is a sum of equal amplitude sin waves of a few frequencies spread over range of interest. The time profile of this signal has duration that is a few periods of the lowest frequency. The voltage response of the battery, average deleted, is the impedance of the battery in the time domain. Since the excitation frequencies are known, synchronous detection processes the time record and each component, both magnitude and phase, is obtained. For compensation, the components, except the one of interest, are reassembled in the time domain. The resulting signal is subtracted from the original signal and the component of interest is synchronously detected. This process is repeated for each component.

Method of Detecting System Function by Measuring Frequency Response

NASA Technical Reports Server (NTRS)

Morrison, John L. (Inventor); Morrison, William H. (Inventor)

2008-01-01

Real time battery impedance spectrum is acquired using one time record, Compensated Synchronous Detection (CSD). This parallel method enables battery diagnostics. The excitation current to a test battery is a sum of equal amplitude sin waves of a few frequencies spread over range of interest. The time profile of this signal has duration that is a few periods of the lowest frequency. The voltage response of the battery, average deleted, is the impedance of the battery in the time domain. Since the excitation frequencies are known, synchronous detection processes the time record and each component, both magnitude and phase, is obtained. For compensation, the components, except the one of interest, are reassembled in the time domain. The resulting signal is subtracted from the original signal and the component of interest is synchronously detected. This process is repeated for each component.

Testing the Race Model Inequality in Redundant Stimuli with Variable Onset Asynchrony

ERIC Educational Resources Information Center

Gondan, Matthias

2009-01-01

In speeded response tasks with redundant signals, parallel processing of the signals is tested by the race model inequality. This inequality states that given a race of two signals, the cumulative distribution of response times for redundant stimuli never exceeds the sum of the cumulative distributions of response times for the single-modality…

ALMA Correlator Real-Time Data Processor

NASA Astrophysics Data System (ADS)

Pisano, J.; Amestica, R.; Perez, J.

2005-10-01

The design of a real-time Linux application utilizing Real-Time Application Interface (RTAI) to process real-time data from the radio astronomy correlator for the Atacama Large Millimeter Array (ALMA) is described. The correlator is a custom-built digital signal processor which computes the cross-correlation function of two digitized signal streams. ALMA will have 64 antennas with 2080 signal streams each with a sample rate of 4 giga-samples per second. The correlator's aggregate data output will be 1 gigabyte per second. The software is defined by hard deadlines with high input and processing data rates, while requiring interfaces to non real-time external computers. The designed computer system - the Correlator Data Processor or CDP, consists of a cluster of 17 SMP computers, 16 of which are compute nodes plus a master controller node all running real-time Linux kernels. Each compute node uses an RTAI kernel module to interface to a 32-bit parallel interface which accepts raw data at 64 megabytes per second in 1 megabyte chunks every 16 milliseconds. These data are transferred to tasks running on multiple CPUs in hard real-time using RTAI's LXRT facility to perform quantization corrections, data windowing, FFTs, and phase corrections for a processing rate of approximately 1 GFLOPS. Highly accurate timing signals are distributed to all seventeen computer nodes in order to synchronize them to other time-dependent devices in the observatory array. RTAI kernel tasks interface to the timing signals providing sub-millisecond timing resolution. The CDP interfaces, via the master node, to other computer systems on an external intra-net for command and control, data storage, and further data (image) processing. The master node accesses these external systems utilizing ALMA Common Software (ACS), a CORBA-based client-server software infrastructure providing logging, monitoring, data delivery, and intra-computer function invocation. The software is being developed in tandem with the correlator hardware which presents software engineering challenges as the hardware evolves. The current status of this project and future goals are also presented.

Mapping the Information Trace in Local Field Potentials by a Computational Method of Two-Dimensional Time-Shifting Synchronization Likelihood Based on Graphic Processing Unit Acceleration.

PubMed

Zhao, Zi-Fang; Li, Xue-Zhu; Wan, You

2017-12-01

The local field potential (LFP) is a signal reflecting the electrical activity of neurons surrounding the electrode tip. Synchronization between LFP signals provides important details about how neural networks are organized. Synchronization between two distant brain regions is hard to detect using linear synchronization algorithms like correlation and coherence. Synchronization likelihood (SL) is a non-linear synchronization-detecting algorithm widely used in studies of neural signals from two distant brain areas. One drawback of non-linear algorithms is the heavy computational burden. In the present study, we proposed a graphic processing unit (GPU)-accelerated implementation of an SL algorithm with optional 2-dimensional time-shifting. We tested the algorithm with both artificial data and raw LFP data. The results showed that this method revealed detailed information from original data with the synchronization values of two temporal axes, delay time and onset time, and thus can be used to reconstruct the temporal structure of a neural network. Our results suggest that this GPU-accelerated method can be extended to other algorithms for processing time-series signals (like EEG and fMRI) using similar recording techniques.

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

PubMed

Zhang, Y; Liu, A; Yu, K

1999-06-01

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

Experimental photonic generation of chirped pulses using nonlinear dispersion-based incoherent processing.

PubMed

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

2015-05-18

We experimentally demonstrate, for the first time, a chirped microwave pulses generator based on the processing of an incoherent optical signal by means of a nonlinear dispersive element. Different capabilities have been demonstrated such as the control of the time-bandwidth product and the frequency tuning increasing the flexibility of the generated waveform compared to coherent techniques. Moreover, the use of differential detection improves considerably the limitation over the signal-to-noise ratio related to incoherent processing.

New signal processing technique for density profile reconstruction using reflectometry.

PubMed

Clairet, F; Ricaud, B; Briolle, F; Heuraux, S; Bottereau, C

2011-08-01

Reflectometry profile measurement requires an accurate determination of the plasma reflected signal. Along with a good resolution and a high signal to noise ratio of the phase measurement, adequate data analysis is required. A new data processing based on time-frequency tomographic representation is used. It provides a clearer separation between multiple components and improves isolation of the relevant signals. In this paper, this data processing technique is applied to two sets of signals coming from two different reflectometer devices used on the Tore Supra tokamak. For the standard density profile reflectometry, it improves the initialization process and its reliability, providing a more accurate profile determination in the far scrape-off layer with density measurements as low as 10(16) m(-1). For a second reflectometer, which provides measurements in front of a lower hybrid launcher, this method improves the separation of the relevant plasma signal from multi-reflection processes due to the proximity of the plasma.

Investigation of signal processing algorithms for an embedded microcontroller-based wearable pulse oximeter.

PubMed

Johnston, W S; Mendelson, Y

2006-01-01

Despite steady progress in the miniaturization of pulse oximeters over the years, significant challenges remain since advanced signal processing must be implemented efficiently in real-time by a relatively small size wearable device. The goal of this study was to investigate several potential digital signal processing algorithms for computing arterial oxygen saturation (SpO(2)) and heart rate (HR) in a battery-operated wearable reflectance pulse oximeter that is being developed in our laboratory for use by medics and first responders in the field. We found that a differential measurement approach, combined with a low-pass filter (LPF), yielded the most suitable signal processing technique for estimating SpO(2), while a signal derivative approach produced the most accurate HR measurements.

Timeseries Signal Processing for Enhancing Mobile Surveys: Learning from Field Studies

NASA Astrophysics Data System (ADS)

Risk, D. A.; Lavoie, M.; Marshall, A. D.; Baillie, J.; Atherton, E. E.; Laybolt, W. D.

2015-12-01

Vehicle-based surveys using laser and other analyzers are now commonplace in research and industry. In many cases when these studies target biologically-relevant gases like methane and carbon dioxide, the minimum detection limits are often coarse (ppm) relative to the analyzer's capabilities (ppb), because of the inherent variability in the ambient background concentrations across the landscape that creates noise and uncertainty. This variation arises from localized biological sinks and sources, but also atmospheric turbulence, air pooling, and other factors. Computational processing routines are widely used in many fields to increase resolution of a target signal in temporally dense data, and offer promise for enhancing mobile surveying techniques. Signal processing routines can both help identify anomalies at very low levels, or can be used inversely to remove localized industrially-emitted anomalies from ecological data. This presentation integrates learnings from various studies in which simple signal processing routines were used successfully to isolate different temporally-varying components of 1 Hz timeseries measured with laser- and UV fluorescence-based analyzers. As illustrative datasets, we present results from industrial fugitive emission studies from across Canada's western provinces and other locations, and also an ecological study that aimed to model near-surface concentration variability across different biomes within eastern Canada. In these cases, signal processing algorithms contributed significantly to the clarity of both industrial, and ecological processes. In some instances, signal processing was too computationally intensive for real-time in-vehicle processing, but we identified workarounds for analyzer-embedded software that contributed to an improvement in real-time resolution of small anomalies. Signal processing is a natural accompaniment to these datasets, and many avenues are open to researchers who wish to enhance existing, and future datasets.

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.

Non-intrusive measurement of hot gas temperature in a gas turbine engine

DOEpatents

DeSilva, Upul P.; Claussen, Heiko; Yan, Michelle Xiaohong; Rosca, Justinian; Ulerich, Nancy H.

2016-09-27

A method and apparatus for operating a gas turbine engine including determining a temperature of a working gas at a predetermined axial location within the engine. An acoustic signal is encoded with a distinct signature defined by a set of predetermined frequencies transmitted as a non-broadband signal. Acoustic signals are transmitted from an acoustic transmitter located at a predetermined axial location along the flow path of the gas turbine engine. A received signal is compared to one or more transmitted signals to identify a similarity of the received signal to a transmitted signal to identify a transmission time for the received signal. A time-of-flight is determined for the signal and the time-of-flight for the signal is processed to determine a temperature in a region of the predetermined axial location.

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

PubMed

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

2012-01-01

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

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

PubMed Central

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

2012-01-01

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

Load-induced modulation of signal transduction networks.

PubMed

Jiang, Peng; Ventura, Alejandra C; Sontag, Eduardo D; Merajver, Sofia D; Ninfa, Alexander J; Del Vecchio, Domitilla

2011-10-11

Biological signal transduction networks are commonly viewed as circuits that pass along information--in the process amplifying signals, enhancing sensitivity, or performing other signal-processing tasks--to transcriptional and other components. Here, we report on a "reverse-causality" phenomenon, which we call load-induced modulation. Through a combination of analytical and experimental tools, we discovered that signaling was modulated, in a surprising way, by downstream targets that receive the signal and, in doing so, apply what in physics is called a load. Specifically, we found that non-intuitive changes in response dynamics occurred for a covalent modification cycle when load was present. Loading altered the response time of a system, depending on whether the activity of one of the enzymes was maximal and the other was operating at its minimal rate or whether both enzymes were operating at submaximal rates. These two conditions, which we call "limit regime" and "intermediate regime," were associated with increased or decreased response times, respectively. The bandwidth, the range of frequency in which the system can process information, decreased in the presence of load, suggesting that downstream targets participate in establishing a balance between noise-filtering capabilities and a circuit's ability to process high-frequency stimulation. Nodes in a signaling network are not independent relay devices, but rather are modulated by their downstream targets.

Interoceptive signals impact visual processing: Cardiac modulation of visual body perception.

PubMed

Ronchi, Roberta; Bernasconi, Fosco; Pfeiffer, Christian; Bello-Ruiz, Javier; Kaliuzhna, Mariia; Blanke, Olaf

2017-09-01

Multisensory perception research has largely focused on exteroceptive signals, but recent evidence has revealed the integration of interoceptive signals with exteroceptive information. Such research revealed that heartbeat signals affect sensory (e.g., visual) processing: however, it is unknown how they impact the perception of body images. Here we linked our participants' heartbeat to visual stimuli and investigated the spatio-temporal brain dynamics of cardio-visual stimulation on the processing of human body images. We recorded visual evoked potentials with 64-channel electroencephalography while showing a body or a scrambled-body (control) that appeared at the frequency of the on-line recorded participants' heartbeat or not (not-synchronous, control). Extending earlier studies, we found a body-independent effect, with cardiac signals enhancing visual processing during two time periods (77-130 ms and 145-246 ms). Within the second (later) time-window we detected a second effect characterised by enhanced activity in parietal, temporo-occipital, inferior frontal, and right basal ganglia-insula regions, but only when non-scrambled body images were flashed synchronously with the heartbeat (208-224 ms). In conclusion, our results highlight the role of interoceptive information for the visual processing of human body pictures within a network integrating cardio-visual signals of relevance for perceptual and cognitive aspects of visual body processing. Copyright © 2017 Elsevier Inc. All rights reserved.

Real Time Phase Noise Meter Based on a Digital Signal Processor

NASA Technical Reports Server (NTRS)

Angrisani, Leopoldo; D'Arco, Mauro; Greenhall, Charles A.; Schiano Lo Morille, Rosario

2006-01-01

A digital signal-processing meter for phase noise measurement on sinusoidal signals is dealt with. It enlists a special hardware architecture, made up of a core digital signal processor connected to a data acquisition board, and takes advantage of a quadrature demodulation-based measurement scheme, already proposed by the authors. Thanks to an efficient measurement process and an optimized implementation of its fundamental stages, the proposed meter succeeds in exploiting all hardware resources in such an effective way as to gain high performance and real-time operation. For input frequencies up to some hundreds of kilohertz, the meter is capable both of updating phase noise power spectrum while seamlessly capturing the analyzed signal into its memory, and granting as good frequency resolution as few units of hertz.

Ultrasonic Signal Processing for Structural Health Monitoring

NASA Astrophysics Data System (ADS)

Michaels, Jennifer E.; Michaels, Thomas E.

2004-02-01

Permanently mounted ultrasonic sensors are a key component of systems under development for structural health monitoring. Signal processing plays a critical role in the viability of such systems due to the difficulty in interpreting signals received from structures of complex geometry. This paper describes a differential feature-based approach to classifying signal changes as either "environmental" or "structural". Data are presented from piezoelectric discs bonded to an aluminum specimen subjected to both environmental changes and introduction of artificial defects. The classifier developed as part of this study was able to correctly identify artificial defects that were not part of the initial training and evaluation data sets. Central to the success of the classifier was the use of the Short Time Cross Correlation to measure coherency between the signal and reference as a function of time.

Real-time spatio-temporal coherence estimation for autonomous mode identification and invariance tracking

NASA Technical Reports Server (NTRS)

Park, Han G. (Inventor); Zak, Michail (Inventor); James, Mark L. (Inventor); Mackey, Ryan M. E. (Inventor)

2003-01-01

A general method of anomaly detection from time-correlated sensor data is disclosed. Multiple time-correlated signals are received. Their cross-signal behavior is compared against a fixed library of invariants. The library is constructed during a training process, which is itself data-driven using the same time-correlated signals. The method is applicable to a broad class of problems and is designed to respond to any departure from normal operation, including faults or events that lie outside the training envelope.

Models and signal processing for an implanted ethanol bio-sensor.

PubMed

Han, Jae-Joon; Doerschuk, Peter C; Gelfand, Saul B; O'Connor, Sean J

2008-02-01

The understanding of drinking patterns leading to alcoholism has been hindered by an inability to unobtrusively measure ethanol consumption over periods of weeks to months in the community environment. An implantable ethanol sensor is under development using microelectromechanical systems technology. For safety and user acceptability issues, the sensor will be implanted subcutaneously and, therefore, measure peripheral-tissue ethanol concentration. Determining ethanol consumption and kinetics in other compartments from the time course of peripheral-tissue ethanol concentration requires sophisticated signal processing based on detailed descriptions of the relevant physiology. A statistical signal processing system based on detailed models of the physiology and using extended Kalman filtering and dynamic programming tools is described which can estimate the time series of ethanol concentration in blood, liver, and peripheral tissue and the time series of ethanol consumption based on peripheral-tissue ethanol concentration measurements.

Signal processing methods for in-situ creep specimen monitoring

NASA Astrophysics Data System (ADS)

Guers, Manton J.; Tittmann, Bernhard R.

2018-04-01

Previous work investigated using guided waves for monitoring creep deformation during accelerated life testing. The basic objective was to relate observed changes in the time-of-flight to changes in the environmental temperature and specimen gage length. The work presented in this paper investigated several signal processing strategies for possible application in the in-situ monitoring system. Signal processing methods for both group velocity (wave-packet envelope) and phase velocity (peak tracking) time-of-flight were considered. Although the Analytic Envelope found via the Hilbert transform is commonly applied for group velocity measurements, erratic behavior in the indicated time-of-flight was observed when this technique was applied to the in-situ data. The peak tracking strategies tested had generally linear trends, and tracking local minima in the raw waveform ultimately showed the most consistent results.

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

NASA Astrophysics Data System (ADS)

Buś, Szymon; Jedrzejewski, Konrad

2016-09-01

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

Event-driven processing for hardware-efficient neural spike sorting

NASA Astrophysics Data System (ADS)

Liu, Yan; Pereira, João L.; Constandinou, Timothy G.

2018-02-01

Objective. The prospect of real-time and on-node spike sorting provides a genuine opportunity to push the envelope of large-scale integrated neural recording systems. In such systems the hardware resources, power requirements and data bandwidth increase linearly with channel count. Event-based (or data-driven) processing can provide here a new efficient means for hardware implementation that is completely activity dependant. In this work, we investigate using continuous-time level-crossing sampling for efficient data representation and subsequent spike processing. Approach. (1) We first compare signals (synthetic neural datasets) encoded with this technique against conventional sampling. (2) We then show how such a representation can be directly exploited by extracting simple time domain features from the bitstream to perform neural spike sorting. (3) The proposed method is implemented in a low power FPGA platform to demonstrate its hardware viability. Main results. It is observed that considerably lower data rates are achievable when using 7 bits or less to represent the signals, whilst maintaining the signal fidelity. Results obtained using both MATLAB and reconfigurable logic hardware (FPGA) indicate that feature extraction and spike sorting accuracies can be achieved with comparable or better accuracy than reference methods whilst also requiring relatively low hardware resources. Significance. By effectively exploiting continuous-time data representation, neural signal processing can be achieved in a completely event-driven manner, reducing both the required resources (memory, complexity) and computations (operations). This will see future large-scale neural systems integrating on-node processing in real-time hardware.

Rapid Structured Volume Grid Smoothing and Adaption Technique

NASA Technical Reports Server (NTRS)

Alter, Stephen J.

2006-01-01

A rapid, structured volume grid smoothing and adaption technique, based on signal processing methods, was developed and applied to the Shuttle Orbiter at hypervelocity flight conditions in support of the Columbia Accident Investigation. Because of the fast pace of the investigation, computational aerothermodynamicists, applying hypersonic viscous flow solving computational fluid dynamic (CFD) codes, refined and enhanced a grid for an undamaged baseline vehicle to assess a variety of damage scenarios. Of the many methods available to modify a structured grid, most are time-consuming and require significant user interaction. By casting the grid data into different coordinate systems, specifically two computational coordinates with arclength as the third coordinate, signal processing methods are used for filtering the data [Taubin, CG v/29 1995]. Using a reverse transformation, the processed data are used to smooth the Cartesian coordinates of the structured grids. By coupling the signal processing method with existing grid operations within the Volume Grid Manipulator tool, problems related to grid smoothing are solved efficiently and with minimal user interaction. Examples of these smoothing operations are illustrated for reductions in grid stretching and volume grid adaptation. In each of these examples, other techniques existed at the time of the Columbia accident, but the incorporation of signal processing techniques reduced the time to perform the corrections by nearly 60%. This reduction in time to perform the corrections therefore enabled the assessment of approximately twice the number of damage scenarios than previously possible during the allocated investigation time.

Rapid Structured Volume Grid Smoothing and Adaption Technique

NASA Technical Reports Server (NTRS)

Alter, Stephen J.

2004-01-01

A rapid, structured volume grid smoothing and adaption technique, based on signal processing methods, was developed and applied to the Shuttle Orbiter at hypervelocity flight conditions in support of the Columbia Accident Investigation. Because of the fast pace of the investigation, computational aerothermodynamicists, applying hypersonic viscous flow solving computational fluid dynamic (CFD) codes, refined and enhanced a grid for an undamaged baseline vehicle to assess a variety of damage scenarios. Of the many methods available to modify a structured grid, most are time-consuming and require significant user interaction. By casting the grid data into different coordinate systems, specifically two computational coordinates with arclength as the third coordinate, signal processing methods are used for filtering the data [Taubin, CG v/29 1995]. Using a reverse transformation, the processed data are used to smooth the Cartesian coordinates of the structured grids. By coupling the signal processing method with existing grid operations within the Volume Grid Manipulator tool, problems related to grid smoothing are solved efficiently and with minimal user interaction. Examples of these smoothing operations are illustrated for reduction in grid stretching and volume grid adaptation. In each of these examples, other techniques existed at the time of the Columbia accident, but the incorporation of signal processing techniques reduced the time to perform the corrections by nearly 60%. This reduction in time to perform the corrections therefore enabled the assessment of approximately twice the number of damage scenarios than previously possible during the allocated investigation time.

Signal Restoration of Non-stationary Acoustic Signals in the Time Domain

NASA Technical Reports Server (NTRS)

Babkin, Alexander S.

1988-01-01

Signal restoration is a method of transforming a nonstationary signal acquired by a ground based microphone to an equivalent stationary signal. The benefit of the signal restoration is a simplification of the flight test requirements because it could dispense with the need to acquire acoustic data with another aircraft flying in concert with the rotorcraft. The data quality is also generally improved because the contamination of the signal by the propeller and wind noise is not present. The restoration methodology can also be combined with other data acquisition methods, such as a multiple linear microphone array for further improvement of the test results. The methodology and software are presented for performing the signal restoration in the time domain. The method has no restrictions on flight path geometry or flight regimes. Only requirement is that the aircraft spatial position be known relative to the microphone location and synchronized with the acoustic data. The restoration process assumes that the moving source radiates a stationary signal, which is then transformed into a nonstationary signal by various modulation processes. The restoration contains only the modulation due to the source motion.

Signal digitizing system and method based on amplitude-to-time optical mapping

DOEpatents

Chou, Jason; Bennett, Corey V; Hernandez, Vince

2015-01-13

A signal digitizing system and method based on analog-to-time optical mapping, optically maps amplitude information of an analog signal of interest first into wavelength information using an amplitude tunable filter (ATF) to impress spectral changes induced by the amplitude of the analog signal onto a carrier signal, i.e. a train of optical pulses, and next from wavelength information to temporal information using a dispersive element so that temporal information representing the amplitude information is encoded in the time domain in the carrier signal. Optical-to-electrical conversion of the optical pulses into voltage waveforms and subsequently digitizing the voltage waveforms into a digital image enables the temporal information to be resolved and quantized in the time domain. The digital image may them be digital signal processed to digitally reconstruct the analog signal based on the temporal information with high fidelity.

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.

Constant versus variable response signal delays in speed--accuracy trade-offs: effects of advance preparation for processing time.

PubMed

Miller, Jeff; Sproesser, Gudrun; Ulrich, Rolf

2008-07-01

In two experiments, we used response signals (RSs) to control processing time and trace out speed--accuracy trade-off(SAT) functions in a difficult perceptual discrimination task. Each experiment compared performance in blocks of trials with constant and, hence, temporally predictable RS lags against performance in blocks with variable, unpredictable RS lags. In both experiments, essentially equivalent SAT functions were observed with constant and variable RS lags. We conclude that there is little effect of advance preparation for a given processing time, suggesting that the discrimination mechanisms underlying SAT functions are driven solely by bottom-up information processing in perceptual discrimination tasks.

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.

Design of a dataway processor for a parallel image signal processing system

NASA Astrophysics Data System (ADS)

Nomura, Mitsuru; Fujii, Tetsuro; Ono, Sadayasu

1995-04-01

Recently, demands for high-speed signal processing have been increasing especially in the field of image data compression, computer graphics, and medical imaging. To achieve sufficient power for real-time image processing, we have been developing parallel signal-processing systems. This paper describes a communication processor called 'dataway processor' designed for a new scalable parallel signal-processing system. The processor has six high-speed communication links (Dataways), a data-packet routing controller, a RISC CORE, and a DMA controller. Each communication link operates at 8-bit parallel in a full duplex mode at 50 MHz. Moreover, data routing, DMA, and CORE operations are processed in parallel. Therefore, sufficient throughput is available for high-speed digital video signals. The processor is designed in a top- down fashion using a CAD system called 'PARTHENON.' The hardware is fabricated using 0.5-micrometers CMOS technology, and its hardware is about 200 K gates.

Poisson pre-processing of nonstationary photonic signals: Signals with equality between mean and variance.

PubMed

Poplová, Michaela; Sovka, Pavel; Cifra, Michal

2017-01-01

Photonic signals are broadly exploited in communication and sensing and they typically exhibit Poisson-like statistics. In a common scenario where the intensity of the photonic signals is low and one needs to remove a nonstationary trend of the signals for any further analysis, one faces an obstacle: due to the dependence between the mean and variance typical for a Poisson-like process, information about the trend remains in the variance even after the trend has been subtracted, possibly yielding artifactual results in further analyses. Commonly available detrending or normalizing methods cannot cope with this issue. To alleviate this issue we developed a suitable pre-processing method for the signals that originate from a Poisson-like process. In this paper, a Poisson pre-processing method for nonstationary time series with Poisson distribution is developed and tested on computer-generated model data and experimental data of chemiluminescence from human neutrophils and mung seeds. The presented method transforms a nonstationary Poisson signal into a stationary signal with a Poisson distribution while preserving the type of photocount distribution and phase-space structure of the signal. The importance of the suggested pre-processing method is shown in Fano factor and Hurst exponent analysis of both computer-generated model signals and experimental photonic signals. It is demonstrated that our pre-processing method is superior to standard detrending-based methods whenever further signal analysis is sensitive to variance of the signal.

Poisson pre-processing of nonstationary photonic signals: Signals with equality between mean and variance

PubMed Central

Poplová, Michaela; Sovka, Pavel

2017-01-01

Photonic signals are broadly exploited in communication and sensing and they typically exhibit Poisson-like statistics. In a common scenario where the intensity of the photonic signals is low and one needs to remove a nonstationary trend of the signals for any further analysis, one faces an obstacle: due to the dependence between the mean and variance typical for a Poisson-like process, information about the trend remains in the variance even after the trend has been subtracted, possibly yielding artifactual results in further analyses. Commonly available detrending or normalizing methods cannot cope with this issue. To alleviate this issue we developed a suitable pre-processing method for the signals that originate from a Poisson-like process. In this paper, a Poisson pre-processing method for nonstationary time series with Poisson distribution is developed and tested on computer-generated model data and experimental data of chemiluminescence from human neutrophils and mung seeds. The presented method transforms a nonstationary Poisson signal into a stationary signal with a Poisson distribution while preserving the type of photocount distribution and phase-space structure of the signal. The importance of the suggested pre-processing method is shown in Fano factor and Hurst exponent analysis of both computer-generated model signals and experimental photonic signals. It is demonstrated that our pre-processing method is superior to standard detrending-based methods whenever further signal analysis is sensitive to variance of the signal. PMID:29216207

Predict or classify: The deceptive role of time-locking in brain signal classification

NASA Astrophysics Data System (ADS)

Rusconi, Marco; Valleriani, Angelo

2016-06-01

Several experimental studies claim to be able to predict the outcome of simple decisions from brain signals measured before subjects are aware of their decision. Often, these studies use multivariate pattern recognition methods with the underlying assumption that the ability to classify the brain signal is equivalent to predict the decision itself. Here we show instead that it is possible to correctly classify a signal even if it does not contain any predictive information about the decision. We first define a simple stochastic model that mimics the random decision process between two equivalent alternatives, and generate a large number of independent trials that contain no choice-predictive information. The trials are first time-locked to the time point of the final event and then classified using standard machine-learning techniques. The resulting classification accuracy is above chance level long before the time point of time-locking. We then analyze the same trials using information theory. We demonstrate that the high classification accuracy is a consequence of time-locking and that its time behavior is simply related to the large relaxation time of the process. We conclude that when time-locking is a crucial step in the analysis of neural activity patterns, both the emergence and the timing of the classification accuracy are affected by structural properties of the network that generates the signal.

A UWB Radar Signal Processing Platform for Real-Time Human Respiratory Feature Extraction Based on Four-Segment Linear Waveform Model.

PubMed

Hsieh, Chi-Hsuan; Chiu, Yu-Fang; Shen, Yi-Hsiang; Chu, Ta-Shun; Huang, Yuan-Hao

2016-02-01

This paper presents an ultra-wideband (UWB) impulse-radio radar signal processing platform used to analyze human respiratory features. Conventional radar systems used in human detection only analyze human respiration rates or the response of a target. However, additional respiratory signal information is available that has not been explored using radar detection. The authors previously proposed a modified raised cosine waveform (MRCW) respiration model and an iterative correlation search algorithm that could acquire additional respiratory features such as the inspiration and expiration speeds, respiration intensity, and respiration holding ratio. To realize real-time respiratory feature extraction by using the proposed UWB signal processing platform, this paper proposes a new four-segment linear waveform (FSLW) respiration model. This model offers a superior fit to the measured respiration signal compared with the MRCW model and decreases the computational complexity of feature extraction. In addition, an early-terminated iterative correlation search algorithm is presented, substantially decreasing the computational complexity and yielding negligible performance degradation. These extracted features can be considered the compressed signals used to decrease the amount of data storage required for use in long-term medical monitoring systems and can also be used in clinical diagnosis. The proposed respiratory feature extraction algorithm was designed and implemented using the proposed UWB radar signal processing platform including a radar front-end chip and an FPGA chip. The proposed radar system can detect human respiration rates at 0.1 to 1 Hz and facilitates the real-time analysis of the respiratory features of each respiration period.

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.

Efficient block processing of long duration biotelemetric brain data for health care monitoring

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

Soumya, I.; Zia Ur Rahman, M., E-mail: mdzr-5@ieee.org; Rama Koti Reddy, D. V.

In real time clinical environment, the brain signals which doctor need to analyze are usually very long. Such a scenario can be made simple by partitioning the input signal into several blocks and applying signal conditioning. This paper presents various block based adaptive filter structures for obtaining high resolution electroencephalogram (EEG) signals, which estimate the deterministic components of the EEG signal by removing noise. To process these long duration signals, we propose Time domain Block Least Mean Square (TDBLMS) algorithm for brain signal enhancement. In order to improve filtering capability, we introduce normalization in the weight update recursion of TDBLMS,more » which results TD-B-normalized-least mean square (LMS). To increase accuracy and resolution in the proposed noise cancelers, we implement the time domain cancelers in frequency domain which results frequency domain TDBLMS and FD-B-Normalized-LMS. Finally, we have applied these algorithms on real EEG signals obtained from human using Emotive Epoc EEG recorder and compared their performance with the conventional LMS algorithm. The results show that the performance of the block based algorithms is superior to the LMS counter-parts in terms of signal to noise ratio, convergence rate, excess mean square error, misadjustment, and coherence.« less

Stream computing for biomedical signal processing: A QRS complex detection case-study.

PubMed

Murphy, B M; O'Driscoll, C; Boylan, G B; Lightbody, G; Marnane, W P

2015-01-01

Recent developments in "Big Data" have brought significant gains in the ability to process large amounts of data on commodity server hardware. Stream computing is a relatively new paradigm in this area, addressing the need to process data in real time with very low latency. While this approach has been developed for dealing with large scale data from the world of business, security and finance, there is a natural overlap with clinical needs for physiological signal processing. In this work we present a case study of streams processing applied to a typical physiological signal processing problem: QRS detection from ECG data.

Subspace-based interference removal methods for a multichannel biomagnetic sensor array.

PubMed

Sekihara, Kensuke; Nagarajan, Srikantan S

2017-10-01

In biomagnetic signal processing, the theory of the signal subspace has been applied to removing interfering magnetic fields, and a representative algorithm is the signal space projection algorithm, in which the signal/interference subspace is defined in the spatial domain as the span of signal/interference-source lead field vectors. This paper extends the notion of this conventional (spatial domain) signal subspace by introducing a new definition of signal subspace in the time domain. It defines the time-domain signal subspace as the span of row vectors that contain the source time course values. This definition leads to symmetric relationships between the time-domain and the conventional (spatial-domain) signal subspaces. As a review, this article shows that the notion of the time-domain signal subspace provides useful insights over existing interference removal methods from a unified perspective. Main results and significance. Using the time-domain signal subspace, it is possible to interpret a number of interference removal methods as the time domain signal space projection. Such methods include adaptive noise canceling, sensor noise suppression, the common temporal subspace projection, the spatio-temporal signal space separation, and the recently-proposed dual signal subspace projection. Our analysis using the notion of the time domain signal space projection reveals implicit assumptions these methods rely on, and shows that the difference between these methods results only from the manner of deriving the interference subspace. Numerical examples that illustrate the results of our arguments are provided.

Subspace-based interference removal methods for a multichannel biomagnetic sensor array

NASA Astrophysics Data System (ADS)

Sekihara, Kensuke; Nagarajan, Srikantan S.

2017-10-01

Objective. In biomagnetic signal processing, the theory of the signal subspace has been applied to removing interfering magnetic fields, and a representative algorithm is the signal space projection algorithm, in which the signal/interference subspace is defined in the spatial domain as the span of signal/interference-source lead field vectors. This paper extends the notion of this conventional (spatial domain) signal subspace by introducing a new definition of signal subspace in the time domain. Approach. It defines the time-domain signal subspace as the span of row vectors that contain the source time course values. This definition leads to symmetric relationships between the time-domain and the conventional (spatial-domain) signal subspaces. As a review, this article shows that the notion of the time-domain signal subspace provides useful insights over existing interference removal methods from a unified perspective. Main results and significance. Using the time-domain signal subspace, it is possible to interpret a number of interference removal methods as the time domain signal space projection. Such methods include adaptive noise canceling, sensor noise suppression, the common temporal subspace projection, the spatio-temporal signal space separation, and the recently-proposed dual signal subspace projection. Our analysis using the notion of the time domain signal space projection reveals implicit assumptions these methods rely on, and shows that the difference between these methods results only from the manner of deriving the interference subspace. Numerical examples that illustrate the results of our arguments are provided.

A simple analytical model for signal amplification by reversible exchange (SABRE) process.

PubMed

Barskiy, Danila A; Pravdivtsev, Andrey N; Ivanov, Konstantin L; Kovtunov, Kirill V; Koptyug, Igor V

2016-01-07

We demonstrate an analytical model for the description of the signal amplification by reversible exchange (SABRE) process. The model relies on a combined analysis of chemical kinetics and the evolution of the nuclear spin system during the hyperpolarization process. The presented model for the first time provides rationale for deciding which system parameters (i.e. J-couplings, relaxation rates, reaction rate constants) have to be optimized in order to achieve higher signal enhancement for a substrate of interest in SABRE experiments.

An overview of data acquisition, signal coding and data analysis techniques for MST radars

NASA Technical Reports Server (NTRS)

Rastogi, P. K.

1986-01-01

An overview is given of the data acquisition, signal processing, and data analysis techniques that are currently in use with high power MST/ST (mesosphere stratosphere troposphere/stratosphere troposphere) radars. This review supplements the works of Rastogi (1983) and Farley (1984) presented at previous MAP workshops. A general description is given of data acquisition and signal processing operations and they are characterized on the basis of their disparate time scales. Then signal coding, a brief description of frequently used codes, and their limitations are discussed, and finally, several aspects of statistical data processing such as signal statistics, power spectrum and autocovariance analysis, outlier removal techniques are discussed.

Review of current GPS methodologies for producing accurate time series and their error sources

NASA Astrophysics Data System (ADS)

He, Xiaoxing; Montillet, Jean-Philippe; Fernandes, Rui; Bos, Machiel; Yu, Kegen; Hua, Xianghong; Jiang, Weiping

2017-05-01

The Global Positioning System (GPS) is an important tool to observe and model geodynamic processes such as plate tectonics and post-glacial rebound. In the last three decades, GPS has seen tremendous advances in the precision of the measurements, which allow researchers to study geophysical signals through a careful analysis of daily time series of GPS receiver coordinates. However, the GPS observations contain errors and the time series can be described as the sum of a real signal and noise. The signal itself can again be divided into station displacements due to geophysical causes and to disturbing factors. Examples of the latter are errors in the realization and stability of the reference frame and corrections due to ionospheric and tropospheric delays and GPS satellite orbit errors. There is an increasing demand on detecting millimeter to sub-millimeter level ground displacement signals in order to further understand regional scale geodetic phenomena hence requiring further improvements in the sensitivity of the GPS solutions. This paper provides a review spanning over 25 years of advances in processing strategies, error mitigation methods and noise modeling for the processing and analysis of GPS daily position time series. The processing of the observations is described step-by-step and mainly with three different strategies in order to explain the weaknesses and strengths of the existing methodologies. In particular, we focus on the choice of the stochastic model in the GPS time series, which directly affects the estimation of the functional model including, for example, tectonic rates, seasonal signals and co-seismic offsets. Moreover, the geodetic community continues to develop computational methods to fully automatize all phases from analysis of GPS time series. This idea is greatly motivated by the large number of GPS receivers installed around the world for diverse applications ranging from surveying small deformations of civil engineering structures (e.g., subsidence of the highway bridge) to the detection of particular geophysical signals.

Real-time digital signal processing in multiphoton and time-resolved microscopy

NASA Astrophysics Data System (ADS)

Wilson, Jesse W.; Warren, Warren S.; Fischer, Martin C.

2016-03-01

The use of multiphoton interactions in biological tissue for imaging contrast requires highly sensitive optical measurements. These often involve signal processing and filtering steps between the photodetector and the data acquisition device, such as photon counting and lock-in amplification. These steps can be implemented as real-time digital signal processing (DSP) elements on field-programmable gate array (FPGA) devices, an approach that affords much greater flexibility than commercial photon counting or lock-in devices. We will present progress toward developing two new FPGA-based DSP devices for multiphoton and time-resolved microscopy applications. The first is a high-speed multiharmonic lock-in amplifier for transient absorption microscopy, which is being developed for real-time analysis of the intensity-dependence of melanin, with applications in vivo and ex vivo (noninvasive histopathology of melanoma and pigmented lesions). The second device is a kHz lock-in amplifier running on a low cost (50-200) development platform. It is our hope that these FPGA-based DSP devices will enable new, high-speed, low-cost applications in multiphoton and time-resolved microscopy.

Visual Information Processing and Response Time in Traffic-Signal Cognition

DTIC Science & Technology

1992-03-01

TYPE AND DATES COVERED IMarch 1992 IMaster’s Thesis 4. TITLE AND SUBTITLE 5. FUNDING NUMBERS VISUAL INEORMATION PIRXC ING AND RESPOSE TIME IN TRAFFIC...34The Influence of the Time Duration of Yellow Traffic Signals On Driver Response," ITE Journal, (November 1980). 145 William D. Kosnic. " Self

Missile signal processing common computer architecture for rapid technology upgrade

NASA Astrophysics Data System (ADS)

Rabinkin, Daniel V.; Rutledge, Edward; Monticciolo, Paul

2004-10-01

Interceptor missiles process IR images to locate an intended target and guide the interceptor towards it. Signal processing requirements have increased as the sensor bandwidth increases and interceptors operate against more sophisticated targets. A typical interceptor signal processing chain is comprised of two parts. Front-end video processing operates on all pixels of the image and performs such operations as non-uniformity correction (NUC), image stabilization, frame integration and detection. Back-end target processing, which tracks and classifies targets detected in the image, performs such algorithms as Kalman tracking, spectral feature extraction and target discrimination. In the past, video processing was implemented using ASIC components or FPGAs because computation requirements exceeded the throughput of general-purpose processors. Target processing was performed using hybrid architectures that included ASICs, DSPs and general-purpose processors. The resulting systems tended to be function-specific, and required custom software development. They were developed using non-integrated toolsets and test equipment was developed along with the processor platform. The lifespan of a system utilizing the signal processing platform often spans decades, while the specialized nature of processor hardware and software makes it difficult and costly to upgrade. As a result, the signal processing systems often run on outdated technology, algorithms are difficult to update, and system effectiveness is impaired by the inability to rapidly respond to new threats. A new design approach is made possible three developments; Moore's Law - driven improvement in computational throughput; a newly introduced vector computing capability in general purpose processors; and a modern set of open interface software standards. Today's multiprocessor commercial-off-the-shelf (COTS) platforms have sufficient throughput to support interceptor signal processing requirements. This application may be programmed under existing real-time operating systems using parallel processing software libraries, resulting in highly portable code that can be rapidly migrated to new platforms as processor technology evolves. Use of standardized development tools and 3rd party software upgrades are enabled as well as rapid upgrade of processing components as improved algorithms are developed. The resulting weapon system will have a superior processing capability over a custom approach at the time of deployment as a result of a shorter development cycles and use of newer technology. The signal processing computer may be upgraded over the lifecycle of the weapon system, and can migrate between weapon system variants enabled by modification simplicity. This paper presents a reference design using the new approach that utilizes an Altivec PowerPC parallel COTS platform. It uses a VxWorks-based real-time operating system (RTOS), and application code developed using an efficient parallel vector library (PVL). A quantification of computing requirements and demonstration of interceptor algorithm operating on this real-time platform are provided.

One process is not enough! A speed-accuracy tradeoff study of recognition memory.

PubMed

Boldini, Angela; Russo, Riccardo; Avons, S E

2004-04-01

Speed-accuracy tradeoff (SAT) methods have been used to contrast single- and dual-process accounts of recognition memory. In these procedures, subjects are presented with individual test items and are required to make recognition decisions under various time constraints. In this experiment, we presented word lists under incidental learning conditions, varying the modality of presentation and level of processing. At test, we manipulated the interval between each visually presented test item and a response signal, thus controlling the amount of time available to retrieve target information. Study-test modality match had a beneficial effect on recognition accuracy at short response-signal delays (< or =300 msec). Conversely, recognition accuracy benefited more from deep than from shallow processing at study only at relatively long response-signal delays (> or =300 msec). The results are congruent with views suggesting that both fast familiarity and slower recollection processes contribute to recognition memory.

Achieving subpixel resolution with time-correlated transient signals in pixelated CdZnTe gamma-ray sensors using a focused laser beam (Conference Presentation)

NASA Astrophysics Data System (ADS)

Ocampo Giraldo, Luis A.; Bolotnikov, Aleksey E.; Camarda, Giuseppe S.; Cui, Yonggang; De Geronimo, Gianluigi; Gul, Rubi; Fried, Jack; Hossain, Anwar; Unlu, Kenan; Vernon, Emerson; Yang, Ge; James, Ralph B.

2017-05-01

High-resolution position-sensitive detectors have been proposed to correct response non-uniformities in Cadmium Zinc Telluride (CZT) crystals by virtually subdividing the detectors area into small voxels and equalizing responses from each voxel. 3D pixelated detectors coupled with multichannel readout electronics are the most advanced type of CZT devices offering many options in signal processing and enhancing detector performance. One recent innovation proposed for pixelated detectors is to use the induced (transient) signals from neighboring pixels to achieve high sub-pixel position resolution while keeping large pixel sizes. The main hurdle in achieving this goal is the relatively low signal induced on the neighboring pixels because of the electrostatic shielding effect caused by the collecting pixel. In addition, to achieve high position sensitivity one should rely on time-correlated transient signals, which means that digitized output signals must be used. We present the results of our studies to measure the amplitude of the pixel signals so that these can be used to measure positions of the interaction points. This is done with the processing of digitized correlated time signals measured from several adjacent pixels taking into account rise-time and charge-sharing effects. In these measurements we used a focused pulsed laser to generate a 10-micron beam at one milliwatt (650-nm wavelength) over the detector surface while the collecting pixel was moved in cardinal directions. The results include measurements that present the benefits of combining conventional pixel geometry with digital pulse processing for the best approach in achieving sub-pixel position resolution with the pixel dimensions of approximately 2 mm. We also present the sub-pixel resolution measurements at comparable energies from various gamma emitting isotopes.

An efficient ASIC implementation of 16-channel on-line recursive ICA processor for real-time EEG system.

PubMed

Fang, Wai-Chi; Huang, Kuan-Ju; Chou, Chia-Ching; Chang, Jui-Chung; Cauwenberghs, Gert; Jung, Tzyy-Ping

2014-01-01

This is a proposal for an efficient very-large-scale integration (VLSI) design, 16-channel on-line recursive independent component analysis (ORICA) processor ASIC for real-time EEG system, implemented with TSMC 40 nm CMOS technology. ORICA is appropriate to be used in real-time EEG system to separate artifacts because of its highly efficient and real-time process features. The proposed ORICA processor is composed of an ORICA processing unit and a singular value decomposition (SVD) processing unit. Compared with previous work [1], this proposed ORICA processor has enhanced effectiveness and reduced hardware complexity by utilizing a deeper pipeline architecture, shared arithmetic processing unit, and shared registers. The 16-channel random signals which contain 8-channel super-Gaussian and 8-channel sub-Gaussian components are used to analyze the dependence of the source components, and the average correlation coefficient is 0.95452 between the original source signals and extracted ORICA signals. Finally, the proposed ORICA processor ASIC is implemented with TSMC 40 nm CMOS technology, and it consumes 15.72 mW at 100 MHz operating frequency.

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.

Burst design and signal processing for the speed of sound measurement of fluids with the pulse-echo technique

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

Dubberke, Frithjof H.; Baumhögger, Elmar; Vrabec, Jadran, E-mail: jadran.vrabec@upb.de

2015-05-15

The pulse-echo technique determines the propagation time of acoustic wave bursts in a fluid over a known propagation distance. It is limited by the signal quality of the received echoes of the acoustic wave bursts, which degrades with decreasing density of the fluid due to acoustic impedance and attenuation effects. Signal sampling is significantly improved in this work by burst design and signal processing such that a wider range of thermodynamic states can be investigated. Applying a Fourier transformation based digital filter on acoustic wave signals increases their signal-to-noise ratio and enhances their time and amplitude resolutions, improving the overallmore » measurement accuracy. In addition, burst design leads to technical advantages for determining the propagation time due to the associated conditioning of the echo. It is shown that the according operation procedure enlarges the measuring range of the pulse-echo technique for supercritical argon and nitrogen at 300 K down to 5 MPa, where it was limited to around 20 MPa before.« less

Processing language in face-to-face conversation: Questions with gestures get faster responses.

PubMed

Holler, Judith; Kendrick, Kobin H; Levinson, Stephen C

2017-09-08

The home of human language use is face-to-face interaction, a context in which communicative exchanges are characterised not only by bodily signals accompanying what is being said but also by a pattern of alternating turns at talk. This transition between turns is astonishingly fast-typically a mere 200-ms elapse between a current and a next speaker's contribution-meaning that comprehending, producing, and coordinating conversational contributions in time is a significant challenge. This begs the question of whether the additional information carried by bodily signals facilitates or hinders language processing in this time-pressured environment. We present analyses of multimodal conversations revealing that bodily signals appear to profoundly influence language processing in interaction: Questions accompanied by gestures lead to shorter turn transition times-that is, to faster responses-than questions without gestures, and responses come earlier when gestures end before compared to after the question turn has ended. These findings hold even after taking into account prosodic patterns and other visual signals, such as gaze. The empirical findings presented here provide a first glimpse of the role of the body in the psycholinguistic processes underpinning human communication.

Is transcranial direct current stimulation a potential method for improving response inhibition?☆

PubMed Central

Kwon, Yong Hyun; Kwon, Jung Won

2013-01-01

Inhibitory control of movement in motor learning requires the ability to suppress an inappropriate action, a skill needed to stop a planned or ongoing motor response in response to changes in a variety of environments. This study used a stop-signal task to determine whether transcranial direct-current stimulation over the pre-supplementary motor area alters the reaction time in motor inhibition. Forty healthy subjects were recruited for this study and were randomly assigned to either the transcranial direct-current stimulation condition or a sham-transcranial direct-current stimulation condition. All subjects consecutively performed the stop-signal task before, during, and after the delivery of anodal transcranial direct-current stimulation over the pre-supplementary motor area (pre-transcranial direct-current stimulation phase, transcranial direct-current stimulation phase, and post-transcranial direct-current stimulation phase). Compared to the sham condition, there were significant reductions in the stop-signal processing times during and after transcranial direct-current stimulation, and change times were significantly greater in the transcranial direct-current stimulation condition. There was no significant change in go processing-times during or after transcranial direct-current stimulation in either condition. Anodal transcranial direct-current stimulation was feasibly coupled to an interactive improvement in inhibitory control. This coupling led to a decrease in the stop-signal process time required for the appropriate responses between motor execution and inhibition. However, there was no transcranial direct-current stimulation effect on the no-signal reaction time during the stop-signal task. Transcranial direct-current stimulation can adjust certain behaviors, and it could be a useful clinical intervention for patients who have difficulties with response inhibition. PMID:25206399

Is transcranial direct current stimulation a potential method for improving response inhibition?

PubMed

Kwon, Yong Hyun; Kwon, Jung Won

2013-04-15

Inhibitory control of movement in motor learning requires the ability to suppress an inappropriate action, a skill needed to stop a planned or ongoing motor response in response to changes in a variety of environments. This study used a stop-signal task to determine whether transcranial direct-current stimulation over the pre-supplementary motor area alters the reaction time in motor inhibition. Forty healthy subjects were recruited for this study and were randomly assigned to either the transcranial direct-current stimulation condition or a sham-transcranial direct-current stimulation condition. All subjects consecutively performed the stop-signal task before, during, and after the delivery of anodal transcranial direct-current stimulation over the pre-supplementary motor area (pre-transcranial direct-current stimulation phase, transcranial direct-current stimulation phase, and post-transcranial direct-current stimulation phase). Compared to the sham condition, there were significant reductions in the stop-signal processing times during and after transcranial direct-current stimulation, and change times were significantly greater in the transcranial direct-current stimulation condition. There was no significant change in go processing-times during or after transcranial direct-current stimulation in either condition. Anodal transcranial direct-current stimulation was feasibly coupled to an interactive improvement in inhibitory control. This coupling led to a decrease in the stop-signal process time required for the appropriate responses between motor execution and inhibition. However, there was no transcranial direct-current stimulation effect on the no-signal reaction time during the stop-signal task. Transcranial direct-current stimulation can adjust certain behaviors, and it could be a useful clinical intervention for patients who have difficulties with response inhibition.

Low cost MATLAB-based pulse oximeter for deployment in research and development applications.

PubMed

Shokouhian, M; Morling, R C S; Kale, I

2013-01-01

Problems such as motion artifact and effects of ambient lights have forced developers to design different signal processing techniques and algorithms to increase the reliability and accuracy of the conventional pulse oximeter device. To evaluate the robustness of these techniques, they are applied either to recorded data or are implemented on chip to be applied to real-time data. Recorded data is the most common method of evaluating however it is not as reliable as real-time measurements. On the other hand, hardware implementation can be both expensive and time consuming. This paper presents a low cost MATLAB-based pulse oximeter that can be used for rapid evaluation of newly developed signal processing techniques and algorithms. Flexibility to apply different signal processing techniques, providing both processed and unprocessed data along with low implementation cost are the important features of this design which makes it ideal for research and development purposes, as well as commercial, hospital and healthcare application.

Optical information-processing systems and architectures II; Proceedings of the Meeting, San Diego, CA, July 9-13, 1990

NASA Astrophysics Data System (ADS)

Javidi, Bahram

The present conference discusses topics in the fields of neural networks, acoustooptic signal processing, pattern recognition, phase-only processing, nonlinear signal processing, image processing, optical computing, and optical information processing. Attention is given to the optical implementation of an inner-product neural associative memory, optoelectronic associative recall via motionless-head/parallel-readout optical disk, a compact real-time acoustooptic image correlator, a multidimensional synthetic estimation filter, and a light-efficient joint transform optical correlator. Also discussed are a high-resolution spatial light modulator, compact real-time interferometric Fourier-transform processors, a fast decorrelation algorithm for permutation arrays, the optical interconnection of optical modules, and carry-free optical binary adders.

The Seismic Tool-Kit (STK): an open source software for seismology and signal processing.

NASA Astrophysics Data System (ADS)

Reymond, Dominique

2016-04-01

We present an open source software project (GNU public license), named STK: Seismic ToolKit, that is dedicated mainly for seismology and signal processing. The STK project that started in 2007, is hosted by SourceForge.net, and count more than 19 500 downloads at the date of writing. The STK project is composed of two main branches: First, a graphical interface dedicated to signal processing (in the SAC format (SAC_ASCII and SAC_BIN): where the signal can be plotted, zoomed, filtered, integrated, derivated, ... etc. (a large variety of IFR and FIR filter is proposed). The estimation of spectral density of the signal are performed via the Fourier transform, with visualization of the Power Spectral Density (PSD) in linear or log scale, and also the evolutive time-frequency representation (or sonagram). The 3-components signals can be also processed for estimating their polarization properties, either for a given window, or either for evolutive windows along the time. This polarization analysis is useful for extracting the polarized noises, differentiating P waves, Rayleigh waves, Love waves, ... etc. Secondly, a panel of Utilities-Program are proposed for working in a terminal mode, with basic programs for computing azimuth and distance in spherical geometry, inter/auto-correlation, spectral density, time-frequency for an entire directory of signals, focal planes, and main components axis, radiation pattern of P waves, Polarization analysis of different waves (including noize), under/over-sampling the signals, cubic-spline smoothing, and linear/non linear regression analysis of data set. A MINimum library of Linear AlGebra (MIN-LINAG) is also provided for computing the main matrix process like: QR/QL decomposition, Cholesky solve of linear system, finding eigen value/eigen vectors, QR-solve/Eigen-solve of linear equations systems ... etc. STK is developed in C/C++, mainly under Linux OS, and it has been also partially implemented under MS-Windows. Usefull links: http://sourceforge.net/projects/seismic-toolkit/ http://sourceforge.net/p/seismic-toolkit/wiki/browse_pages/

Relative timing: from behaviour to neurons

PubMed Central

Aghdaee, S. Mehdi; Battelli, Lorella; Assad, John A.

2014-01-01

Processing of temporal information is critical to behaviour. Here, we review the phenomenology and mechanism of relative timing, ordinal comparisons between the timing of occurrence of events. Relative timing can be an implicit component of particular brain computations or can be an explicit, conscious judgement. Psychophysical measurements of explicit relative timing have revealed clues about the interaction of sensory signals in the brain as well as in the influence of internal states, such as attention, on those interactions. Evidence from human neurophysiological and functional imaging studies, neuropsychological examination in brain-lesioned patients, and temporary disruptive interventions such as transcranial magnetic stimulation (TMS), point to a role of the parietal cortex in relative timing. Relative timing has traditionally been modelled as a ‘race’ between competing neural signals. We propose an updated race process based on the integration of sensory evidence towards a decision threshold rather than simple signal propagation. The model suggests a general approach for identifying brain regions involved in relative timing, based on looking for trial-by-trial correlations between neural activity and temporal order judgements (TOJs). Finally, we show how the paradigm can be used to reveal signals related to TOJs in parietal cortex of monkeys trained in a TOJ task. PMID:24446505

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

Unveiling the Biometric Potential of Finger-Based ECG Signals

PubMed Central

Lourenço, André; Silva, Hugo; Fred, Ana

2011-01-01

The ECG signal has been shown to contain relevant information for human identification. Even though results validate the potential of these signals, data acquisition methods and apparatus explored so far compromise user acceptability, requiring the acquisition of ECG at the chest. In this paper, we propose a finger-based ECG biometric system, that uses signals collected at the fingers, through a minimally intrusive 1-lead ECG setup recurring to Ag/AgCl electrodes without gel as interface with the skin. The collected signal is significantly more noisy than the ECG acquired at the chest, motivating the application of feature extraction and signal processing techniques to the problem. Time domain ECG signal processing is performed, which comprises the usual steps of filtering, peak detection, heartbeat waveform segmentation, and amplitude normalization, plus an additional step of time normalization. Through a simple minimum distance criterion between the test patterns and the enrollment database, results have revealed this to be a promising technique for biometric applications. PMID:21837235

Unveiling the biometric potential of finger-based ECG signals.

PubMed

Lourenço, André; Silva, Hugo; Fred, Ana

2011-01-01

The ECG signal has been shown to contain relevant information for human identification. Even though results validate the potential of these signals, data acquisition methods and apparatus explored so far compromise user acceptability, requiring the acquisition of ECG at the chest. In this paper, we propose a finger-based ECG biometric system, that uses signals collected at the fingers, through a minimally intrusive 1-lead ECG setup recurring to Ag/AgCl electrodes without gel as interface with the skin. The collected signal is significantly more noisy than the ECG acquired at the chest, motivating the application of feature extraction and signal processing techniques to the problem. Time domain ECG signal processing is performed, which comprises the usual steps of filtering, peak detection, heartbeat waveform segmentation, and amplitude normalization, plus an additional step of time normalization. Through a simple minimum distance criterion between the test patterns and the enrollment database, results have revealed this to be a promising technique for biometric applications.

Creep and slip: Seismic precursors to the Nuugaatsiaq landslide (Greenland)

NASA Astrophysics Data System (ADS)

Poli, Piero

2017-09-01

Precursory signals to material's failure are predicted by numerical models and observed in laboratory experiments or using field data. These precursory signals are a marker of slip acceleration on weak regions, such as crustal faults. Observation of these precursory signals of catastrophic natural events, such as earthquakes and landslides, is necessary for improving our knowledge about the physics of the nucleation process. Furthermore, observing such precursory signals may help to forecast these catastrophic events or reduce their hazard. I report here the observation of seismic precursors to the Nuugaatsiaq landslide in Greenland. Time evolution of the detected precursors implies that an aseismic slip event is taking place for hours before the landslide, with an exponential increase of slip velocity. Furthermore, time evolution of the precursory signals' amplitude sheds light on the evolution of the fault physics during the nucleation process.

Surface Electromyography Signal Processing and Classification Techniques

PubMed Central

Chowdhury, Rubana H.; Reaz, Mamun B. I.; Ali, Mohd Alauddin Bin Mohd; Bakar, Ashrif A. A.; Chellappan, Kalaivani; Chang, Tae. G.

2013-01-01

Electromyography (EMG) signals are becoming increasingly important in many applications, including clinical/biomedical, prosthesis or rehabilitation devices, human machine interactions, and more. However, noisy EMG signals are the major hurdles to be overcome in order to achieve improved performance in the above applications. Detection, processing and classification analysis in electromyography (EMG) is very desirable because it allows a more standardized and precise evaluation of the neurophysiological, rehabitational and assistive technological findings. This paper reviews two prominent areas; first: the pre-processing method for eliminating possible artifacts via appropriate preparation at the time of recording EMG signals, and second: a brief explanation of the different methods for processing and classifying EMG signals. This study then compares the numerous methods of analyzing EMG signals, in terms of their performance. The crux of this paper is to review the most recent developments and research studies related to the issues mentioned above. PMID:24048337

Real-Time EEG Signal Enhancement Using Canonical Correlation Analysis and Gaussian Mixture Clustering

PubMed Central

Huang, Chih-Sheng; Yang, Wen-Yu; Chuang, Chun-Hsiang; Wang, Yu-Kai

2018-01-01

Electroencephalogram (EEG) signals are usually contaminated with various artifacts, such as signal associated with muscle activity, eye movement, and body motion, which have a noncerebral origin. The amplitude of such artifacts is larger than that of the electrical activity of the brain, so they mask the cortical signals of interest, resulting in biased analysis and interpretation. Several blind source separation methods have been developed to remove artifacts from the EEG recordings. However, the iterative process for measuring separation within multichannel recordings is computationally intractable. Moreover, manually excluding the artifact components requires a time-consuming offline process. This work proposes a real-time artifact removal algorithm that is based on canonical correlation analysis (CCA), feature extraction, and the Gaussian mixture model (GMM) to improve the quality of EEG signals. The CCA was used to decompose EEG signals into components followed by feature extraction to extract representative features and GMM to cluster these features into groups to recognize and remove artifacts. The feasibility of the proposed algorithm was demonstrated by effectively removing artifacts caused by blinks, head/body movement, and chewing from EEG recordings while preserving the temporal and spectral characteristics of the signals that are important to cognitive research. PMID:29599950

Brain-computer interface signal processing at the Wadsworth Center: mu and sensorimotor beta rhythms.

PubMed

McFarland, Dennis J; Krusienski, Dean J; Wolpaw, Jonathan R

2006-01-01

The Wadsworth brain-computer interface (BCI), based on mu and beta sensorimotor rhythms, uses one- and two-dimensional cursor movement tasks and relies on user training. This is a real-time closed-loop system. Signal processing consists of channel selection, spatial filtering, and spectral analysis. Feature translation uses a regression approach and normalization. Adaptation occurs at several points in this process on the basis of different criteria and methods. It can use either feedforward (e.g., estimating the signal mean for normalization) or feedback control (e.g., estimating feature weights for the prediction equation). We view this process as the interaction between a dynamic user and a dynamic system that coadapt over time. Understanding the dynamics of this interaction and optimizing its performance represent a major challenge for BCI research.

Single photon laser altimeter simulator and statistical signal processing

NASA Astrophysics Data System (ADS)

Vacek, Michael; Prochazka, Ivan

2013-05-01

Spaceborne altimeters are common instruments onboard the deep space rendezvous spacecrafts. They provide range and topographic measurements critical in spacecraft navigation. Simultaneously, the receiver part may be utilized for Earth-to-satellite link, one way time transfer, and precise optical radiometry. The main advantage of single photon counting approach is the ability of processing signals with very low signal-to-noise ratio eliminating the need of large telescopes and high power laser source. Extremely small, rugged and compact microchip lasers can be employed. The major limiting factor, on the other hand, is the acquisition time needed to gather sufficient volume of data in repetitive measurements in order to process and evaluate the data appropriately. Statistical signal processing is adopted to detect signals with average strength much lower than one photon per measurement. A comprehensive simulator design and range signal processing algorithm are presented to identify a mission specific altimeter configuration. Typical mission scenarios (celestial body surface landing and topographical mapping) are simulated and evaluated. The high interest and promising single photon altimeter applications are low-orbit (˜10 km) and low-radial velocity (several m/s) topographical mapping (asteroids, Phobos and Deimos) and landing altimetry (˜10 km) where range evaluation repetition rates of ˜100 Hz and 0.1 m precision may be achieved. Moon landing and asteroid Itokawa topographical mapping scenario simulations are discussed in more detail.

Method and apparatus for signal processing in a sensor system for use in spectroscopy

DOEpatents

O'Connor, Paul [Bellport, NY; DeGeronimo, Gianluigi [Nesconset, NY; Grosholz, Joseph [Natrona Heights, PA

2008-05-27

A method for processing pulses arriving randomly in time on at least one channel using multiple peak detectors includes asynchronously selecting a non-busy peak detector (PD) in response to a pulse-generated trigger signal, connecting the channel to the selected PD in response to the trigger signal, and detecting a pulse peak amplitude. Amplitude and time of arrival data are output in first-in first-out (FIFO) sequence. An apparatus includes trigger comparators to generate the trigger signal for the pulse-receiving channel, PDs, a switch for connecting the channel to the selected PD, and logic circuitry which maintains the write pointer. Also included, time-to-amplitude converters (TACs) convert time of arrival to analog voltage and an analog multiplexer provides FIFO output. A multi-element sensor system for spectroscopy includes detector elements, channels, trigger comparators, PDs, a switch, and a logic circuit with asynchronous write pointer. The system includes TACs, a multiplexer and analog-to-digital converter.

Two-dimensional signal processing with application to image restoration

NASA Technical Reports Server (NTRS)

Assefi, T.

1974-01-01

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

Interferometer with Continuously Varying Path Length Measured in Wavelengths to the Reference Mirror

NASA Technical Reports Server (NTRS)

Ohara, Tetsuo (Inventor)

2016-01-01

An interferometer in which the path length of the reference beam, measured in wavelengths, is continuously changing in sinusoidal fashion and the interference signal created by combining the measurement beam and the reference beam is processed in real time to obtain the physical distance along the measurement beam between the measured surface and a spatial reference frame such as the beam splitter. The processing involves analyzing the Fourier series of the intensity signal at one or more optical detectors in real time and using the time-domain multi-frequency harmonic signals to extract the phase information independently at each pixel position of one or more optical detectors and converting the phase information to distance information.

Functional description of signal processing in the Rogue GPS receiver

NASA Technical Reports Server (NTRS)

Thomas, J. B.

1988-01-01

Over the past year, two Rogue GPS prototype receivers have been assembled and successfully subjected to a variety of laboratory and field tests. A functional description is presented of signal processing in the Rogue receiver, tracing the signal from RF input to the output values of group delay, phase, and data bits. The receiver can track up to eight satellites, without time multiplexing among satellites or channels, simultaneously measuring both group delay and phase for each of three channels (L1-C/A, L1-P, L2-P). The Rogue signal processing described requires generation of the code for all three channels. Receiver functional design, which emphasized accuracy, reliability, flexibility, and dynamic capability, is summarized. A detailed functional description of signal processing is presented, including C/A-channel and P-channel processing, carrier-aided averaging of group delays, checks for cycle slips, acquistion, and distinctive features.

Imaging synthetic aperture radar

DOEpatents

Burns, Bryan L.; Cordaro, J. Thomas

1997-01-01

A linear-FM SAR imaging radar method and apparatus to produce a real-time image by first arranging the returned signals into a plurality of subaperture arrays, the columns of each subaperture array having samples of dechirped baseband pulses, and further including a processing of each subaperture array to obtain coarse-resolution in azimuth, then fine-resolution in range, and lastly, to combine the processed subapertures to obtain the final fine-resolution in azimuth. Greater efficiency is achieved because both the transmitted signal and a local oscillator signal mixed with the returned signal can be varied on a pulse-to-pulse basis as a function of radar motion. Moreover, a novel circuit can adjust the sampling location and the A/D sample rate of the combined dechirped baseband signal which greatly reduces processing time and hardware. The processing steps include implementing a window function, stabilizing either a central reference point and/or all other points of a subaperture with respect to doppler frequency and/or range as a function of radar motion, sorting and compressing the signals using a standard fourier transforms. The stabilization of each processing part is accomplished with vector multiplication using waveforms generated as a function of radar motion wherein these waveforms may be synthesized in integrated circuits. Stabilization of range migration as a function of doppler frequency by simple vector multiplication is a particularly useful feature of the invention; as is stabilization of azimuth migration by correcting for spatially varying phase errors prior to the application of an autofocus process.

Digital seismo-acoustic signal processing aboard a wireless sensor platform

NASA Astrophysics Data System (ADS)

Marcillo, O.; Johnson, J. B.; Lorincz, K.; Werner-Allen, G.; Welsh, M.

2006-12-01

We are developing a low power, low-cost wireless sensor array to conduct real-time signal processing of earthquakes at active volcanoes. The sensor array, which integrates data from both seismic and acoustic sensors, is based on Moteiv TMote Sky wireless sensor nodes (www.moteiv.com). The nodes feature a Texas Instruments MSP430 microcontroller, 48 Kbytes of program memory, 10 Kbytes of static RAM, 1 Mbyte of external flash memory, and a 2.4-GHz Chipcon CC2420 IEEE 802.15.4 radio. The TMote Sky is programmed in TinyOS. Basic signal processing occurs on an array of three peripheral sensor nodes. These nodes are tied into a dedicated GPS receiver node, which is focused on time synchronization, and a central communications node, which handles data integration and additional processing. The sensor nodes incorporate dual 12-bit digitizers sampling a seismic sensor and a pressure transducer at 100 samples per second. The wireless capabilities of the system allow flexible array geometry, with a maximum aperture of 200m. We have already developed the digital signal processing routines on board the Moteiv Tmote sensor nodes. The developed routines accomplish Real-time Seismic-Amplitude Measurement (RSAM), Seismic Spectral- Amplitude Measurement (SSAM), and a user-configured Short Term Averaging / Long Term Averaging (STA LTA ratio), which is used to calculate first arrivals. The processed data from individual nodes are transmitted back to a central node, where additional processing may be performed. Such processing will include back azimuth determination and other wave field analyses. Future on-board signal processing will focus on event characterization utilizing pattern recognition and spectral characterization. The processed data is intended as low bandwidth information which can be transmitted periodically and at low cost through satellite telemetry to a web server. The processing is limited by the computational capabilities (RAM, ROM) of the nodes. Nevertheless, we envision this product to be a useful tool for assessing the state of unrest at remote volcanoes.

Real Time Implementation of an LPC Algorithm. Speech Signal Processing Research at CHI

DTIC Science & Technology

1975-05-01

SIGNAL PROCESSING HARDWARE 2-1 2.1 INTRODUCTION 2-1 2.2 TWO- CHANNEL AUDIO SIGNAL SYSTEM 2-2 2.3 MULTI- CHANNEL AUDIO SIGNAL SYSTEM 2-5 2.3.1... Channel Audio Signal System 2-30 I ii kv^i^ünt«.jfc*. ji .„* ,:-v*. ’.ii. *.. ...... — ■ -,,.,-c-» —ipponp ■^ TOHaBWgBpwiBWgPlpaiPWgW v.«.wN...Messages .... 1-55 1-13. Lost or Out of Order Message 1-56 2-1. Block Diagram of Two- Channel Audio Signal System . . 2-3 2-2. Block Diagram of Audio

Process observation in fiber laser-based selective laser melting

NASA Astrophysics Data System (ADS)

Thombansen, Ulrich; Gatej, Alexander; Pereira, Milton

2015-01-01

The process observation in selective laser melting (SLM) focuses on observing the interaction point where the powder is processed. To provide process relevant information, signals have to be acquired that are resolved in both time and space. Especially in high-power SLM, where more than 1 kW of laser power is used, processing speeds of several meters per second are required for a high-quality processing results. Therefore, an implementation of a suitable process observation system has to acquire a large amount of spatially resolved data at low sampling speeds or it has to restrict the acquisition to a predefined area at a high sampling speed. In any case, it is vitally important to synchronously record the laser beam position and the acquired signal. This is a prerequisite that allows the recorded data become information. Today, most SLM systems employ f-theta lenses to focus the processing laser beam onto the powder bed. This report describes the drawbacks that result for process observation and suggests a variable retro-focus system which solves these issues. The beam quality of fiber lasers delivers the processing laser beam to the powder bed at relevant focus diameters, which is a key prerequisite for this solution to be viable. The optical train we present here couples the processing laser beam and the process observation coaxially, ensuring consistent alignment of interaction zone and observed area. With respect to signal processing, we have developed a solution that synchronously acquires signals from a pyrometer and the position of the laser beam by sampling the data with a field programmable gate array. The relevance of the acquired signals has been validated by the scanning of a sample filament. Experiments with grooved samples show a correlation between different powder thicknesses and the acquired signals at relevant processing parameters. This basic work takes a first step toward self-optimization of the manufacturing process in SLM. It enables the addition of cognitive functions to the manufacturing system to the extent that the system could track its own process. The results are based on analyzing and redesigning the optical train, in combination with a real-time signal acquisition system which provides a solution to certain technological barriers.

Overview of the DART project

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

Berry, K.R.; Hansen, F.R.; Napolitano, L.M.

1992-01-01

DART (DSP Arrary for Reconfigurable Tasks) is a parallel architecture of two high-performance SDP (digital signal processing) chips with the flexibility to handle a wide range of real-time applications. Each of the 32-bit floating-point DSP processes in DART is programmable in a high-level languate ( C'' or Ada). We have added extensions to the real-time operating system used by DART in order to support parallel processor. The combination of high-level language programmability, a real-time operating system, and parallel processing support significantly reduces the development cost of application software for signal processing and control applications. We have demonstrated this capability bymore » using DART to reconstruct images in the prototype VIP (Video Imaging Projectile) groundstation.« less

Overview of the DART project

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

Berry, K.R.; Hansen, F.R.; Napolitano, L.M.

1992-01-01

DART (DSP Arrary for Reconfigurable Tasks) is a parallel architecture of two high-performance SDP (digital signal processing) chips with the flexibility to handle a wide range of real-time applications. Each of the 32-bit floating-point DSP processes in DART is programmable in a high-level languate (``C`` or Ada). We have added extensions to the real-time operating system used by DART in order to support parallel processor. The combination of high-level language programmability, a real-time operating system, and parallel processing support significantly reduces the development cost of application software for signal processing and control applications. We have demonstrated this capability by usingmore » DART to reconstruct images in the prototype VIP (Video Imaging Projectile) groundstation.« less

Time-frequency analysis of acoustic signals in the audio-frequency range generated during Hadfield's steel friction

NASA Astrophysics Data System (ADS)

Dobrynin, S. A.; Kolubaev, E. A.; Smolin, A. Yu.; Dmitriev, A. I.; Psakhie, S. G.

2010-07-01

Time-frequency analysis of sound waves detected by a microphone during the friction of Hadfield’s steel has been performed using wavelet transform and window Fourier transform methods. This approach reveals a relationship between the appearance of quasi-periodic intensity outbursts in the acoustic response signals and the processes responsible for the formation of wear products. It is shown that the time-frequency analysis of acoustic emission in a tribosystem can be applied, along with traditional approaches, to studying features in the wear and friction process.

Optical fiber sensor technique for strain measurement

DOEpatents

Butler, Michael A.; Ginley, David S.

1989-01-01

Laser light from a common source is split and conveyed through two similar optical fibers and emitted at their respective ends to form an interference pattern, one of the optical fibers having a portion thereof subjected to a strain. Changes in the strain cause changes in the optical path length of the strain fiber, and generate corresponding changes in the interference pattern. The interference pattern is received and transduced into signals representative of fringe shifts corresponding to changes in the strain experienced by the strained one of the optical fibers. These signals are then processed to evaluate strain as a function of time, typical examples of the application of the apparatus including electrodeposition of a metallic film on a conductive surface provided on the outside of the optical fiber being strained, so that strains generated in the optical fiber during the course of the electrodeposition are measurable as a function of time. In one aspect of the invention, signals relating to the fringe shift are stored for subsequent processing and analysis, whereas in another aspect of the invention the signals are processed for real-time display of the strain changes under study.

Seismpol_ a visual-basic computer program for interactive and automatic earthquake waveform analysis

NASA Astrophysics Data System (ADS)

Patanè, Domenico; Ferrari, Ferruccio

1997-11-01

A Microsoft Visual-Basic computer program for waveform analysis of seismic signals is presented. The program combines interactive and automatic processing of digital signals using data recorded by three-component seismic stations. The analysis procedure can be used in either an interactive earthquake analysis or an automatic on-line processing of seismic recordings. The algorithm works in the time domain using the Covariance Matrix Decomposition method (CMD), so that polarization characteristics may be computed continuously in real time and seismic phases can be identified and discriminated. Visual inspection of the particle motion in hortogonal planes of projection (hodograms) reduces the danger of misinterpretation derived from the application of the polarization filter. The choice of time window and frequency intervals improves the quality of the extracted polarization information. In fact, the program uses a band-pass Butterworth filter to process the signals in the frequency domain by analysis of a selected signal window into a series of narrow frequency bands. Significant results supported by well defined polarizations and source azimuth estimates for P and S phases are also obtained for short-period seismic events (local microearthquakes).

Super-Resolution of Multi-Pixel and Sub-Pixel Images for the SDI

DTIC Science & Technology

1993-06-08

where the phase of the transmitted signal is not needed. The Wigner - Ville distribution ( WVD ) of a real signal s(t), associated with the complex...B. Boashash, 0. P. Kenny and H. J. Whitehouse, "Radar imaging using the Wigner - Ville distribution ", in Real-Time Signal Processing, J. P. Letellier...analytic signal z(t), is a time- frequency distribution defined as-’- 00 W(tf) Z (~t + ) t- -)exp(-i2nft) . (45) Note that the WVD is the double Fourier

A fast discrete S-transform for biomedical signal processing.

PubMed

Brown, Robert A; Frayne, Richard

2008-01-01

Determining the frequency content of a signal is a basic operation in signal and image processing. The S-transform provides both the true frequency and globally referenced phase measurements characteristic of the Fourier transform and also generates local spectra, as does the wavelet transform. Due to this combination, the S-transform has been successfully demonstrated in a variety of biomedical signal and image processing tasks. However, the computational demands of the S-transform have limited its application in medicine to this point in time. This abstract introduces the fast S-transform, a more efficient discrete implementation of the classic S-transform with dramatically reduced computational requirements.

Signal propagation in cortical networks: a digital signal processing approach.

PubMed

Rodrigues, Francisco Aparecido; da Fontoura Costa, Luciano

2009-01-01

This work reports a digital signal processing approach to representing and modeling transmission and combination of signals in cortical networks. The signal dynamics is modeled in terms of diffusion, which allows the information processing undergone between any pair of nodes to be fully characterized in terms of a finite impulse response (FIR) filter. Diffusion without and with time decay are investigated. All filters underlying the cat and macaque cortical organization are found to be of low-pass nature, allowing the cortical signal processing to be summarized in terms of the respective cutoff frequencies (a high cutoff frequency meaning little alteration of signals through their intermixing). Several findings are reported and discussed, including the fact that the incorporation of temporal activity decay tends to provide more diversified cutoff frequencies. Different filtering intensity is observed for each community in those networks. In addition, the brain regions involved in object recognition tend to present the highest cutoff frequencies for both the cat and macaque networks.

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).

A real-time spike sorting method based on the embedded GPU.

PubMed

Zelan Yang; Kedi Xu; Xiang Tian; Shaomin Zhang; Xiaoxiang Zheng

2017-07-01

Microelectrode arrays with hundreds of channels have been widely used to acquire neuron population signals in neuroscience studies. Online spike sorting is becoming one of the most important challenges for high-throughput neural signal acquisition systems. Graphic processing unit (GPU) with high parallel computing capability might provide an alternative solution for increasing real-time computational demands on spike sorting. This study reported a method of real-time spike sorting through computing unified device architecture (CUDA) which was implemented on an embedded GPU (NVIDIA JETSON Tegra K1, TK1). The sorting approach is based on the principal component analysis (PCA) and K-means. By analyzing the parallelism of each process, the method was further optimized in the thread memory model of GPU. Our results showed that the GPU-based classifier on TK1 is 37.92 times faster than the MATLAB-based classifier on PC while their accuracies were the same with each other. The high-performance computing features of embedded GPU demonstrated in our studies suggested that the embedded GPU provide a promising platform for the real-time neural signal processing.

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

NASA Technical Reports Server (NTRS)

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

1986-01-01

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

System for monitoring an industrial process and determining sensor status

DOEpatents

Gross, K.C.; Hoyer, K.K.; Humenik, K.E.

1995-10-17

A method and system for monitoring an industrial process and a sensor are disclosed. The method and system include generating a first and second signal characteristic of an industrial process variable. One of the signals can be an artificial signal generated by an auto regressive moving average technique. After obtaining two signals associated with one physical variable, a difference function is obtained by determining the arithmetic difference between the two pairs of signals over time. A frequency domain transformation is made of the difference function to obtain Fourier modes describing a composite function. A residual function is obtained by subtracting the composite function from the difference function and the residual function (free of nonwhite noise) is analyzed by a statistical probability ratio test. 17 figs.

System for monitoring an industrial process and determining sensor status

DOEpatents

Gross, K.C.; Hoyer, K.K.; Humenik, K.E.

1997-05-13

A method and system are disclosed for monitoring an industrial process and a sensor. The method and system include generating a first and second signal characteristic of an industrial process variable. One of the signals can be an artificial signal generated by an auto regressive moving average technique. After obtaining two signals associated with one physical variable, a difference function is obtained by determining the arithmetic difference between the two pairs of signals over time. A frequency domain transformation is made of the difference function to obtain Fourier modes describing a composite function. A residual function is obtained by subtracting the composite function from the difference function and the residual function (free of nonwhite noise) is analyzed by a statistical probability ratio test. 17 figs.

System for monitoring an industrial process and determining sensor status

DOEpatents

Gross, Kenneth C.; Hoyer, Kristin K.; Humenik, Keith E.

1995-01-01

A method and system for monitoring an industrial process and a sensor. The method and system include generating a first and second signal characteristic of an industrial process variable. One of the signals can be an artificial signal generated by an auto regressive moving average technique. After obtaining two signals associated with one physical variable, a difference function is obtained by determining the arithmetic difference between the two pairs of signals over time. A frequency domain transformation is made of the difference function to obtain Fourier modes describing a composite function. A residual function is obtained by subtracting the composite function from the difference function and the residual function (free of nonwhite noise) is analyzed by a statistical probability ratio test.

System for monitoring an industrial process and determining sensor status

DOEpatents

Gross, Kenneth C.; Hoyer, Kristin K.; Humenik, Keith E.

1997-01-01

A method and system for monitoring an industrial process and a sensor. The method and system include generating a first and second signal characteristic of an industrial process variable. One of the signals can be an artificial signal generated by an auto regressive moving average technique. After obtaining two signals associated with one physical variable, a difference function is obtained by determining the arithmetic difference between the two pairs of signals over time. A frequency domain transformation is made of the difference function to obtain Fourier modes describing a composite function. A residual function is obtained by subtracting the composite function from the difference function and the residual function (free of nonwhite noise) is analyzed by a statistical probability ratio test.

System For Surveillance Of Spectral Signals

DOEpatents

Gross, Kenneth C.; Wegerich, Stephan W.; Criss-Puszkiewicz, Cynthia; Wilks, Alan D.

2004-10-12

A method and system for monitoring at least one of a system, a process and a data source. A method and system have been developed for carrying out surveillance, testing and modification of an ongoing process or other source of data, such as a spectroscopic examination. A signal from the system under surveillance is collected and compared with a reference signal, a frequency domain transformation carried out for the system signal and reference signal, a frequency domain difference function established. The process is then repeated until a full range of data is accumulated over the time domain and a Sequential Probability Ratio Test ("SPRT") methodology applied to determine a three-dimensional surface plot characteristic of the operating state of the system under surveillance.

System For Surveillance Of Spectral Signals

DOEpatents

Gross, Kenneth C.; Wegerich, Stephan; Criss-Puszkiewicz, Cynthia; Wilks, Alan D.

2003-04-22

A method and system for monitoring at least one of a system, a process and a data source. A method and system have been developed for carrying out surveillance, testing and modification of an ongoing process or other source of data, such as a spectroscopic examination. A signal from the system under surveillance is collected and compared with a reference signal, a frequency domain transformation carried out for the system signal and reference signal, a frequency domain difference function established. The process is then repeated until a full range of data is accumulated over the time domain and a Sequential Probability Ratio Test methodology applied to determine a three-dimensional surface plot characteristic of the operating state of the system under surveillance.

System for surveillance of spectral signals

DOEpatents

Gross, Kenneth C.; Wegerich, Stephan W.; Criss-Puszkiewicz, Cynthia; Wilks, Alan D.

2006-02-14

A method and system for monitoring at least one of a system, a process and a data source. A method and system have been developed for carrying out surveillance, testing and modification of an ongoing process or other source of data, such as a spectroscopic examination. A signal from the system under surveillance is collected and compared with a reference signal, a frequency domain transformation carried out for the system signal and reference signal, a frequency domain difference function established. The process is then repeated until a full range of data is accumulated over the time domain and a Sequential Probability Ratio Test ("SPRT") methodology applied to determine a three-dimensional surface plot characteristic of the operating state of the system under surveillance.

System for surveillance of spectral signals

DOEpatents

Gross, Kenneth C.; Wegerich, Stephan W.; Criss-Puszkiewicz, Cynthia; Wilks, Alan D.

2001-01-01

A method and system for monitoring at least one of a system, a process and a data source. A method and system have been developed for carrying out surveillance, testing and modification of an ongoing process or other source of data, such as a spectroscopic examination. A signal from the system under surveillance is collected and compared with a reference signal, a frequency domain transformation carried out for the system signal and reference signal, a frequency domain difference function established. The process is then repeated until a full range of data is accumulated over the time domain and a SPRT sequential probability ratio test methodology applied to determine a three-dimensional surface plot characteristic of the operating state of the system under surveillance.

Nonlinear Real-Time Optical Signal Processing.

DTIC Science & Technology

1984-10-01

I 1.8 IIII III1 1 / U , 0 7 USCIPI Report 1130 E ~C~,OUTfitA N Ivj) UNIVERSITY OF SOUTHERN CALIFORNIA - I FINAL TECHNICAL REPORT April 15, 1981 - June...30, 1984 N NONLINEAR REAL-TIME OPTICAL SIGNAL PROCESSING i E ~ A.A. Sawchuk, Principal Investigator T.C. Strand and A.R. Tanguay. Jr. October 1, 1984...Erter.d) logic system. A computer generated hologram fabricated on an e -beam system serves as a beamsteering interconnection element. A completely

A Baseline-Free Defect Imaging Technique in Plates Using Time Reversal of Lamb Waves

NASA Astrophysics Data System (ADS)

Hyunjo, Jeong; Sungjong, Cho; Wei, Wei

2011-06-01

We present an analytical investigation for a baseline-free imaging of a defect in plate-like structures using the time-reversal of Lamb waves. We first consider the flexural wave (A0 mode) propagation in a plate containing a defect, and reception and time reversal process of the output signal at the receiver. The received output signal is then composed of two parts: a directly propagated wave and a scattered wave from the defect. The time reversal of these waves recovers the original input signal, and produces two additional sidebands that contain the time-of-flight information on the defect location. One of the side-band signals is then extracted as a pure defect signal. A defect localization image is then constructed from a beamforming technique based on the time-frequency analysis of the side band signal for each transducer pair in a network of sensors. The simulation results show that the proposed scheme enables the accurate, baseline-free imaging of a defect.

Time-delayed directional beam phased array antenna

DOEpatents

Fund, Douglas Eugene; Cable, John William; Cecil, Tony Myron

2004-10-19

An antenna comprising a phased array of quadrifilar helix or other multifilar antenna elements and a time-delaying feed network adapted to feed the elements. The feed network can employ a plurality of coaxial cables that physically bridge a microstrip feed circuitry to feed power signals to the elements. The cables provide an incremental time delay which is related to their physical lengths, such that replacing cables having a first set of lengths with cables having a second set of lengths functions to change the time delay and shift or steer the antenna's main beam. Alternatively, the coaxial cables may be replaced with a programmable signal processor unit adapted to introduce the time delay using signal processing techniques applied to the power signals.

Signal processing method and system for noise removal and signal extraction

DOEpatents

Fu, Chi Yung; Petrich, Loren

2009-04-14

A signal processing method and system combining smooth level wavelet pre-processing together with artificial neural networks all in the wavelet domain for signal denoising and extraction. Upon receiving a signal corrupted with noise, an n-level decomposition of the signal is performed using a discrete wavelet transform to produce a smooth component and a rough component for each decomposition level. The n.sup.th level smooth component is then inputted into a corresponding neural network pre-trained to filter out noise in that component by pattern recognition in the wavelet domain. Additional rough components, beginning at the highest level, may also be retained and inputted into corresponding neural networks pre-trained to filter out noise in those components also by pattern recognition in the wavelet domain. In any case, an inverse discrete wavelet transform is performed on the combined output from all the neural networks to recover a clean signal back in the time domain.

Tracking radar advanced signal processing and computing for Kwajalein Atoll (KA) application

NASA Astrophysics Data System (ADS)

Cottrill, Stanley D.

1992-11-01

Two means are examined whereby the operations of KMR during mission execution may be improved through the introduction of advanced signal processing techniques. In the first approach, the addition of real time coherent signal processing technology to the FPQ-19 radar is considered. In the second approach, the incorporation of the MMW radar, with its very fine range precision, to the MMS system is considered. The former appears very attractive and a Phase 2 SBIR has been proposed. The latter does not appear promising enough to warrant further development.

Improving EEG-Based Motor Imagery Classification for Real-Time Applications Using the QSA Method.

PubMed

Batres-Mendoza, Patricia; Ibarra-Manzano, Mario A; Guerra-Hernandez, Erick I; Almanza-Ojeda, Dora L; Montoro-Sanjose, Carlos R; Romero-Troncoso, Rene J; Rostro-Gonzalez, Horacio

2017-01-01

We present an improvement to the quaternion-based signal analysis (QSA) technique to extract electroencephalography (EEG) signal features with a view to developing real-time applications, particularly in motor imagery (IM) cognitive processes. The proposed methodology (iQSA, improved QSA) extracts features such as the average, variance, homogeneity, and contrast of EEG signals related to motor imagery in a more efficient manner (i.e., by reducing the number of samples needed to classify the signal and improving the classification percentage) compared to the original QSA technique. Specifically, we can sample the signal in variable time periods (from 0.5 s to 3 s, in half-a-second intervals) to determine the relationship between the number of samples and their effectiveness in classifying signals. In addition, to strengthen the classification process a number of boosting-technique-based decision trees were implemented. The results show an 82.30% accuracy rate for 0.5 s samples and 73.16% for 3 s samples. This is a significant improvement compared to the original QSA technique that offered results from 33.31% to 40.82% without sampling window and from 33.44% to 41.07% with sampling window, respectively. We can thus conclude that iQSA is better suited to develop real-time applications.

Improving EEG-Based Motor Imagery Classification for Real-Time Applications Using the QSA Method

PubMed Central

Batres-Mendoza, Patricia; Guerra-Hernandez, Erick I.; Almanza-Ojeda, Dora L.; Montoro-Sanjose, Carlos R.

2017-01-01

We present an improvement to the quaternion-based signal analysis (QSA) technique to extract electroencephalography (EEG) signal features with a view to developing real-time applications, particularly in motor imagery (IM) cognitive processes. The proposed methodology (iQSA, improved QSA) extracts features such as the average, variance, homogeneity, and contrast of EEG signals related to motor imagery in a more efficient manner (i.e., by reducing the number of samples needed to classify the signal and improving the classification percentage) compared to the original QSA technique. Specifically, we can sample the signal in variable time periods (from 0.5 s to 3 s, in half-a-second intervals) to determine the relationship between the number of samples and their effectiveness in classifying signals. In addition, to strengthen the classification process a number of boosting-technique-based decision trees were implemented. The results show an 82.30% accuracy rate for 0.5 s samples and 73.16% for 3 s samples. This is a significant improvement compared to the original QSA technique that offered results from 33.31% to 40.82% without sampling window and from 33.44% to 41.07% with sampling window, respectively. We can thus conclude that iQSA is better suited to develop real-time applications. PMID:29348744

Digital methods of recording color television images on film tape

NASA Astrophysics Data System (ADS)

Krivitskaya, R. Y.; Semenov, V. M.

1985-04-01

Three methods are now available for recording color television images on film tape, directly or after appropriate finish of signal processing. Conventional recording of images from the screens of three kinescopes with synthetic crystal face plates is still most effective for high fidelity. This method was improved by digital preprocessing of brightness color-difference signal. Frame-by-frame storage of these signals in the memory in digital form is followed by gamma and aperture correction and electronic correction of crossover distortions in the color layers of the film with fixing in accordance with specific emulsion procedures. The newer method of recording color television images with line arrays of light-emitting diodes involves dichromic superposing mirrors and a movable scanning mirror. This method allows the use of standard movie cameras, simplifies interlacing-to-linewise conversion and the mechanical equipment, and lengthens exposure time while it shortens recording time. The latest image transform method requires an audio-video recorder, a memory disk, a digital computer, and a decoder. The 9-step procedure includes preprocessing the total color television signal with reduction of noise level and time errors, followed by frame frequency conversion and setting the number of lines. The total signal is then resolved into its brightness and color-difference components and phase errors and image blurring are also reduced. After extraction of R,G,B signals and colorimetric matching of TV camera and film tape, the simultaneous R,B, B signals are converted from interlacing to sequential triades of color-quotient frames with linewise scanning at triple frequency. Color-quotient signals are recorded with an electron beam on a smoothly moving black-and-white film tape under vacuum. While digital techniques improve the signal quality and simplify the control of processes, not requiring stabilization of circuits, image processing is still analog.

Biosensor method and system based on feature vector extraction

DOEpatents

Greenbaum, Elias; Rodriguez, Jr., Miguel; Qi, Hairong; Wang, Xiaoling

2013-07-02

A system for biosensor-based detection of toxins includes providing at least one time-dependent control signal generated by a biosensor in a gas or liquid medium, and obtaining a time-dependent biosensor signal from the biosensor in the gas or liquid medium to be monitored or analyzed for the presence of one or more toxins selected from chemical, biological or radiological agents. The time-dependent biosensor signal is processed to obtain a plurality of feature vectors using at least one of amplitude statistics and a time-frequency analysis. At least one parameter relating to toxicity of the gas or liquid medium is then determined from the feature vectors based on reference to the control signal.

Impact of Software Settings on Multiple-Breath Washout Outcomes.

PubMed

Summermatter, Selina; Singer, Florian; Latzin, Philipp; Yammine, Sophie

2015-01-01

Multiple-breath washout (MBW) is an attractive test to assess ventilation inhomogeneity, a marker of peripheral lung disease. Standardization of MBW is hampered as little data exists on possible measurement bias. We aimed to identify potential sources of measurement bias based on MBW software settings. We used unprocessed data from nitrogen (N2) MBW (Exhalyzer D, Eco Medics AG) applied in 30 children aged 5-18 years: 10 with CF, 10 formerly preterm, and 10 healthy controls. This setup calculates the tracer gas N2 mainly from measured O2 and CO2concentrations. The following software settings for MBW signal processing were changed by at least 5 units or >10% in both directions or completely switched off: (i) environmental conditions, (ii) apparatus dead space, (iii) O2 and CO2 signal correction, and (iv) signal alignment (delay time). Primary outcome was the change in lung clearance index (LCI) compared to LCI calculated with the settings as recommended. A change in LCI exceeding 10% was considered relevant. Changes in both environmental and dead space settings resulted in uniform but modest LCI changes and exceeded >10% in only two measurements. Changes in signal alignment and O2 signal correction had the most relevant impact on LCI. Decrease of O2 delay time by 40 ms (7%) lead to a mean LCI increase of 12%, with >10% LCI change in 60% of the children. Increase of O2 delay time by 40 ms resulted in mean LCI decrease of 9% with LCI changing >10% in 43% of the children. Accurate LCI results depend crucially on signal processing settings in MBW software. Especially correct signal delay times are possible sources of incorrect LCI measurements. Algorithms of signal processing and signal alignment should thus be optimized to avoid susceptibility of MBW measurements to this significant measurement bias.

The Seismic Tool-Kit (STK): An Open Source Software For Learning the Basis of Signal Processing and Seismology.

NASA Astrophysics Data System (ADS)

Reymond, D.

2016-12-01

We present an open source software project (GNU public license), named STK: Seismic Tool-Kit, that is dedicated mainly for learning signal processing and seismology. The STK project that started in 2007, is hosted by SourceForge.net, and count more than 20000 downloads at the date of writing.The STK project is composed of two main branches:First, a graphical interface dedicated to signal processing (in the SAC format (SAC_ASCII and SAC_BIN): where the signal can be plotted, zoomed, filtered, integrated, derivated, ... etc. (a large variety of IFR and FIR filter is proposed). The passage in the frequency domain via the Fourier transform is used to introduce the estimation of spectral density of the signal , with visualization of the Power Spectral Density (PSD) in linear or log scale, and also the evolutive time-frequency representation (or sonagram). The 3-components signals can be also processed for estimating their polarization properties, either for a given window, or either for evolutive windows along the time. This polarization analysis is useful for extracting the polarized noises, differentiating P waves, Rayleigh waves, Love waves, ... etc. Secondly, a panel of Utilities-Program are proposed for working in a terminal mode, with basic programs for computing azimuth and distance in spherical geometry, inter/auto-correlation, spectral density, time-frequency for an entire directory of signals, focal planes, and main components axis, radiation pattern of P waves, Polarization analysis of different waves (including noise), under/over-sampling the signals, cubic-spline smoothing, and linear/non linear regression analysis of data set. STK is developed in C/C++, mainly under Linux OS, and it has been also partially implemented under MS-Windows. STK has been used in some schools for viewing and plotting seismic records provided by IRIS, and it has been used as a practical support for teaching the basis of signal processing. Useful links:http://sourceforge.net/projects/seismic-toolkit/http://sourceforge.net/p/seismic-toolkit/wiki/browse_pages/

The Vector, Signal, and Image Processing Library (VSIPL): an Open Standard for Astronomical Data Processing

NASA Astrophysics Data System (ADS)

Kepner, J. V.; Janka, R. S.; Lebak, J.; Richards, M. A.

1999-12-01

The Vector/Signal/Image Processing Library (VSIPL) is a DARPA initiated effort made up of industry, government and academic representatives who have defined an industry standard API for vector, signal, and image processing primitives for real-time signal processing on high performance systems. VSIPL supports a wide range of data types (int, float, complex, ...) and layouts (vectors, matrices and tensors) and is ideal for astronomical data processing. The VSIPL API is intended to serve as an open, vendor-neutral, industry standard interface. The object-based VSIPL API abstracts the memory architecture of the underlying machine by using the concept of memory blocks and views. Early experiments with VSIPL code conversions have been carried out by the High Performance Computing Program team at the UCSD. Commercially, several major vendors of signal processors are actively developing implementations. VSIPL has also been explicitly required as part of a recent Rome Labs teraflop procurement. This poster presents the VSIPL API, its functionality and the status of various implementations.

Time-frequency representation of a highly nonstationary signal via the modified Wigner distribution

NASA Technical Reports Server (NTRS)

Zoladz, T. F.; Jones, J. H.; Jong, J.

1992-01-01

A new signal analysis technique called the modified Wigner distribution (MWD) is presented. The new signal processing tool has been very successful in determining time frequency representations of highly non-stationary multicomponent signals in both simulations and trials involving actual Space Shuttle Main Engine (SSME) high frequency data. The MWD departs from the classic Wigner distribution (WD) in that it effectively eliminates the cross coupling among positive frequency components in a multiple component signal. This attribute of the MWD, which prevents the generation of 'phantom' spectral peaks, will undoubtedly increase the utility of the WD for real world signal analysis applications which more often than not involve multicomponent signals.

Platform for Post-Processing Waveform-Based NDE

NASA Technical Reports Server (NTRS)

Roth, Don J.

2010-01-01

Signal- and image-processing methods are commonly needed to extract information from the waves, improve resolution of, and highlight defects in an image. Since some similarity exists for all waveform-based nondestructive evaluation (NDE) methods, it would seem that a common software platform containing multiple signal- and image-processing techniques to process the waveforms and images makes sense where multiple techniques, scientists, engineers, and organizations are involved. NDE Wave & Image Processor Version 2.0 software provides a single, integrated signal- and image-processing and analysis environment for total NDE data processing and analysis. It brings some of the most useful algorithms developed for NDE over the past 20 years into a commercial-grade product. The software can import signal/spectroscopic data, image data, and image series data. This software offers the user hundreds of basic and advanced signal- and image-processing capabilities including esoteric 1D and 2D wavelet-based de-noising, de-trending, and filtering. Batch processing is included for signal- and image-processing capability so that an optimized sequence of processing operations can be applied to entire folders of signals, spectra, and images. Additionally, an extensive interactive model-based curve-fitting facility has been included to allow fitting of spectroscopy data such as from Raman spectroscopy. An extensive joint-time frequency module is included for analysis of non-stationary or transient data such as that from acoustic emission, vibration, or earthquake data.

RSRE (Royal Signals and Radar Establishment) 1985 Research Review,

DTIC Science & Technology

1985-01-01

together with a 4-pulse canceller having signal processing allows adequate height time varied weighting . Temporal threshold accuracy and performance in...figure of 10 dB systems and is included within the Contraves achieved. Signal processing and target Seaguard defence system. It is a declaration are...6). This array is Taylor weighted by the t strip-line feed network to produce -29 dB Naval/Marine Radar first azimuthal sidelobe. The cosec2 low

Adaptive filtering in biological signal processing.

PubMed

Iyer, V K; Ploysongsang, Y; Ramamoorthy, P A

1990-01-01

The high dependence of conventional optimal filtering methods on the a priori knowledge of the signal and noise statistics render them ineffective in dealing with signals whose statistics cannot be predetermined accurately. Adaptive filtering methods offer a better alternative, since the a priori knowledge of statistics is less critical, real time processing is possible, and the computations are less expensive for this approach. Adaptive filtering methods compute the filter coefficients "on-line", converging to the optimal values in the least-mean square (LMS) error sense. Adaptive filtering is therefore apt for dealing with the "unknown" statistics situation and has been applied extensively in areas like communication, speech, radar, sonar, seismology, and biological signal processing and analysis for channel equalization, interference and echo canceling, line enhancement, signal detection, system identification, spectral analysis, beamforming, modeling, control, etc. In this review article adaptive filtering in the context of biological signals is reviewed. An intuitive approach to the underlying theory of adaptive filters and its applicability are presented. Applications of the principles in biological signal processing are discussed in a manner that brings out the key ideas involved. Current and potential future directions in adaptive biological signal processing are also discussed.

: Signal Decomposition of High Resolution Time Series River data to Separate Local and Regional Components of Conductivity

EPA Science Inventory

Signal processing techniques were applied to high-resolution time series data obtained from conductivity loggers placed upstream and downstream of a wastewater treatment facility along a river. Data was collected over 14-60 days, and several seasons. The power spectral densit...

Analysis of the times involved in processing and communication in a lower limb simulation system controlled by SEMG

NASA Astrophysics Data System (ADS)

Profumieri, A.; Bonell, C.; Catalfamo, P.; Cherniz, A.

2016-04-01

Virtual reality has been proposed for different applications, including the evaluation of new control strategies and training protocols for upper limb prostheses and for the study of new rehabilitation programs. In this study, a lower limb simulation environment commanded by surface electromyography signals is evaluated. The time delays generated by the acquisition and processing stages for the signals that would command the knee joint, were measured and different acquisition windows were analysed. The subjective perception of the quality of simulation was also evaluated when extra delays were added to the process. The results showed that the acquisition window is responsible for the longest delay. Also, the basic implemented processes allowed for the acquisition of three signal channels for commanding the simulation. Finally, the communication between different applications is arguably efficient, although it depends on the amount of data to be sent.

A digital signal processing system for coherent laser radar

NASA Technical Reports Server (NTRS)

Hampton, Diana M.; Jones, William D.; Rothermel, Jeffry

1991-01-01

A data processing system for use with continuous-wave lidar is described in terms of its configuration and performance during the second survey mission of NASA'a Global Backscatter Experiment. The system is designed to estimate a complete lidar spectrum in real time, record the data from two lidars, and monitor variables related to the lidar operating environment. The PC-based system includes a transient capture board, a digital-signal processing (DSP) board, and a low-speed data-acquisition board. Both unprocessed and processed lidar spectrum data are monitored in real time, and the results are compared to those of a previous non-DSP-based system. Because the DSP-based system is digital it is slower than the surface-acoustic-wave signal processor and collects 2500 spectra/s. However, the DSP-based system provides complete data sets at two wavelengths from the continuous-wave lidars.

Eliminating Bias In Acousto-Optical Spectrum Analysis

NASA Technical Reports Server (NTRS)

Ansari, Homayoon; Lesh, James R.

1992-01-01

Scheme for digital processing of video signals in acousto-optical spectrum analyzer provides real-time correction for signal-dependent spectral bias. Spectrum analyzer described in "Two-Dimensional Acousto-Optical Spectrum Analyzer" (NPO-18092), related apparatus described in "Three-Dimensional Acousto-Optical Spectrum Analyzer" (NPO-18122). Essence of correction is to average over digitized outputs of pixels in each CCD row and to subtract this from the digitized output of each pixel in row. Signal processed electro-optically with reference-function signals to form two-dimensional spectral image in CCD camera.

Analysis of Seasonal Signal in GPS Short-Baseline Time Series

NASA Astrophysics Data System (ADS)

Wang, Kaihua; Jiang, Weiping; Chen, Hua; An, Xiangdong; Zhou, Xiaohui; Yuan, Peng; Chen, Qusen

2018-04-01

Proper modeling of seasonal signals and their quantitative analysis are of interest in geoscience applications, which are based on position time series of permanent GPS stations. Seasonal signals in GPS short-baseline (< 2 km) time series, if they exist, are mainly related to site-specific effects, such as thermal expansion of the monument (TEM). However, only part of the seasonal signal can be explained by known factors due to the limited data span, the GPS processing strategy and/or the adoption of an imperfect TEM model. In this paper, to better understand the seasonal signal in GPS short-baseline time series, we adopted and processed six different short-baselines with data span that varies from 2 to 14 years and baseline length that varies from 6 to 1100 m. To avoid seasonal signals that are overwhelmed by noise, each of the station pairs is chosen with significant differences in their height (> 5 m) or type of the monument. For comparison, we also processed an approximately zero baseline with a distance of < 1 m and identical monuments. The daily solutions show that there are apparent annual signals with annual amplitude of 1 mm (maximum amplitude of 1.86 ± 0.17 mm) on almost all of the components, which are consistent with the results from previous studies. Semi-annual signal with a maximum amplitude of 0.97 ± 0.25 mm is also present. The analysis of time-correlated noise indicates that instead of flicker (FL) or random walk (RW) noise, band-pass-filtered (BP) noise is valid for approximately 40% of the baseline components, and another 20% of the components can be best modeled by a combination of the first-order Gauss-Markov (FOGM) process plus white noise (WN). The TEM displacements are then modeled by considering the monument height of the building structure beneath the GPS antenna. The median contributions of TEM to the annual amplitude in the vertical direction are 84% and 46% with and without additional parts of the monument, respectively. Obvious annual signals with amplitude > 0.4 mm in the horizontal direction are observed in five short-baselines, and the amplitudes exceed 1 mm in four of them. These horizontal seasonal signals are likely related to the propagation of daily/sub-daily TEM displacement or other signals related to the site environment. Mismodeling of the tropospheric delay may also introduce spurious seasonal signals with annual amplitudes of 5 and 2 mm, respectively, for two short-baselines with elevation differences greater than 100 m. The results suggest that the monument height of the additional part of a typical GPS station should be considered when estimating the TEM displacement and that the tropospheric delay should be modeled cautiously, especially with station pairs with apparent elevation differences. The scheme adopted in this paper is expected to explicate more seasonal signals in GPS coordinate time series, particularly in the vertical direction.

Multi-sensor investigation of the Sumatran Tsunami: observations and analysis of hydroacoustic, seismic, infrasonic, and tide gauge data

NASA Astrophysics Data System (ADS)

Bhattacharyya, J.; Pulli, J.; Gibson, R.; Upton, Z.

2005-05-01

We present an analysis of the acoustic signals from the December 26, 2004 Sumatra earthquakes, in conjunction with the seismic and tide gauge information from the event. The M9.0 mainshock and its aftershocks were recorded by a suite of seismic sensors around the globe, giving us information on its location and the source process. Recently installed sensor assets in the Indian Ocean have enabled us to study additional features of this significant event. Hydroacoustic signals were recorded by three hydrophone arrays, and the direction finding capability of these arrays allows us to examine the location, time and extent of the T-wave generation process. We detect a clear variation of the back-azimuth that is consistent with the spatial extent of the source rupture. Recordings from nearly co-located seismometers provide insights into the acoustic-to-seismic conversion process for T-waves at islands, along with the variation in signal characteristics with source size. Two separate infrasound arrays detect the atmospheric signals generated by the event, along with additional observations of the seismic surface wave and the T-phase. We will present a comparison of the signals from the mainshock, as a function of location and size, with those from aftershocks and similar events in the nearby region. Our acoustic observations compare favorably with model predictions of wave propagation in the region. For the hydroacoustic data, the azimuth, arrival time, and signal blockage characteristics, from three separate arrays, associate the onset of the signal with the mainshock and with a time extent consistent with the rupture propagation. Our analysis of the T-phase travel times suggests that the seismic-to-acoustic conversion occurs more than 100 km from the epicenter. The infrasound signal's arrival time and signal duration are consistent with both stratospheric and thermospheric propagation from a source region near the mainshock. We use the tide gauge data from stations around the Indian Ocean to identify the arrival time of the Tsunami. The acoustic and seismic signals associated with the earthquakes arrive at the remote stations significantly ahead of the Tsunami. We combine the information from the various sensors to investigate the ability of the acoustic stations to detect the Tsunami.

High frequency signal acquisition and control system based on DSP+FPGA

NASA Astrophysics Data System (ADS)

Liu, Xiao-qi; Zhang, Da-zhi; Yin, Ya-dong

2017-10-01

This paper introduces a design and implementation of high frequency signal acquisition and control system based on DSP + FPGA. The system supports internal/external clock and internal/external trigger sampling. It has a maximum sampling rate of 400MBPS and has a 1.4GHz input bandwidth for the ADC. Data can be collected continuously or periodically in systems and they are stored in DDR2. At the same time, the system also supports real-time acquisition, the collected data after digital frequency conversion and Cascaded Integrator-Comb (CIC) filtering, which then be sent to the CPCI bus through the high-speed DSP, can be assigned to the fiber board for subsequent processing. The system integrates signal acquisition and pre-processing functions, which uses high-speed A/D, high-speed DSP and FPGA mixed technology and has a wide range of uses in data acquisition and recording. In the signal processing, the system can be seamlessly connected to the dedicated processor board. The system has the advantages of multi-selectivity, good scalability and so on, which satisfies the different requirements of different signals in different projects.

Method and apparatus for improving resolution in spectrometers processing output steps from non-ideal signal sources

DOEpatents

Warburton, William K.; Momayezi, Michael

2006-06-20

A method and apparatus for processing step-like output signals (primary signals) generated by non-ideal, for example, nominally single-pole ("N-1P ") devices. An exemplary method includes creating a set of secondary signals by directing the primary signal along a plurality of signal paths to a signal summation point, summing the secondary signals reaching the signal summation point after propagating along the signal paths to provide a summed signal, performing a filtering or delaying operation in at least one of said signal paths so that the secondary signals reaching said summing point have a defined time correlation with respect to one another, applying a set of weighting coefficients to the secondary signals propagating along said signal paths, and performing a capturing operation after any filtering or delaying operations so as to provide a weighted signal sum value as a measure of the integrated area Q_gT of the input signal.

Towards the understanding of network information processing in biology

NASA Astrophysics Data System (ADS)

Singh, Vijay

Living organisms perform incredibly well in detecting a signal present in the environment. This information processing is achieved near optimally and quite reliably, even though the sources of signals are highly variable and complex. The work in the last few decades has given us a fair understanding of how individual signal processing units like neurons and cell receptors process signals, but the principles of collective information processing on biological networks are far from clear. Information processing in biological networks, like the brain, metabolic circuits, cellular-signaling circuits, etc., involves complex interactions among a large number of units (neurons, receptors). The combinatorially large number of states such a system can exist in makes it impossible to study these systems from the first principles, starting from the interactions between the basic units. The principles of collective information processing on such complex networks can be identified using coarse graining approaches. This could provide insights into the organization and function of complex biological networks. Here I study models of biological networks using continuum dynamics, renormalization, maximum likelihood estimation and information theory. Such coarse graining approaches identify features that are essential for certain processes performed by underlying biological networks. We find that long-range connections in the brain allow for global scale feature detection in a signal. These also suppress the noise and remove any gaps present in the signal. Hierarchical organization with long-range connections leads to large-scale connectivity at low synapse numbers. Time delays can be utilized to separate a mixture of signals with temporal scales. Our observations indicate that the rules in multivariate signal processing are quite different from traditional single unit signal processing.

Comparison of multichannel wide dynamic range compression and ChannelFree processing in open canal hearing instruments.

PubMed

Plyler, Patrick N; Reber, Monika Bertges; Kovach, Amanda; Galloway, Elisabeth; Humphrey, Elizabeth

2013-02-01

Multichannel wide dynamic range compression (WDRC) and ChannelFree processing have similar goals yet differ significantly in terms of signal processing. Multichannel WDRC devices divide the input signal into separate frequency bands; a separate level is determined within each frequency band; and compression in each band is based on the level within each band. ChannelFree processing detects the wideband level, and gain adjustments are based on the wideband signal level and adjusted up to 20,000 times per second. Although both signal processing strategies are currently available in hearing aids, it is unclear if differences in these signal processing strategies affect the performance and/or preference of the end user. The purpose of the research was to determine the effects of multichannel wide dynamic range compression and ChannelFree processing on performance and/or preference of listeners using open-canal hearing instruments. An experimental study in which subjects were exposed to a repeated measures design was utilized. Fourteen adult listeners with mild sloping to moderately severe sensorineural hearing loss participated (mean age 67 yr). Participants completed two 5 wk trial periods for each signal processing strategy. Probe microphone, behavioral and subjective measures were conducted unaided and aided at the end of each trial period. Behavioral and subjective results for both signal processing strategies were significantly better than unaided results; however, behavioral and subjective results were not significantly different between the signal processing strategies. Multichannel WDRC and ChannelFree processing are both effective signal processing strategies that provide significant benefit for hearing instrument users. Overall preference between the strategies may be related to the degree of hearing loss of the user, high-frequency in-situ levels, and/or acceptance of background noise. American Academy of Audiology.

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

Lovell, Jack, E-mail: jack.lovell@durham.ac.uk; Culham Centre for Fusion Energy, Culham Science Centre, Abingdon, Oxon OX14 3DB; Naylor, Graham

A new resistive bolometer system has been developed for MAST-Upgrade. It will measure radiated power in the new Super-X divertor, with millisecond time resolution, along 16 vertical and 16 horizontal lines of sight. The system uses a Xilinx Zynq-7000 series Field-Programmable Gate Array (FPGA) in the D-TACQ ACQ2106 carrier to perform real time data acquisition and signal processing. The FPGA enables AC-synchronous detection using high performance digital filtering to achieve a high signal-to-noise ratio and will be able to output processed data in real time with millisecond latency. The system has been installed on 8 previously unused channels of themore » JET vertical bolometer system. Initial results suggest good agreement with data from existing vertical channels but with higher bandwidth and signal-to-noise ratio.« less

Long-range wind monitoring in real time with optimized coherent lidar

NASA Astrophysics Data System (ADS)

Dolfi-Bouteyre, Agnes; Canat, Guillaume; Lombard, Laurent; Valla, Matthieu; Durécu, Anne; Besson, Claudine

2017-03-01

Two important enabling technologies for pulsed coherent detection wind lidar are the laser and real-time signal processing. In particular, fiber laser is limited in peak power by nonlinear effects, such as stimulated Brillouin scattering (SBS). We report on various technologies that have been developed to mitigate SBS and increase peak power in 1.5-μm fiber lasers, such as special large mode area fiber designs or strain management. Range-resolved wind profiles up to a record range of 16 km within 0.1-s averaging time have been obtained thanks to those high-peak power fiber lasers. At long range, the lidar signal gets much weaker than the noise and special care is required to extract the Doppler peak from the spectral noise. To optimize real-time processing for weak carrier-to-noise ratio signal, we have studied various Doppler mean frequency estimators (MFE) and the influence of data accumulation on outliers occurrence. Five real-time MFEs (maximum, centroid, matched filter, maximum likelihood, and polynomial fit) have been compared in terms of error and processing time using lidar experimental data. MFE errors and data accumulation limits are established using a spectral method.

Digital CODEC for real-time processing of broadcast quality video signals at 1.8 bits/pixel

NASA Technical Reports Server (NTRS)

Shalkhauser, Mary JO; Whyte, Wayne A., Jr.

1989-01-01

Advances in very large-scale integration and recent work in the field of bandwidth efficient digital modulation techniques have combined to make digital video processing technically feasible and potentially cost competitive for broadcast quality television transmission. A hardware implementation was developed for a DPCM-based digital television bandwidth compression algorithm which processes standard NTSC composite color television signals and produces broadcast quality video in real time at an average of 1.8 bits/pixel. The data compression algorithm and the hardware implementation of the CODEC are described, and performance results are provided.

Digital CODEC for real-time processing of broadcast quality video signals at 1.8 bits/pixel

NASA Technical Reports Server (NTRS)

Shalkhauser, Mary JO; Whyte, Wayne A.

1991-01-01

Advances in very large scale integration and recent work in the field of bandwidth efficient digital modulation techniques have combined to make digital video processing technically feasible an potentially cost competitive for broadcast quality television transmission. A hardware implementation was developed for DPCM (differential pulse code midulation)-based digital television bandwidth compression algorithm which processes standard NTSC composite color television signals and produces broadcast quality video in real time at an average of 1.8 bits/pixel. The data compression algorithm and the hardware implementation of the codec are described, and performance results are provided.

Robust Nonlinear Causality Analysis of Nonstationary Multivariate Physiological Time Series.

PubMed

Schack, Tim; Muma, Michael; Feng, Mengling; Guan, Cuntai; Zoubir, Abdelhak M

2018-06-01

An important research area in biomedical signal processing is that of quantifying the relationship between simultaneously observed time series and to reveal interactions between the signals. Since biomedical signals are potentially nonstationary and the measurements may contain outliers and artifacts, we introduce a robust time-varying generalized partial directed coherence (rTV-gPDC) function. The proposed method, which is based on a robust estimator of the time-varying autoregressive (TVAR) parameters, is capable of revealing directed interactions between signals. By definition, the rTV-gPDC only displays the linear relationships between the signals. We therefore suggest to approximate the residuals of the TVAR process, which potentially carry information about the nonlinear causality by a piece-wise linear time-varying moving-average model. The performance of the proposed method is assessed via extensive simulations. To illustrate the method's applicability to real-world problems, it is applied to a neurophysiological study that involves intracranial pressure, arterial blood pressure, and brain tissue oxygenation level (PtiO2) measurements. The rTV-gPDC reveals causal patterns that are in accordance with expected cardiosudoral meachanisms and potentially provides new insights regarding traumatic brain injuries. The rTV-gPDC is not restricted to the above problem but can be useful in revealing interactions in a broad range of applications.

Investigation of Cepstrum Analysis for Seismic/Acoustic Signal Sensor Range Determination.

DTIC Science & Technology

1981-01-01

distorted by transmission through a linear system . For example, the effect of multipath and reverberation may be modeled in terms of a signal that is...called the short time averaged cepstrum. To derive some analytical expressions for short time average cepstrums we choose some functions of interest...linear process applied to the time series or any equivalent time function Repiod Period The amount of time required for one cycle of a time series Saphe

The design of photoelectric signal processing system for a nuclear magnetic resonance gyroscope based on FPGA

NASA Astrophysics Data System (ADS)

Zhang, Xian; Zhou, Binquan; Li, Hong; Zhao, Xinghua; Mu, Weiwei; Wu, Wenfeng

2017-10-01

Navigation technology is crucial to the national defense and military, which can realize the measurement of orientation, positioning, attitude and speed for moving object. Inertial navigation is not only autonomous, real-time, continuous, hidden, undisturbed but also no time-limited and environment-limited. The gyroscope is the core component of the inertial navigation system, whose precision and size are the bottleneck of the performance. However, nuclear magnetic resonance gyroscope is characteristic of the advantage of high precision and small size. Nuclear magnetic resonance gyroscope can meet the urgent needs of high-tech weapons and equipment development of new generation. This paper mainly designs a set of photoelectric signal processing system for nuclear magnetic resonance gyroscope based on FPGA, which process and control the information of detecting laser .The photoelectric signal with high frequency carrier is demodulated by in-phase and quadrature demodulation method. Finally, the processing system of photoelectric signal can compensate the residual magnetism of the shielding barrel and provide the information of nuclear magnetic resonance gyroscope angular velocity.

A real-time GNSS-R system based on software-defined radio and graphics processing units

NASA Astrophysics Data System (ADS)

Hobiger, Thomas; Amagai, Jun; Aida, Masanori; Narita, Hideki

2012-04-01

Reflected signals of the Global Navigation Satellite System (GNSS) from the sea or land surface can be utilized to deduce and monitor physical and geophysical parameters of the reflecting area. Unlike most other remote sensing techniques, GNSS-Reflectometry (GNSS-R) operates as a passive radar that takes advantage from the increasing number of navigation satellites that broadcast their L-band signals. Thereby, most of the GNSS-R receiver architectures are based on dedicated hardware solutions. Software-defined radio (SDR) technology has advanced in the recent years and enabled signal processing in real-time, which makes it an ideal candidate for the realization of a flexible GNSS-R system. Additionally, modern commodity graphic cards, which offer massive parallel computing performances, allow to handle the whole signal processing chain without interfering with the PC's CPU. Thus, this paper describes a GNSS-R system which has been developed on the principles of software-defined radio supported by General Purpose Graphics Processing Units (GPGPUs), and presents results from initial field tests which confirm the anticipated capability of the system.

Time-frequency analysis of time-varying modulated signals based on improved energy separation by iterative generalized demodulation

NASA Astrophysics Data System (ADS)

Feng, Zhipeng; Chu, Fulei; Zuo, Ming J.

2011-03-01

Energy separation algorithm is good at tracking instantaneous changes in frequency and amplitude of modulated signals, but it is subject to the constraints of mono-component and narrow band. In most cases, time-varying modulated vibration signals of machinery consist of multiple components, and have so complicated instantaneous frequency trajectories on time-frequency plane that they overlap in frequency domain. For such signals, conventional filters fail to obtain mono-components of narrow band, and their rectangular decomposition of time-frequency plane may split instantaneous frequency trajectories thus resulting in information loss. Regarding the advantage of generalized demodulation method in decomposing multi-component signals into mono-components, an iterative generalized demodulation method is used as a preprocessing tool to separate signals into mono-components, so as to satisfy the requirements by energy separation algorithm. By this improvement, energy separation algorithm can be generalized to a broad range of signals, as long as the instantaneous frequency trajectories of signal components do not intersect on time-frequency plane. Due to the good adaptability of energy separation algorithm to instantaneous changes in signals and the mono-component decomposition nature of generalized demodulation, the derived time-frequency energy distribution has fine resolution and is free from cross term interferences. The good performance of the proposed time-frequency analysis is illustrated by analyses of a simulated signal and the on-site recorded nonstationary vibration signal of a hydroturbine rotor during a shut-down transient process, showing that it has potential to analyze time-varying modulated signals of multi-components.

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

Choong, W. -S.; Abu-Nimeh, F.; Moses, W. W.

Here, we present a 16-channel front-end readout board for the OpenPET electronics system. A major task in developing a nuclear medical imaging system, such as a positron emission computed tomograph (PET) or a single-photon emission computed tomograph (SPECT), is the electronics system. While there are a wide variety of detector and camera design concepts, the relatively simple nature of the acquired data allows for a common set of electronics requirements that can be met by a flexible, scalable, and high-performance OpenPET electronics system. The analog signals from the different types of detectors used in medical imaging share similar characteristics, whichmore » allows for a common analog signal processing. The OpenPET electronics processes the analog signals with Detector Boards. Here we report on the development of a 16-channel Detector Board. Each signal is digitized by a continuously sampled analog-to-digital converter (ADC), which is processed by a field programmable gate array (FPGA) to extract pulse height information. A leading edge discriminator creates a timing edge that is "time stamped" by a time-to-digital converter (TDC) implemented inside the FPGA. In conclusion, this digital information from each channel is sent to an FPGA that services 16 analog channels, and then information from multiple channels is processed by this FPGA to perform logic for crystal lookup, DOI calculation, calibration, etc.« less

Coherent-subspace array processing based on wavelet covariance: an application to broad-band, seismo-volcanic signals

NASA Astrophysics Data System (ADS)

Saccorotti, G.; Nisii, V.; Del Pezzo, E.

2008-07-01

Long-Period (LP) and Very-Long-Period (VLP) signals are the most characteristic seismic signature of volcano dynamics, and provide important information about the physical processes occurring in magmatic and hydrothermal systems. These events are usually characterized by sharp spectral peaks, which may span several frequency decades, by emergent onsets, and by a lack of clear S-wave arrivals. These two latter features make both signal detection and location a challenging task. In this paper, we propose a processing procedure based on Continuous Wavelet Transform of multichannel, broad-band data to simultaneously solve the signal detection and location problems. Our method consists of two steps. First, we apply a frequency-dependent threshold to the estimates of the array-averaged WCO in order to locate the time-frequency regions spanned by coherent arrivals. For these data, we then use the time-series of the complex wavelet coefficients for deriving the elements of the spatial Cross-Spectral Matrix. From the eigenstructure of this matrix, we eventually estimate the kinematic signals' parameters using the MUltiple SIgnal Characterization (MUSIC) algorithm. The whole procedure greatly facilitates the detection and location of weak, broad-band signals, in turn avoiding the time-frequency resolution trade-off and frequency leakage effects which affect conventional covariance estimates based upon Windowed Fourier Transform. The method is applied to explosion signals recorded at Stromboli volcano by either a short-period, small aperture antenna, or a large-aperture, broad-band network. The LP (0.2 < T < 2s) components of the explosive signals are analysed using data from the small-aperture array and under the plane-wave assumption. In this manner, we obtain a precise time- and frequency-localization of the directional properties for waves impinging at the array. We then extend the wavefield decomposition method using a spherical wave front model, and analyse the VLP components (T > 2s) of the explosion recordings from the broad-band network. Source locations obtained this way are fully compatible with those retrieved from application of more traditional (and computationally expensive) time-domain techniques, such as the Radial Semblance method.

Playback system designed for X-Band SAR

NASA Astrophysics Data System (ADS)

Yuquan, Liu; Changyong, Dou

2014-03-01

SAR(Synthetic Aperture Radar) has extensive application because it is daylight and weather independent. In particular, X-Band SAR strip map, designed by Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, provides high ground resolution images, at the same time it has a large spatial coverage and a short acquisition time, so it is promising in multi-applications. When sudden disaster comes, the emergency situation acquires radar signal data and image as soon as possible, in order to take action to reduce loss and save lives in the first time. This paper summarizes a type of X-Band SAR playback processing system designed for disaster response and scientific needs. It describes SAR data workflow includes the payload data transmission and reception process. Playback processing system completes signal analysis on the original data, providing SAR level 0 products and quick image. Gigabit network promises radar signal transmission efficiency from recorder to calculation unit. Multi-thread parallel computing and ping pong operation can ensure computation speed. Through gigabit network, multi-thread parallel computing and ping pong operation, high speed data transmission and processing meet the SAR radar data playback real time requirement.

Applications of Hilbert Spectral Analysis for Speech and Sound Signals

NASA Technical Reports Server (NTRS)

Huang, Norden E.

2003-01-01

A new method for analyzing nonlinear and nonstationary data has been developed, and the natural applications are to speech and sound signals. The key part of the method is the Empirical Mode Decomposition method with which any complicated data set can be decomposed into a finite and often small number of Intrinsic Mode Functions (IMF). An IMF is defined as any function having the same numbers of zero-crossing and extrema, and also having symmetric envelopes defined by the local maxima and minima respectively. The IMF also admits well-behaved Hilbert transform. This decomposition method is adaptive, and, therefore, highly efficient. Since the decomposition is based on the local characteristic time scale of the data, it is applicable to nonlinear and nonstationary processes. With the Hilbert transform, the Intrinsic Mode Functions yield instantaneous frequencies as functions of time, which give sharp identifications of imbedded structures. This method invention can be used to process all acoustic signals. Specifically, it can process the speech signals for Speech synthesis, Speaker identification and verification, Speech recognition, and Sound signal enhancement and filtering. Additionally, as the acoustical signals from machinery are essentially the way the machines are talking to us. Therefore, the acoustical signals, from the machines, either from sound through air or vibration on the machines, can tell us the operating conditions of the machines. Thus, we can use the acoustic signal to diagnosis the problems of machines.

PPM Receiver Implemented in Software

NASA Technical Reports Server (NTRS)

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

2010-01-01

A computer program has been written as a tool for developing optical pulse-position- modulation (PPM) receivers in which photodetector outputs are fed to analog-to-digital converters (ADCs) and all subsequent signal processing is performed digitally. The program can be used, for example, to simulate an all-digital version of the PPM receiver described in Parallel Processing of Broad-Band PPM Signals (NPO-40711), which appears elsewhere in this issue of NASA Tech Briefs. The program can also be translated into a design for digital PPM receiver hardware. The most notable innovation embodied in the software and the underlying PPM-reception concept is a digital processing subsystem that performs synchronization of PPM time slots, even though the digital processing is, itself, asynchronous in the sense that no attempt is made to synchronize it with the incoming optical signal a priori and there is no feedback to analog signal processing subsystems or ADCs. Functions performed by the software receiver include time-slot synchronization, symbol synchronization, coding preprocessing, and diagnostic functions. The program is written in the MATLAB and Simulink software system. The software receiver is highly parameterized and, hence, programmable: for example, slot- and symbol-synchronization filters have programmable bandwidths.

Measurement fidelity of heart rate variability signal processing: The devil is in the details

PubMed Central

Jarrin, Denise C.; McGrath, Jennifer J.; Giovanniello, Sabrina; Poirier, Paul; Lambert, Marie

2017-01-01

Heart rate variability (HRV) is a particularly valuable quantitative marker of the flexibility and balance of the autonomic nervous system. Significant advances in software programs to automatically derive HRV have led to its extensive use in psychophysiological research. However, there is a lack of systematic comparisons across software programs used to derive HRV indices. Further, researchers report meager details on important signal processing decisions making synthesis across studies challenging. The aim of the present study was to evaluate the measurement fidelity of time- and frequency-domain HRV indices derived from three predominant signal processing software programs commonly used in clinical and research settings. Triplicate ECG recordings were derived from 20 participants using identical data acquisition hardware. Among the time-domain indices, there was strong to excellent correspondence (ICCavg =0.93) for SDNN, SDANN, SDNNi, rMSSD, and pNN50. The frequency-domain indices yielded excellent correspondence (ICCavg =0.91) for LF, HF, and LF/HF ratio, except for VLF which exhibited poor correspondence (ICCavg =0.19). Stringent user-decisions and technical specifications for nuanced HRV processing details are essential to ensure measurement fidelity across signal processing software programs. PMID:22820268

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.

The feasibility of the auto tuning respiratory compensation system with ultrasonic image tracking technique.

PubMed

Chuang, Ho-Chiao; Hsu, Hsiao-Yu; Nieh, Shu-Kan; Tien, Der-Chi

2015-01-01

The purpose of this study is to assess the feasibility of using the analytical technique of ultrasound images in combination with an auto tumor localization system. During respiration, the activity of breathing in and out causes organs displacement at the lower lobe of the lung, and the maximum displacement range happens in the Superior-Inferior (SI) direction. Therefore, in this study all the tumor positioning is in SI direction under respiratory compensation, in which the compensations are carried out to the organs at the lower lobe and adjacent to the lower lobe of lung.In this research, due to the processes of ultrasound imaging generation, image analysis and signal transmission, when the captured respiratory signals are sent to auto tumor localization system, there was a signal time delay. The total delay time of the entire signal transmission process was 0.254 ± 0.023 seconds (with the lowest standard deviation) after implementing a series of analyses. To compensate for this signal delay time (0.254 ± 0.023 sec), a phase lead compensator (PLC) was designed and built into the auto tumor localization system. By analyzing the impact of the delay time and the respiratory waveforms under different frequencies on the phase lead compensator, an overall system delay time can be configured. Results showed as the respiratory frequency increased, variable value ``a'' and the subsequent gain ``k'' in the controller becomes larger. Moreover, value ``a'' and ``k'' increased as the system delay time increased when the respiratory frequency was fixed. The relationship of value ``a'' and ``k'' to the respiratory frequency can be obtained by using the curve fitting method to compensate for the respiratory motion for tumor localization. Through the comparison of the uncompensated signal and the compensated signal performed by the auto tumor localization system on the simulated respiratory signal, the feasibility of using ultrasound image analysis technology combined with the developed auto tumor localization system can be evaluated. The results show that the simulated respiratory signals under different frequencies of 0.5, 0.333, 0.25, 0.2 and 0.167 Hz with phase lead compensators were improved and stabilized. The compensation rate increased to the range of 7.04$∼ $18.82%, and the final compensation rate is about 97%. Therefore the auto tumor localization system combined with the ultrasound image analysis techniques is feasible.In this study, the developed ultrasound image analysis techniques combined into the auto tumor localization system has the following four advantages: (1) It is a non-invasive way (ultrasonic images) to monitor the entire compensating process of the active respiration instead of using a C-arm (invasive) to observe the organs motion. (2) During radiation therapy, the whole treatment process can be continuous, which can save the overall treatment time. (3) It is an independent system, which can be mounted onto any treatment couch. (4) Users can operate this system easily without the need of prior complicated training process.

An open-loop system design for deep space signal processing applications

NASA Astrophysics Data System (ADS)

Tang, Jifei; Xia, Lanhua; Mahapatra, Rabi

2018-06-01

A novel open-loop system design with high performance is proposed for space positioning and navigation signal processing. Divided by functions, the system has four modules, bandwidth selectable data recorder, narrowband signal analyzer, time-delay difference of arrival estimator and ANFIS supplement processor. A hardware-software co-design approach is made to accelerate computing capability and improve system efficiency. Embedded with the proposed signal processing algorithms, the designed system is capable of handling tasks with high accuracy over long period of continuous measurements. The experiment results show the Doppler frequency tracking root mean square error during 3 h observation is 0.0128 Hz, while the TDOA residue analysis in correlation power spectrum is 0.1166 rad.

The detection and analysis of point processes in biological signals

NASA Technical Reports Server (NTRS)

Anderson, D. J.; Correia, M. J.

1977-01-01

A pragmatic approach to the detection and analysis of discrete events in biomedical signals is taken. Examples from both clinical and basic research are provided. Introductory sections discuss not only discrete events which are easily extracted from recordings by conventional threshold detectors but also events embedded in other information carrying signals. The primary considerations are factors governing event-time resolution and the effects limits to this resolution have on the subsequent analysis of the underlying process. The analysis portion describes tests for qualifying the records as stationary point processes and procedures for providing meaningful information about the biological signals under investigation. All of these procedures are designed to be implemented on laboratory computers of modest computational capacity.

Nonlinear Real-Time Optical Signal Processing.

DTIC Science & Technology

1981-06-30

bandwidth and space-bandwidth products. Real-time homonorphic and loga- rithmic filtering by halftone nonlinear processing has been achieved. A...Page ABSTRACT 1 1. RESEARCH OBJECTIVES AND PROGRESS 3 I-- 1.1 Introduction and Project overview 3 1.2 Halftone Processing 9 1.3 Direct Nonlinear...time homomorphic and logarithmic filtering by halftone nonlinear processing has been achieved. A detailed analysis of degradation due to the finite gamma

Time-frequency domain SNR estimation and its application in seismic data processing

NASA Astrophysics Data System (ADS)

Zhao, Yan; Liu, Yang; Li, Xuxuan; Jiang, Nansen

2014-08-01

Based on an approach estimating frequency domain signal-to-noise ratio (FSNR), we propose a method to evaluate time-frequency domain signal-to-noise ratio (TFSNR). This method adopts short-time Fourier transform (STFT) to estimate instantaneous power spectrum of signal and noise, and thus uses their ratio to compute TFSNR. Unlike FSNR describing the variation of SNR with frequency only, TFSNR depicts the variation of SNR with time and frequency, and thus better handles non-stationary seismic data. By considering TFSNR, we develop methods to improve the effects of inverse Q filtering and high frequency noise attenuation in seismic data processing. Inverse Q filtering considering TFSNR can better solve the problem of amplitude amplification of noise. The high frequency noise attenuation method considering TFSNR, different from other de-noising methods, distinguishes and suppresses noise using an explicit criterion. Examples of synthetic and real seismic data illustrate the correctness and effectiveness of the proposed methods.

Demonstration of optical computing logics based on binary decision diagram.

PubMed

Lin, Shiyun; Ishikawa, Yasuhiko; Wada, Kazumi

2012-01-16

Optical circuits are low power consumption and fast speed alternatives for the current information processing based on transistor circuits. However, because of no transistor function available in optics, the architecture for optical computing should be chosen that optics prefers. One of which is Binary Decision Diagram (BDD), where signal is processed by sending an optical signal from the root through a serial of switching nodes to the leaf (terminal). Speed of optical computing is limited by either transmission time of optical signals from the root to the leaf or switching time of a node. We have designed and experimentally demonstrated 1-bit and 2-bit adders based on the BDD architecture. The switching nodes are silicon ring resonators with a modulation depth of 10 dB and the states are changed by the plasma dispersion effect. The quality, Q of the rings designed is 1500, which allows fast transmission of signal, e.g., 1.3 ps calculated by a photon escaping time. A total processing time is thus analyzed to be ~9 ps for a 2-bit adder and would scales linearly with the number of bit. It is two orders of magnitude faster than the conventional CMOS circuitry, ~ns scale of delay. The presented results show the potential of fast speed optical computing circuits.

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

Electronic circuit detects left ventricular ejection events in cardiovascular system

NASA Technical Reports Server (NTRS)

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

1972-01-01

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

Parallel implementation of all-digital timing recovery for high-speed and real-time optical coherent receivers.

PubMed

Zhou, Xian; Chen, Xue

2011-05-09

The digital coherent receivers combine coherent detection with digital signal processing (DSP) to compensate for transmission impairments, and therefore are a promising candidate for future high-speed optical transmission system. However, the maximum symbol rate supported by such real-time receivers is limited by the processing rate of hardware. In order to cope with this difficulty, the parallel processing algorithms is imperative. In this paper, we propose a novel parallel digital timing recovery loop (PDTRL) based on our previous work. Furthermore, for increasing the dynamic dispersion tolerance range of receivers, we embed a parallel adaptive equalizer in the PDTRL. This parallel joint scheme (PJS) can be used to complete synchronization, equalization and polarization de-multiplexing simultaneously. Finally, we demonstrate that PDTRL and PJS allow the hardware to process 112 Gbit/s POLMUX-DQPSK signal at the hundreds MHz range. © 2011 Optical Society of America

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.

Independent component analysis algorithm FPGA design to perform real-time blind source separation

NASA Astrophysics Data System (ADS)

Meyer-Baese, Uwe; Odom, Crispin; Botella, Guillermo; Meyer-Baese, Anke

2015-05-01

The conditions that arise in the Cocktail Party Problem prevail across many fields creating a need for of Blind Source Separation. The need for BSS has become prevalent in several fields of work. These fields include array processing, communications, medical signal processing, and speech processing, wireless communication, audio, acoustics and biomedical engineering. The concept of the cocktail party problem and BSS led to the development of Independent Component Analysis (ICA) algorithms. ICA proves useful for applications needing real time signal processing. The goal of this research was to perform an extensive study on ability and efficiency of Independent Component Analysis algorithms to perform blind source separation on mixed signals in software and implementation in hardware with a Field Programmable Gate Array (FPGA). The Algebraic ICA (A-ICA), Fast ICA, and Equivariant Adaptive Separation via Independence (EASI) ICA were examined and compared. The best algorithm required the least complexity and fewest resources while effectively separating mixed sources. The best algorithm was the EASI algorithm. The EASI ICA was implemented on hardware with Field Programmable Gate Arrays (FPGA) to perform and analyze its performance in real time.

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.

Research on the frequency hopping bistatic sonar system

NASA Astrophysics Data System (ADS)

Liang, Guo-long; Zhang, Yao; Zhang, Guang-pu; Liu, Kai

2011-10-01

A new model for bistatic sonar system is established, in which frequency hopping (FH) signals are used for targets detection according to some rules. This model can decrease the time between adjacent signals and obtain more information in a unit time. The receiving system will receive and process the signals of different frequency respectively, according the FH pattern, for detecting and locating targets. This method can helps yield more stable and accurate outputs, using the characteristic of the FH signals, increase the ability of anti-detection and anti partial-band jamming.

Digital signal processing the Tevatron BPM signals

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

Cancelo, G.; James, E.; Wolbers, S.

2005-05-01

The Beam Position Monitor (TeV BPM) readout system at Fermilab's Tevatron has been updated and is currently being commissioned. The new BPMs use new analog and digital hardware to achieve better beam position measurement resolution. The new system reads signals from both ends of the existing directional stripline pickups to provide simultaneous proton and antiproton measurements. The signals provided by the two ends of the BPM pickups are processed by analog band-pass filters and sampled by 14-bit ADCs at 74.3MHz. A crucial part of this work has been the design of digital filters that process the signal. This paper describesmore » the digital processing and estimation techniques used to optimize the beam position measurement. The BPM electronics must operate in narrow-band and wide-band modes to enable measurements of closed-orbit and turn-by-turn positions. The filtering and timing conditions of the signals are tuned accordingly for the operational modes. The analysis and the optimized result for each mode are presented.« less

Correlation processing for correction of phase distortions in subaperture imaging.

PubMed

Tavh, B; Karaman, M

1999-01-01

Ultrasonic subaperture imaging combines synthetic aperture and phased array approaches and permits low-cost systems with improved image quality. In subaperture processing, a large array is synthesized using echo signals collected from a number of receive subapertures by multiple firings of a phased transmit subaperture. Tissue inhomogeneities and displacements in subaperture imaging may cause significant phase distortions on received echo signals. Correlation processing on reference echo signals can be used for correction of the phase distortions, for which the accuracy and robustness are critically limited by the signal correlation. In this study, we explore correlation processing techniques for adaptive subaperture imaging with phase correction for motion and tissue inhomogeneities. The proposed techniques use new subaperture data acquisition schemes to produce reference signal sets with improved signal correlation. The experimental test results were obtained using raw radio frequency (RF) data acquired from two different phantoms with 3.5 MHz, 128-element transducer array. The results show that phase distortions can effectively be compensated by the proposed techniques in real-time adaptive subaperture imaging.

Method to improve the blade tip-timing accuracy of fiber bundle sensor under varying tip clearance

NASA Astrophysics Data System (ADS)

Duan, Fajie; Zhang, Jilong; Jiang, Jiajia; Guo, Haotian; Ye, Dechao

2016-01-01

Blade vibration measurement based on the blade tip-timing method has become an industry-standard procedure. Fiber bundle sensors are widely used for tip-timing measurement. However, the variation of clearance between the sensor and the blade will bring a tip-timing error to fiber bundle sensors due to the change in signal amplitude. This article presents methods based on software and hardware to reduce the error caused by the tip clearance change. The software method utilizes both the rising and falling edges of the tip-timing signal to determine the blade arrival time, and a calibration process suitable for asymmetric tip-timing signals is presented. The hardware method uses an automatic gain control circuit to stabilize the signal amplitude. Experiments are conducted and the results prove that both methods can effectively reduce the impact of tip clearance variation on the blade tip-timing and improve the accuracy of measurements.

A process modification for CMOS monolithic active pixel sensors for enhanced depletion, timing performance and radiation tolerance

NASA Astrophysics Data System (ADS)

Snoeys, W.; Aglieri Rinella, G.; Hillemanns, H.; Kugathasan, T.; Mager, M.; Musa, L.; Riedler, P.; Reidt, F.; Van Hoorne, J.; Fenigstein, A.; Leitner, T.

2017-11-01

For the upgrade of its Inner Tracking System, the ALICE experiment plans to install a new tracker fully constructed with monolithic active pixel sensors implemented in a standard 180 nm CMOS imaging sensor process, with a deep pwell allowing full CMOS within the pixel. Reverse substrate bias increases the tolerance to non-ionizing energy loss (NIEL) well beyond 1013 1 MeVneq /cm2, but does not allow full depletion of the sensitive layer and hence full charge collection by drift, mandatory for more extreme radiation tolerance. This paper describes a process modification to fully deplete the epitaxial layer even with a small charge collection electrode. It uses a low dose blanket deep high energy n-type implant in the pixel array and does not require significant circuit or layout changes so that the same design can be fabricated both in the standard and modified process. When exposed to a 55 Fe source at a reverse substrate bias of -6 V, pixels implemented in the standard and the modified process in a low and high dose variant for the deep n-type implant respectively yield a signal of about 115 mV, 110 mV and 90 mV at the output of a follower circuit. Signal rise times heavily affected by the speed of this circuit are 27 . 8 + / - 5 ns, 23 . 2 + / - 4 . 2 ns, and 22 . 2 + / - 3 . 7 ns rms, respectively. In a different setup, the single pixel signal from a 90 Sr source only degrades by less than 20% for the modified process after a 1015 1 MeVneq /cm2 irradiation, while the signal rise time only degrades by about 16 + / - 2 ns to 19 + / - 2 . 8 ns rms. From sensors implemented in the standard process no useful signal could be extracted after the same exposure. These first results indicate the process modification maintains low sensor capacitance, improves timing performance and increases NIEL tolerance by at least an order of magnitude.

GNSS Space-Time Interference Mitigation and Attitude Determination in the Presence of Interference Signals

PubMed Central

Daneshmand, Saeed; Jahromi, Ali Jafarnia; Broumandan, Ali; Lachapelle, Gérard

2015-01-01

The use of Space-Time Processing (STP) in Global Navigation Satellite System (GNSS) applications is gaining significant attention due to its effectiveness for both narrowband and wideband interference suppression. However, the resulting distortion and bias on the cross correlation functions due to space-time filtering is a major limitation of this technique. Employing the steering vector of the GNSS signals in the filter structure can significantly reduce the distortion on cross correlation functions and lead to more accurate pseudorange measurements. This paper proposes a two-stage interference mitigation approach in which the first stage estimates an interference-free subspace before the acquisition and tracking phases and projects all received signals into this subspace. The next stage estimates array attitude parameters based on detecting and employing GNSS signals that are less distorted due to the projection process. Attitude parameters enable the receiver to estimate the steering vector of each satellite signal and use it in the novel distortionless STP filter to significantly reduce distortion and maximize Signal-to-Noise Ratio (SNR). GPS signals were collected using a six-element antenna array under open sky conditions to first calibrate the antenna array. Simulated interfering signals were then added to the digitized samples in software to verify the applicability of the proposed receiver structure and assess its performance for several interference scenarios. PMID:26016909

GNSS space-time interference mitigation and attitude determination in the presence of interference signals.

PubMed

Daneshmand, Saeed; Jahromi, Ali Jafarnia; Broumandan, Ali; Lachapelle, Gérard

2015-05-26

The use of Space-Time Processing (STP) in Global Navigation Satellite System (GNSS) applications is gaining significant attention due to its effectiveness for both narrowband and wideband interference suppression. However, the resulting distortion and bias on the cross correlation functions due to space-time filtering is a major limitation of this technique. Employing the steering vector of the GNSS signals in the filter structure can significantly reduce the distortion on cross correlation functions and lead to more accurate pseudorange measurements. This paper proposes a two-stage interference mitigation approach in which the first stage estimates an interference-free subspace before the acquisition and tracking phases and projects all received signals into this subspace. The next stage estimates array attitude parameters based on detecting and employing GNSS signals that are less distorted due to the projection process. Attitude parameters enable the receiver to estimate the steering vector of each satellite signal and use it in the novel distortionless STP filter to significantly reduce distortion and maximize Signal-to-Noise Ratio (SNR). GPS signals were collected using a six-element antenna array under open sky conditions to first calibrate the antenna array. Simulated interfering signals were then added to the digitized samples in software to verify the applicability of the proposed receiver structure and assess its performance for several interference scenarios.

Realization of guitar audio effects using methods of digital signal processing

NASA Astrophysics Data System (ADS)

Buś, Szymon; Jedrzejewski, Konrad

2015-09-01

The paper is devoted to studies on possibilities of realization of guitar audio effects by means of methods of digital signal processing. As a result of research, some selected audio effects corresponding to the specifics of guitar sound were realized as the real-time system called Digital Guitar Multi-effect. Before implementation in the system, the selected effects were investigated using the dedicated application with a graphical user interface created in Matlab environment. In the second stage, the real-time system based on a microcontroller and an audio codec was designed and realized. The system is designed to perform audio effects on the output signal of an electric guitar.

Station to instrumented aircraft L-band telemetry system and RF signal controller for spacecraft simulations and station calibration

NASA Technical Reports Server (NTRS)

Scaffidi, C. A.; Stocklin, F. J.; Feldman, M. B.

1971-01-01

An L-band telemetry system designed to provide the capability of near-real-time processing of calibration data is described. The system also provides the capability of performing computerized spacecraft simulations, with the aircraft as a data source, and evaluating the network response. The salient characteristics of a telemetry analysis and simulation program (TASP) are discussed, together with the results of TASP testing. The results of the L-band system testing have successfully demonstrated the capability of near-real-time processing of telemetry test data, the control of the ground-received signal to within + or - 0.5 db, and the computer generation of test signals.

Signal Decomposition of High Resolution Time Series River Data to Separate Local and Regional Components of Conductivity

EPA Science Inventory

Signal processing techniques were applied to high-resolution time series data obtained from conductivity loggers placed upstream and downstream of an oil and gas wastewater treatment facility along a river. Data was collected over 14-60 days. The power spectral density was us...

Efficient Processing of Data for Locating Lightning Strikes

NASA Technical Reports Server (NTRS)

Medelius, Pedro J.; Starr, Stan

2003-01-01

Two algorithms have been devised to increase the efficiency of processing of data in lightning detection and ranging (LDAR) systems so as to enable the accurate location of lightning strikes in real time. In LDAR, the location of a lightning strike is calculated by solving equations for the differences among the times of arrival (DTOAs) of the lightning signals at multiple antennas as functions of the locations of the antennas and the speed of light. The most difficult part of the problem is computing the DTOAs from digitized versions of the signals received by the various antennas. One way (a time-domain approach) to determine the DTOAs is to compute cross-correlations among variously differentially delayed replicas of the digitized signals and to select, as the DTOAs, those differential delays that yield the maximum correlations. Another way (a frequency-domain approach) to determine the DTOAs involves the computation of cross-correlations among Fourier transforms of variously differentially phased replicas of the digitized signals, along with utilization of the relationship among phase difference, time delay, and frequency.

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.

DHS Internship Paper

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

Dreyer, J

2007-09-18

During my internship at Lawrence Livermore National Laboratory I worked with microcalorimeter gamma-ray and fast-neutron detectors based on superconducting Transition Edge Sensors (TESs). These instruments are being developed for fundamental science and nuclear non-proliferation applications because of their extremely high energy resolution; however, this comes at the expense of a small pixel size and slow decay times. The small pixel sizes are being addressed by developing detector arrays while the low count rate is being addressed by developing Digital Signal Processors (DSPs) that allow higher throughput than traditional pulse processing algorithms. Traditionally, low-temperature microcalorimeter pulses have been processed off-line withmore » optimum filtering routines based on the measured spectral characteristics of the signal and the noise. These optimum filters rely on the spectral content of the signal being identical for all events, and therefore require capturing the entire pulse signal without pile-up. In contrast, the DSP algorithm being developed is based on differences in signal levels before and after a trigger event, and therefore does not require the waveform to fully decay, or even the signal level to be close to the base line. The readout system allows for real time data acquisition and analysis at count rates exceeding 100 Hz for pulses with several {approx}ms decay times with minimal loss of energy resolution. Originally developed for gamma-ray analysis with HPGe detectors we have modified the hardware and firmware of the system to accommodate the slower TES signals and optimized the parameters of the filtering algorithm to maximize either resolution or throughput. The following presents an overview of the digital signal processing hardware and discusses the results of characterization measurements made to determine the systems performance.« less

Nonlinear Estimation of Discrete-Time Signals Under Random Observation Delay

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

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

2008-11-06

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

Biosensor method and system based on feature vector extraction

DOEpatents

Greenbaum, Elias [Knoxville, TN; Rodriguez, Jr., Miguel; Qi, Hairong [Knoxville, TN; Wang, Xiaoling [San Jose, CA

2012-04-17

A method of biosensor-based detection of toxins comprises the steps of providing at least one time-dependent control signal generated by a biosensor in a gas or liquid medium, and obtaining a time-dependent biosensor signal from the biosensor in the gas or liquid medium to be monitored or analyzed for the presence of one or more toxins selected from chemical, biological or radiological agents. The time-dependent biosensor signal is processed to obtain a plurality of feature vectors using at least one of amplitude statistics and a time-frequency analysis. At least one parameter relating to toxicity of the gas or liquid medium is then determined from the feature vectors based on reference to the control signal.

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

NASA Technical Reports Server (NTRS)

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

1984-01-01

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

Investigation of digital encoding techniques for television transmission

NASA Technical Reports Server (NTRS)

Schilling, D. L.

1983-01-01

Composite color television signals are sampled at four times the color subcarrier and transformed using intraframe two dimensional Walsh functions. It is shown that by properly sampling a composite color signal and employing a Walsh transform the YIQ time signals which sum to produce the composite color signal can be represented, in the transform domain, by three component signals in space. By suitably zonal quantizing the transform coefficients, the YIQ signals can be processed independently to achieve data compression and obtain the same results as component coding. Computer simulations of three bandwidth compressors operating at 1.09, 1.53 and 1.8 bits/ sample are presented. The above results can also be applied to the PAL color system.

Extraction and analysis of neuron firing signals from deep cortical video microscopy

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

Kerekes, Ryan A; Blundon, Jay

We introduce a method for extracting and analyzing neuronal activity time signals from video of the cortex of a live animal. The signals correspond to the firing activity of individual cortical neurons. Activity signals are based on the changing fluorescence of calcium indicators in the cells over time. We propose a cell segmentation method that relies on a user-specified center point, from which the signal extraction method proceeds. A stabilization approach is used to reduce tissue motion in the video. The extracted signal is then processed to flatten the baseline and detect action potentials. We show results from applying themore » method to a cortical video of a live mouse.« less

Evaluation of dispersive Bragg gratings (BG) structures for the processing of RF signals with large time delays and bandwidths

NASA Astrophysics Data System (ADS)

Kaba, M.; Zhou, F. C.; Lim, A.; Decoster, D.; Huignard, J.-P.; Tonda, S.; Dolfi, D.; Chazelas, J.

2007-11-01

The applications of microwave optoelectronics are extremely large since they extend from the Radio-over-Fibre to the Homeland security and defence systems. Then, the improved maturity of the optoelectronic components operating up to 40GHz permit to consider new optical processing functions (filtering, beamforming, ...) which can operate over very wideband microwave analogue signals. Specific performances are required which imply optical delay lines able to exhibit large Time-Bandwidth product values. It is proposed to evaluate slow light approach through highly dispersive structures based on either uniform or chirped Bragg Gratings. Therefore, we highlight the impact of the major parameters of such structures: index modulation depth, grating length, grating period, chirp coefficient and demonstrate the high potentiality of Bragg Grating for Large RF signals bandwidth processing under slow-light propagation.

Optical fiber sensor technique for strain measurement during materials deposition, chemical reaction, and relaxation

DOEpatents

Butler, M.A.; Ginley, D.S.

1988-01-21

Laser light from a common source is split and conveyed through two similar optical fibers and emitted at their respective ends to form an interference pattern, one of the optical fibers having a portion thereof subjected to a strain. Changes in the strain cause changes in the optical path length of the strain fiber, and generate corresponding changes in the interference pattern. The interference pattern is received and transduced into signals representative of fringe shifts corresponding to changes in the strain experienced by the strained one of the optical fibers. These signals are then processed to evaluate strain as a function of time, typical examples of the application of the apparatus including electrodeposition of a metallic film on a conductive surface provided on the outside of the optical fiber being strained, so that strains generated in the optical fiber during the course of the electrodeposition are measurable as a function of time. In one aspect of the invention, signals relating to the fringe shift are stored for subsequent processing and analysis, whereas in another aspect of the invention the signals are processed for real-time display of the strain changes under study. 9 figs.

Low Computational Signal Acquisition for GNSS Receivers Using a Resampling Strategy and Variable Circular Correlation Time

PubMed Central

Zhang, Yeqing; Wang, Meiling; Li, Yafeng

2018-01-01

For the objective of essentially decreasing computational complexity and time consumption of signal acquisition, this paper explores a resampling strategy and variable circular correlation time strategy specific to broadband multi-frequency GNSS receivers. In broadband GNSS receivers, the resampling strategy is established to work on conventional acquisition algorithms by resampling the main lobe of received broadband signals with a much lower frequency. Variable circular correlation time is designed to adapt to different signal strength conditions and thereby increase the operation flexibility of GNSS signal acquisition. The acquisition threshold is defined as the ratio of the highest and second highest correlation results in the search space of carrier frequency and code phase. Moreover, computational complexity of signal acquisition is formulated by amounts of multiplication and summation operations in the acquisition process. Comparative experiments and performance analysis are conducted on four sets of real GPS L2C signals with different sampling frequencies. The results indicate that the resampling strategy can effectively decrease computation and time cost by nearly 90–94% with just slight loss of acquisition sensitivity. With circular correlation time varying from 10 ms to 20 ms, the time cost of signal acquisition has increased by about 2.7–5.6% per millisecond, with most satellites acquired successfully. PMID:29495301

Low Computational Signal Acquisition for GNSS Receivers Using a Resampling Strategy and Variable Circular Correlation Time.

PubMed

Zhang, Yeqing; Wang, Meiling; Li, Yafeng

2018-02-24

For the objective of essentially decreasing computational complexity and time consumption of signal acquisition, this paper explores a resampling strategy and variable circular correlation time strategy specific to broadband multi-frequency GNSS receivers. In broadband GNSS receivers, the resampling strategy is established to work on conventional acquisition algorithms by resampling the main lobe of received broadband signals with a much lower frequency. Variable circular correlation time is designed to adapt to different signal strength conditions and thereby increase the operation flexibility of GNSS signal acquisition. The acquisition threshold is defined as the ratio of the highest and second highest correlation results in the search space of carrier frequency and code phase. Moreover, computational complexity of signal acquisition is formulated by amounts of multiplication and summation operations in the acquisition process. Comparative experiments and performance analysis are conducted on four sets of real GPS L2C signals with different sampling frequencies. The results indicate that the resampling strategy can effectively decrease computation and time cost by nearly 90-94% with just slight loss of acquisition sensitivity. With circular correlation time varying from 10 ms to 20 ms, the time cost of signal acquisition has increased by about 2.7-5.6% per millisecond, with most satellites acquired successfully.

A survey on signals and systems in ambulatory blood pressure monitoring using pulse transit time.

PubMed

Buxi, Dilpreet; Redouté, Jean-Michel; Yuce, Mehmet Rasit

2015-03-01

Blood pressure monitoring based on pulse transit or arrival time has been the focus of much research in order to design ambulatory blood pressure monitors. The accuracy of these monitors is limited by several challenges, such as acquisition and processing of physiological signals as well as changes in vascular tone and the pre-ejection period. In this work, a literature survey covering recent developments is presented in order to identify gaps in the literature. The findings of the literature are classified according to three aspects. These are the calibration of pulse transit/arrival times to blood pressure, acquisition and processing of physiological signals and finally, the design of fully integrated blood pressure measurement systems. Alternative technologies as well as locations for the measurement of the pulse wave signal should be investigated in order to improve the accuracy during calibration. Furthermore, the integration and validation of monitoring systems needs to be improved in current ambulatory blood pressure monitors.

Low-Latency Digital Signal Processing for Feedback and Feedforward in Quantum Computing and Communication

NASA Astrophysics Data System (ADS)

Salathé, Yves; Kurpiers, Philipp; Karg, Thomas; Lang, Christian; Andersen, Christian Kraglund; Akin, Abdulkadir; Krinner, Sebastian; Eichler, Christopher; Wallraff, Andreas

2018-03-01

Quantum computing architectures rely on classical electronics for control and readout. Employing classical electronics in a feedback loop with the quantum system allows us to stabilize states, correct errors, and realize specific feedforward-based quantum computing and communication schemes such as deterministic quantum teleportation. These feedback and feedforward operations are required to be fast compared to the coherence time of the quantum system to minimize the probability of errors. We present a field-programmable-gate-array-based digital signal processing system capable of real-time quadrature demodulation, a determination of the qubit state, and a generation of state-dependent feedback trigger signals. The feedback trigger is generated with a latency of 110 ns with respect to the timing of the analog input signal. We characterize the performance of the system for an active qubit initialization protocol based on the dispersive readout of a superconducting qubit and discuss potential applications in feedback and feedforward algorithms.

SignalPlant: an open signal processing software platform.

PubMed

Plesinger, F; Jurco, J; Halamek, J; Jurak, P

2016-07-01

The growing technical standard of acquisition systems allows the acquisition of large records, often reaching gigabytes or more in size as is the case with whole-day electroencephalograph (EEG) recordings, for example. Although current 64-bit software for signal processing is able to process (e.g. filter, analyze, etc) such data, visual inspection and labeling will probably suffer from rather long latency during the rendering of large portions of recorded signals. For this reason, we have developed SignalPlant-a stand-alone application for signal inspection, labeling and processing. The main motivation was to supply investigators with a tool allowing fast and interactive work with large multichannel records produced by EEG, electrocardiograph and similar devices. The rendering latency was compared with EEGLAB and proves significantly faster when displaying an image from a large number of samples (e.g. 163-times faster for 75  ×  10(6) samples). The presented SignalPlant software is available free and does not depend on any other computation software. Furthermore, it can be extended with plugins by third parties ensuring its adaptability to future research tasks and new data formats.

Method and system for downhole clock synchronization

DOEpatents

Hall, David R.; Bartholomew, David B.; Johnson, Monte; Moon, Justin; Koehler, Roger O.

2006-11-28

A method and system for use in synchronizing at least two clocks in a downhole network are disclosed. The method comprises determining a total signal latency between a controlling processing element and at least one downhole processing element in a downhole network and sending a synchronizing time over the downhole network to the at least one downhole processing element adjusted for the signal latency. Electronic time stamps may be used to measure latency between processing elements. A system for electrically synchronizing at least two clocks connected to a downhole network comprises a controlling processing element connected to a synchronizing clock in communication over a downhole network with at least one downhole processing element comprising at least one downhole clock. Preferably, the downhole network is integrated into a downhole tool string.

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.

A method for discrimination of noise and EMG signal regions recorded during rhythmic behaviors.

PubMed

Ying, Rex; Wall, Christine E

2016-12-08

Analyses of muscular activity during rhythmic behaviors provide critical data for biomechanical studies. Electrical potentials measured from muscles using electromyography (EMG) require discrimination of noise regions as the first step in analysis. An experienced analyst can accurately identify the onset and offset of EMG but this process takes hours to analyze a short (10-15s) record of rhythmic EMG bursts. Existing computational techniques reduce this time but have limitations. These include a universal threshold for delimiting noise regions (i.e., a single signal value for identifying the EMG signal onset and offset), pre-processing using wide time intervals that dampen sensitivity for EMG signal characteristics, poor performance when a low frequency component (e.g., DC offset) is present, and high computational complexity leading to lack of time efficiency. We present a new statistical method and MATLAB script (EMG-Extractor) that includes an adaptive algorithm to discriminate noise regions from EMG that avoids these limitations and allows for multi-channel datasets to be processed. We evaluate the EMG-Extractor with EMG data on mammalian jaw-adductor muscles during mastication, a rhythmic behavior typified by low amplitude onsets/offsets and complex signal pattern. The EMG-Extractor consistently and accurately distinguishes noise from EMG in a manner similar to that of an experienced analyst. It outputs the raw EMG signal region in a form ready for further analysis. Copyright © 2016 Elsevier Ltd. All rights reserved.

Signal restoration through deconvolution applied to deep mantle seismic probes

NASA Astrophysics Data System (ADS)

Stefan, W.; Garnero, E.; Renaut, R. A.

2006-12-01

We present a method of signal restoration to improve the signal-to-noise ratio, sharpen seismic arrival onset, and act as an empirical source deconvolution of specific seismic arrivals. Observed time-series gi are modelled as a convolution of a simpler time-series fi, and an invariant point spread function (PSF) h that attempts to account for the earthquake source process. The method is used on the shear wave time window containing SKS and S, whereby using a Gaussian PSF produces more impulsive, narrower, signals in the wave train. The resulting restored time-series facilitates more accurate and objective relative traveltime estimation of the individual seismic arrivals. We demonstrate the accuracy of the reconstruction method on synthetic seismograms generated by the reflectivity method. Clean and sharp reconstructions are obtained with real data, even for signals with relatively high noise content. Reconstructed signals are simpler, more impulsive, and narrower, which allows highlighting of some details of arrivals that are not readily apparent in raw waveforms. In particular, phases nearly coincident in time can be separately identified after processing. This is demonstrated for two seismic wave pairs used to probe deep mantle and core-mantle boundary structure: (1) the Sab and Scd arrivals, which travel above and within, respectively, a 200-300-km-thick, higher than average shear wave velocity layer at the base of the mantle, observable in the 88-92 deg epicentral distance range and (2) SKS and SPdiff KS, which are core waves with the latter having short arcs of P-wave diffraction, and are nearly identical in timing near 108-110 deg in distance. A Java/Matlab algorithm was developed for the signal restoration, which can be downloaded from the authors web page, along with example data and synthetic seismograms.

Signal Processing Methods Monitor Cranial Pressure

NASA Technical Reports Server (NTRS)

2010-01-01

Dr. Norden Huang, of Goddard Space Flight Center, invented a set of algorithms (called the Hilbert-Huang Transform, or HHT) for analyzing nonlinear and nonstationary signals that developed into a user-friendly signal processing technology for analyzing time-varying processes. At an auction managed by Ocean Tomo Federal Services LLC, licenses of 10 U.S. patents and 1 domestic patent application related to HHT were sold to DynaDx Corporation, of Mountain View, California. DynaDx is now using the licensed NASA technology for medical diagnosis and prediction of brain blood flow-related problems, such as stroke, dementia, and traumatic brain injury.

Research on control law accelerator of digital signal process chip TMS320F28035 for real-time data acquisition and processing

NASA Astrophysics Data System (ADS)

Zhao, Shuangle; Zhang, Xueyi; Sun, Shengli; Wang, Xudong

2017-08-01

TI C2000 series digital signal process (DSP) chip has been widely used in electrical engineering, measurement and control, communications and other professional fields, DSP TMS320F28035 is one of the most representative of a kind. When using the DSP program, need data acquisition and data processing, and if the use of common mode C or assembly language programming, the program sequence, analogue-to-digital (AD) converter cannot be real-time acquisition, often missing a lot of data. The control low accelerator (CLA) processor can run in parallel with the main central processing unit (CPU), and the frequency is consistent with the main CPU, and has the function of floating point operations. Therefore, the CLA coprocessor is used in the program, and the CLA kernel is responsible for data processing. The main CPU is responsible for the AD conversion. The advantage of this method is to reduce the time of data processing and realize the real-time performance of data acquisition.

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.

Welding quality evaluation of resistance spot welding using the time-varying inductive reactance signal

NASA Astrophysics Data System (ADS)

Zhang, Hongjie; Hou, Yanyan; Yang, Tao; Zhang, Qian; Zhao, Jian

2018-05-01

In the spot welding process, a high alternating current is applied, resulting in a time-varying electromagnetic field surrounding the welder. When measuring the welding voltage signal, the impedance of the measuring circuit consists of two parts: dynamic resistance relating to weld nugget nucleation event and inductive reactance caused by mutual inductance. The aim of this study is to develop a method to acquire the dynamic reactance signal and to discuss the possibility of using this signal to evaluate the weld quality. For this purpose, a series of experiments were carried out. The reactance signals under different welding conditions were compared and the results showed that the morphological feature of the reactance signal was closely related to the welding current and it was also significantly influenced by some abnormal welding conditions. Some features were extracted from the reactance signal and combined to construct weld nugget strength and diameter prediction models based on the radial basis function (RBF) neural network. In addition, several features were also used to monitor the expulsion in the welding process by using Fisher linear discriminant analysis. The results indicated that using the dynamic reactance signal to evaluate weld quality is possible and feasible.

A method for velocity signal reconstruction of AFDISAR/PDV based on crazy-climber algorithm

NASA Astrophysics Data System (ADS)

Peng, Ying-cheng; Guo, Xian; Xing, Yuan-ding; Chen, Rong; Li, Yan-jie; Bai, Ting

2017-10-01

The resolution of Continuous wavelet transformation (CWT) is different when the frequency is different. For this property, the time-frequency signal of coherent signal obtained by All Fiber Displacement Interferometer System for Any Reflector (AFDISAR) is extracted. Crazy-climber Algorithm is adopted to extract wavelet ridge while Velocity history curve of the measuring object is obtained. Numerical simulation is carried out. The reconstruction signal is completely consistent with the original signal, which verifies the accuracy of the algorithm. Vibration of loudspeaker and free end of Hopkinson incident bar under impact loading are measured by AFDISAR, and the measured coherent signals are processed. Velocity signals of loudspeaker and free end of Hopkinson incident bar are reconstructed respectively. Comparing with the theoretical calculation, the particle vibration arrival time difference error of the free end of Hopkinson incident bar is 2μs. It is indicated from the results that the algorithm is of high accuracy, and is of high adaptability to signals of different time-frequency feature. The algorithm overcomes the limitation of modulating the time window artificially according to the signal variation when adopting STFT, and is suitable for extracting signal measured by AFDISAR.

The Combined Effect of Periodic Signals and Noise on the Dilution of Precision of GNSS Station Velocity Uncertainties

NASA Astrophysics Data System (ADS)

Klos, Anna; Olivares, German; Teferle, Felix Norman; Bogusz, Janusz

2016-04-01

Station velocity uncertainties determined from a series of Global Navigation Satellite System (GNSS) position estimates depend on both the deterministic and stochastic models applied to the time series. While the deterministic model generally includes parameters for a linear and several periodic terms the stochastic model is a representation of the noise character of the time series in form of a power-law process. For both of these models the optimal model may vary from one time series to another while the models also depend, to some degree, on each other. In the past various power-law processes have been shown to fit the time series and the sources for the apparent temporally-correlated noise were attributed to, for example, mismodelling of satellites orbits, antenna phase centre variations, troposphere, Earth Orientation Parameters, mass loading effects and monument instabilities. Blewitt and Lavallée (2002) demonstrated how improperly modelled seasonal signals affected the estimates of station velocity uncertainties. However, in their study they assumed that the time series followed a white noise process with no consideration of additional temporally-correlated noise. Bos et al. (2010) empirically showed for a small number of stations that the noise character was much more important for the reliable estimation of station velocity uncertainties than the seasonal signals. In this presentation we pick up from Blewitt and Lavallée (2002) and Bos et al. (2010), and have derived formulas for the computation of the General Dilution of Precision (GDP) under presence of periodic signals and temporally-correlated noise in the time series. We show, based on simulated and real time series from globally distributed IGS (International GNSS Service) stations processed by the Jet Propulsion Laboratory (JPL), that periodic signals dominate the effect on the velocity uncertainties at short time scales while for those beyond four years, the type of noise becomes much more important. In other words, for time series long enough, the assumed periodic signals do not affect the velocity uncertainties as much as the assumed noise model. We calculated the GDP to be the ratio between two errors of velocity: without and with inclusion of seasonal terms of periods equal to one year and its overtones till 3rd. To all these cases power-law processes of white, flicker and random-walk noise were added separately. Few oscillations in GDP can be noticed for integer years, which arise from periodic terms added. Their amplitudes in GDP increase along with the increasing spectral index. Strong peaks of oscillations in GDP are indicated for short time scales, especially for random-walk processes. This means that badly monumented stations are affected the most. Local minima and maxima in GDP are also enlarged as the noise approaches random walk. We noticed that the semi-annual signal increased the local GDP minimum for white noise. This suggests that adding power-law noise to a deterministic model with annual term or adding a semi-annual term to white noise causes an increased velocity uncertainty even at the points, where determined velocity is not biased.

Characterization of a 300-GHz Transmission System for Digital Communications

NASA Astrophysics Data System (ADS)

Hudlička, Martin; Salhi, Mohammed; Kleine-Ostmann, Thomas; Schrader, Thorsten

2017-08-01

The paper presents the characterization of a 300-GHz transmission system for modern digital communications. The quality of the modulated signal at the output of the system (error vector magnitude, EVM) is measured using a vector signal analyzer. A method using a digital real-time oscilloscope and consecutive mathematical processing in a computer is shown for analysis of signals with bandwidths exceeding that of state-of-the-art vector signal analyzers. The uncertainty of EVM measured using the real-time oscilloscope is open to analysis. Behaviour of the 300-GHz transmission system is studied with respect to various modulation schemes and different signal symbol rates.

Real-Time Processing of Continuous Physiological Signals in a Neurocritical Care Unit on a Stream Data Analytics Platform.

PubMed

Bai, Yong; Sow, Daby; Vespa, Paul; Hu, Xiao

2016-01-01

Continuous high-volume and high-frequency brain signals such as intracranial pressure (ICP) and electroencephalographic (EEG) waveforms are commonly collected by bedside monitors in neurocritical care. While such signals often carry early signs of neurological deterioration, detecting these signs in real time with conventional data processing methods mainly designed for retrospective analysis has been extremely challenging. Such methods are not designed to handle the large volumes of waveform data produced by bedside monitors. In this pilot study, we address this challenge by building a prototype system using the IBM InfoSphere Streams platform, a scalable stream computing platform, to detect unstable ICP dynamics in real time. The system continuously receives electrocardiographic and ICP signals and analyzes ICP pulse morphology looking for deviations from a steady state. We also designed a Web interface to display in real time the result of this analysis in a Web browser. With this interface, physicians are able to ubiquitously check on the status of their patients and gain direct insight into and interpretation of the patient's state in real time. The prototype system has been successfully tested prospectively on live hospitalized patients.

Turbulent Statistics From Time-Resolved PIV Measurements of a Jet Using Empirical Mode Decomposition

NASA Technical Reports Server (NTRS)

Dahl, Milo D.

2013-01-01

Empirical mode decomposition is an adaptive signal processing method that when applied to a broadband signal, such as that generated by turbulence, acts as a set of band-pass filters. This process was applied to data from time-resolved, particle image velocimetry measurements of subsonic jets prior to computing the second-order, two-point, space-time correlations from which turbulent phase velocities and length and time scales could be determined. The application of this method to large sets of simultaneous time histories is new. In this initial study, the results are relevant to acoustic analogy source models for jet noise prediction. The high frequency portion of the results could provide the turbulent values for subgrid scale models for noise that is missed in large-eddy simulations. The results are also used to infer that the cross-correlations between different components of the decomposed signals at two points in space, neglected in this initial study, are important.

Turbulent Statistics from Time-Resolved PIV Measurements of a Jet Using Empirical Mode Decomposition

NASA Technical Reports Server (NTRS)

Dahl, Milo D.

2012-01-01

Empirical mode decomposition is an adaptive signal processing method that when applied to a broadband signal, such as that generated by turbulence, acts as a set of band-pass filters. This process was applied to data from time-resolved, particle image velocimetry measurements of subsonic jets prior to computing the second-order, two-point, space-time correlations from which turbulent phase velocities and length and time scales could be determined. The application of this method to large sets of simultaneous time histories is new. In this initial study, the results are relevant to acoustic analogy source models for jet noise prediction. The high frequency portion of the results could provide the turbulent values for subgrid scale models for noise that is missed in large-eddy simulations. The results are also used to infer that the cross-correlations between different components of the decomposed signals at two points in space, neglected in this initial study, are important.

Liquid Argon TPC Signal Formation, Signal Processing and Hit Reconstruction

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

Baller, Bruce

2017-03-11

This document describes the early stage of the reconstruction chain that was developed for the ArgoNeuT and MicroBooNE experiments at Fermilab. These experiments study accelerator neutrino interactions that occur in a Liquid Argon Time Projection Chamber. Reconstructing the properties of particles produced in these interactions requires knowledge of the micro-physics processes that affect the creation and transport of ionization electrons to the readout system. A wire signal deconvolution technique was developed to convert wire signals to a standard form for hit reconstruction, to remove artifacts in the electronics chain and to remove coherent noise.

EEG Recording and Online Signal Processing on Android: A Multiapp Framework for Brain-Computer Interfaces on Smartphone

PubMed Central

Debener, Stefan; Emkes, Reiner; Volkening, Nils; Fudickar, Sebastian; Bleichner, Martin G.

2017-01-01

Objective Our aim was the development and validation of a modular signal processing and classification application enabling online electroencephalography (EEG) signal processing on off-the-shelf mobile Android devices. The software application SCALA (Signal ProCessing and CLassification on Android) supports a standardized communication interface to exchange information with external software and hardware. Approach In order to implement a closed-loop brain-computer interface (BCI) on the smartphone, we used a multiapp framework, which integrates applications for stimulus presentation, data acquisition, data processing, classification, and delivery of feedback to the user. Main Results We have implemented the open source signal processing application SCALA. We present timing test results supporting sufficient temporal precision of audio events. We also validate SCALA with a well-established auditory selective attention paradigm and report above chance level classification results for all participants. Regarding the 24-channel EEG signal quality, evaluation results confirm typical sound onset auditory evoked potentials as well as cognitive event-related potentials that differentiate between correct and incorrect task performance feedback. Significance We present a fully smartphone-operated, modular closed-loop BCI system that can be combined with different EEG amplifiers and can easily implement other paradigms. PMID:29349070

EEG Recording and Online Signal Processing on Android: A Multiapp Framework for Brain-Computer Interfaces on Smartphone.

PubMed

Blum, Sarah; Debener, Stefan; Emkes, Reiner; Volkening, Nils; Fudickar, Sebastian; Bleichner, Martin G

2017-01-01

Our aim was the development and validation of a modular signal processing and classification application enabling online electroencephalography (EEG) signal processing on off-the-shelf mobile Android devices. The software application SCALA (Signal ProCessing and CLassification on Android) supports a standardized communication interface to exchange information with external software and hardware. In order to implement a closed-loop brain-computer interface (BCI) on the smartphone, we used a multiapp framework, which integrates applications for stimulus presentation, data acquisition, data processing, classification, and delivery of feedback to the user. We have implemented the open source signal processing application SCALA. We present timing test results supporting sufficient temporal precision of audio events. We also validate SCALA with a well-established auditory selective attention paradigm and report above chance level classification results for all participants. Regarding the 24-channel EEG signal quality, evaluation results confirm typical sound onset auditory evoked potentials as well as cognitive event-related potentials that differentiate between correct and incorrect task performance feedback. We present a fully smartphone-operated, modular closed-loop BCI system that can be combined with different EEG amplifiers and can easily implement other paradigms.

Hybrid photonic signal processing

NASA Astrophysics Data System (ADS)

Ghauri, Farzan Naseer

This thesis proposes research of novel hybrid photonic signal processing systems in the areas of optical communications, test and measurement, RF signal processing and extreme environment optical sensors. It will be shown that use of innovative hybrid techniques allows design of photonic signal processing systems with superior performance parameters and enhanced capabilities. These applications can be divided into domains of analog-digital hybrid signal processing applications and free-space---fiber-coupled hybrid optical sensors. The analog-digital hybrid signal processing applications include a high-performance analog-digital hybrid MEMS variable optical attenuator that can simultaneously provide high dynamic range as well as high resolution attenuation controls; an analog-digital hybrid MEMS beam profiler that allows high-power watt-level laser beam profiling and also provides both submicron-level high resolution and wide area profiling coverage; and all optical transversal RF filters that operate on the principle of broadband optical spectral control using MEMS and/or Acousto-Optic tunable Filters (AOTF) devices which can provide continuous, digital or hybrid signal time delay and weight selection. The hybrid optical sensors presented in the thesis are extreme environment pressure sensors and dual temperature-pressure sensors. The sensors employ hybrid free-space and fiber-coupled techniques for remotely monitoring a system under simultaneous extremely high temperatures and pressures.

The Time-Domain Matched Filter and the Spectral-Domain Matched Filter in 1-Dimensional NMR Spectroscopy.

PubMed

Spencer, Richard G

2010-09-01

A type of "matched filter" (MF), used extensively in the processing of one-dimensional spectra, is defined by multiplication of a free-induction decay (FID) by a decaying exponential with the same time constant as that of the FID. This maximizes, in a sense to be defined, the signal-to-noise ratio (SNR) in the spectrum obtained after Fourier transformation. However, a different entity known also as the matched filter was introduced by van Vleck in the context of pulse detection in the 1940's and has become widely integrated into signal processing practice. These two types of matched filters appear to be quite distinct. In the NMR case, the "filter", that is, the exponential multiplication, is defined by the characteristics of, and applied to, a time domain signal in order to achieve improved SNR in the spectral domain. In signal processing, the filter is defined by the characteristics of a signal in the spectral domain, and applied in order to improve the SNR in the temporal (pulse) domain. We reconcile these two distinct implementations of the matched filter, demonstrating that the NMR "matched filter" is a special case of the matched filter more rigorously defined in the signal processing literature. In addition, two limitations in the use of the MF are highlighted. First, application of the MF distorts resonance ratios as defined by amplitudes, although not as defined by areas. Second, the MF maximizes SNR with respect to resonance amplitude, while intensities are often more appropriately defined by areas. Maximizing the SNR with respect to area requires a somewhat different approach to matched filtering.

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.

Real-time processing of radar return on a parallel computer

NASA Technical Reports Server (NTRS)

Aalfs, David D.

1992-01-01

NASA is working with the FAA to demonstrate the feasibility of pulse Doppler radar as a candidate airborne sensor to detect low altitude windshears. The need to provide the pilot with timely information about possible hazards has motivated a demand for real-time processing of a radar return. Investigated here is parallel processing as a means of accommodating the high data rates required. A PC based parallel computer, called the transputer, is used to investigate issues in real time concurrent processing of radar signals. A transputer network is made up of an array of single instruction stream processors that can be networked in a variety of ways. They are easily reconfigured and software development is largely independent of the particular network topology. The performance of the transputer is evaluated in light of the computational requirements. A number of algorithms have been implemented on the transputers in OCCAM, a language specially designed for parallel processing. These include signal processing algorithms such as the Fast Fourier Transform (FFT), pulse-pair, and autoregressive modelling, as well as routing software to support concurrency. The most computationally intensive task is estimating the spectrum. Two approaches have been taken on this problem, the first and most conventional of which is to use the FFT. By using table look-ups for the basis function and other optimizing techniques, an algorithm has been developed that is sufficient for real time. The other approach is to model the signal as an autoregressive process and estimate the spectrum based on the model coefficients. This technique is attractive because it does not suffer from the spectral leakage problem inherent in the FFT. Benchmark tests indicate that autoregressive modeling is feasible in real time.

Smartphone Cortex Controlled Real-Time Image Processing and Reprocessing for Concentration Independent LED Induced Fluorescence Detection in Capillary Electrophoresis.

PubMed

Szarka, Mate; Guttman, Andras

2017-10-17

We present the application of a smartphone anatomy based technology in the field of liquid phase bioseparations, particularly in capillary electrophoresis. A simple capillary electrophoresis system was built with LED induced fluorescence detection and a credit card sized minicomputer to prove the concept of real time fluorescent imaging (zone adjustable time-lapse fluorescence image processor) and separation controller. The system was evaluated by analyzing under- and overloaded aminopyrenetrisulfonate (APTS)-labeled oligosaccharide samples. The open source software based image processing tool allowed undistorted signal modulation (reprocessing) if the signal was inappropriate for the actual detection system settings (too low or too high). The novel smart detection tool for fluorescently labeled biomolecules greatly expands dynamic range and enables retrospective correction for injections with unsuitable signal levels without the necessity to repeat the analysis.

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.

An FPGA-based bolometer for the MAST-U Super-X divertor.

PubMed

Lovell, Jack; Naylor, Graham; Field, Anthony; Drewelow, Peter; Sharples, Ray

2016-11-01

A new resistive bolometer system has been developed for MAST-Upgrade. It will measure radiated power in the new Super-X divertor, with millisecond time resolution, along 16 vertical and 16 horizontal lines of sight. The system uses a Xilinx Zynq-7000 series Field-Programmable Gate Array (FPGA) in the D-TACQ ACQ2106 carrier to perform real time data acquisition and signal processing. The FPGA enables AC-synchronous detection using high performance digital filtering to achieve a high signal-to-noise ratio and will be able to output processed data in real time with millisecond latency. The system has been installed on 8 previously unused channels of the JET vertical bolometer system. Initial results suggest good agreement with data from existing vertical channels but with higher bandwidth and signal-to-noise ratio.

Imaging of a Defect in Thin Plates Using the Time Reversal of Single Mode Lamb Waves

NASA Astrophysics Data System (ADS)

Jeong, Hyunjo; Lee, Jung-Sik; Bae, Sung-Min

2011-06-01

This paper presents an analytical investigation for a baseline-free imaging of a defect in plate-like structures using the time-reversal of Lamb waves. We first consider the flexural wave (A0 mode) propagation in a plate containing a defect, and reception and time reversal process of the output signal at the receiver. The received output signal is then composed of two parts: a directly propagated wave and a scattered wave from the defect. The time reversal of these waves recovers the original input signal, and produces two additional sidebands that contain the time-of-flight information on the defect location. One of the side band signals is then extracted as a pure defect signal. A defect localization image is then constructed from a beamforming technique based on the time-frequency analysis of the side band signal for each transducer pair in a network of sensors. The simulation results show that the proposed scheme enables the accurate, baseline-free detection of a defect, so that experimental studies are needed to verify the proposed method and to be applied to real structure.

Method and apparatus for measuring flow velocity using matched filters

DOEpatents

Raptis, Apostolos C.

1983-01-01

An apparatus and method for measuring the flow velocities of individual phase flow components of a multiphase flow utilizes matched filters. Signals arising from flow noise disturbance are extracted from the flow, at upstream and downstream locations. The signals are processed through pairs of matched filters which are matched to the flow disturbance frequency characteristics of the phase flow component to be measured. The processed signals are then cross-correlated to determine the transit delay time of the phase flow component between sensing positions.

Remote Whispering Applying Time Reversal

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

Anderson, Brian Eric

The purpose of this project was to explore the use of time reversal technologies as a means for communication to a targeted individual or location. The idea is to have the privacy of whispering in one’s ear, but to do this remotely from loudspeakers not located near the target. Applications of this work include communicating with hostages and survivors in rescue operations, communicating imaging and operational conditions in deep drilling operations, monitoring storage of spent nuclear fuel in storage casks without wires, or clandestine activities requiring signaling between specific points. This technology provides a solution in any application where wiresmore » and radio communications are not possible or not desired. It also may be configured to self calibrate on a regular basis to adjust for changing conditions. These communications allow two people to converse with one another in real time, converse in an inaudible frequency range or medium (i.e. using ultrasonic frequencies and/or sending vibrations through a structure), or send information for a system to interpret (even allowing remote control of a system using sound). The time reversal process allows one to focus energy to a specific location in space and to send a clean transmission of a selected signal only to that location. In order for the time reversal process to work, a calibration signal must be obtained. This signal may be obtained experimentally using an impulsive sound, a known chirp signal, or other known signals. It may also be determined from a numerical model of a known environment in which the focusing is desired or from passive listening over time to ambient noise.« less

Certification of windshear performance with RTCA class D radomes

NASA Technical Reports Server (NTRS)

Mathews, Bruce D.; Miller, Fran; Rittenhouse, Kirk; Barnett, Lee; Rowe, William

1994-01-01

Superposition testing of detection range performance forms a digital signal for input into a simulation of signal and data processing equipment and algorithms to be employed in a sensor system for advanced warning of hazardous windshear. For suitable pulse-Doppler radar, recording of the digital data at the input to the digital signal processor furnishes a realistic operational scenario and environmentally responsive clutter signal including all sidelobe clutter, ground moving target indications (GMTI), and large signal spurious due to mainbeam clutter and/or RFI respective of the urban airport clutter and aircraft scenarios (approach and landing antenna pointing). For linear radar system processes, a signal at the same point in the process from a hazard phenomena may be calculated from models of the scattering phenomena, for example, as represented in fine 3 dimensional reflectivity and velocity grid structures. Superposition testing furnishes a competing signal environment for detection and warning time performance confirmation of phenomena uncontrollable in a natural environment.

Real time SAR processing

NASA Technical Reports Server (NTRS)

Premkumar, A. B.; Purviance, J. E.

1990-01-01

A simplified model for the SAR imaging problem is presented. The model is based on the geometry of the SAR system. Using this model an expression for the entire phase history of the received SAR signal is formulated. From the phase history, it is shown that the range and the azimuth coordinates for a point target image can be obtained by processing the phase information during the intrapulse and interpulse periods respectively. An architecture for a VLSI implementation for the SAR signal processor is presented which generates images in real time. The architecture uses a small number of chips, a new correlation processor, and an efficient azimuth correlation process.

Global interrupt and barrier networks

DOEpatents

Blumrich, Matthias A.; Chen, Dong; Coteus, Paul W.; Gara, Alan G.; Giampapa, Mark E; Heidelberger, Philip; Kopcsay, Gerard V.; Steinmacher-Burow, Burkhard D.; Takken, Todd E.

2008-10-28

A system and method for generating global asynchronous signals in a computing structure. Particularly, a global interrupt and barrier network is implemented that implements logic for generating global interrupt and barrier signals for controlling global asynchronous operations performed by processing elements at selected processing nodes of a computing structure in accordance with a processing algorithm; and includes the physical interconnecting of the processing nodes for communicating the global interrupt and barrier signals to the elements via low-latency paths. The global asynchronous signals respectively initiate interrupt and barrier operations at the processing nodes at times selected for optimizing performance of the processing algorithms. In one embodiment, the global interrupt and barrier network is implemented in a scalable, massively parallel supercomputing device structure comprising a plurality of processing nodes interconnected by multiple independent networks, with each node including one or more processing elements for performing computation or communication activity as required when performing parallel algorithm operations. One multiple independent network includes a global tree network for enabling high-speed global tree communications among global tree network nodes or sub-trees thereof. The global interrupt and barrier network may operate in parallel with the global tree network for providing global asynchronous sideband signals.

A computer controlled signal preprocessor for laser fringe anemometer applications

NASA Technical Reports Server (NTRS)

Oberle, Lawrence G.

1987-01-01

The operation of most commercially available laser fringe anemometer (LFA) counter-processors assumes that adjustments are made to the signal processing independent of the computer used for reducing the data acquired. Not only does the researcher desire a record of these parameters attached to the data acquired, but changes in flow conditions generally require that these settings be changed to improve data quality. Because of this limitation, on-line modification of the data acquisition parameters can be difficult and time consuming. A computer-controlled signal preprocessor has been developed which makes possible this optimization of the photomultiplier signal as a normal part of the data acquisition process. It allows computer control of the filter selection, signal gain, and photo-multiplier voltage. The raw signal from the photomultiplier tube is input to the preprocessor which, under the control of a digital computer, filters the signal and amplifies it to an acceptable level. The counter-processor used at Lewis Research Center generates the particle interarrival times, as well as the time-of-flight of the particle through the probe volume. The signal preprocessor allows computer control of the acquisition of these data.Through the preprocessor, the computer also can control the hand shaking signals for the interface between itself and the counter-processor. Finally, the signal preprocessor splits the pedestal from the signal before filtering, and monitors the photo-multiplier dc current, sends a signal proportional to this current to the computer through an analog to digital converter, and provides an alarm if the current exceeds a predefined maximum. Complete drawings and explanations are provided in the text as well as a sample interface program for use with the data acquisition software.

Improving Walkability Through Control Strategies at Signalized Intersections

DOT National Transportation Integrated Search

2017-01-01

As cities and communities nationwide seek to develop Complete Streets that foster livability and accommodate all modes, signal timing control strategies that include pedestrians in the operational decision process are gaining importance. This researc...

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

DTIC Science & Technology

1978-06-01

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

EARLINET Single Calculus Chain - technical - Part 1: Pre-processing of raw lidar data

NASA Astrophysics Data System (ADS)

D'Amico, Giuseppe; Amodeo, Aldo; Mattis, Ina; Freudenthaler, Volker; Pappalardo, Gelsomina

2016-02-01

In this paper we describe an automatic tool for the pre-processing of aerosol lidar data called ELPP (EARLINET Lidar Pre-Processor). It is one of two calculus modules of the EARLINET Single Calculus Chain (SCC), the automatic tool for the analysis of EARLINET data. ELPP is an open source module that executes instrumental corrections and data handling of the raw lidar signals, making the lidar data ready to be processed by the optical retrieval algorithms. According to the specific lidar configuration, ELPP automatically performs dead-time correction, atmospheric and electronic background subtraction, gluing of lidar signals, and trigger-delay correction. Moreover, the signal-to-noise ratio of the pre-processed signals can be improved by means of configurable time integration of the raw signals and/or spatial smoothing. ELPP delivers the statistical uncertainties of the final products by means of error propagation or Monte Carlo simulations. During the development of ELPP, particular attention has been payed to make the tool flexible enough to handle all lidar configurations currently used within the EARLINET community. Moreover, it has been designed in a modular way to allow an easy extension to lidar configurations not yet implemented. The primary goal of ELPP is to enable the application of quality-assured procedures in the lidar data analysis starting from the raw lidar data. This provides the added value of full traceability of each delivered lidar product. Several tests have been performed to check the proper functioning of ELPP. The whole SCC has been tested with the same synthetic data sets, which were used for the EARLINET algorithm inter-comparison exercise. ELPP has been successfully employed for the automatic near-real-time pre-processing of the raw lidar data measured during several EARLINET inter-comparison campaigns as well as during intense field campaigns.

Teaching Earth Signals Analysis Using the Java-DSP Earth Systems Edition: Modern and Past Climate Change

ERIC Educational Resources Information Center

Ramamurthy, Karthikeyan Natesan; Hinnov, Linda A.; Spanias, Andreas S.

2014-01-01

Modern data collection in the Earth Sciences has propelled the need for understanding signal processing and time-series analysis techniques. However, there is an educational disconnect in the lack of instruction of time-series analysis techniques in many Earth Science academic departments. Furthermore, there are no platform-independent freeware…

Solar loading thermography: Time-lapsed thermographic survey and advanced thermographic signal processing for the inspection of civil engineering and cultural heritage structures

NASA Astrophysics Data System (ADS)

Ibarra-Castanedo, Clemente; Sfarra, Stefano; Klein, Matthieu; Maldague, Xavier

2017-05-01

The experimental results from infrared thermography surveys over two buildings externally exposed walls are presented. Data acquisition was performed on a static configuration by recording direct and indirect solar loading during several days and was processed using advanced signal processing techniques in order to increase signal-to-noise ratio and signature contrast of the elements of interest. It is demonstrated that it is possible to detect the thermal signature of large internal structures as well as surface features under such thermographic scenarios. Results from a long-wave microbolometer compared favorably to those from a mid-wave cooled infrared camera for the detection of large subsurface features from unprocessed images. In both cases, however, advanced signal processing greatly improved contrast of the internal features.

Design and Experiment of Electrooculogram (EOG) System and Its Application to Control Mobile Robot

NASA Astrophysics Data System (ADS)

Sanjaya, W. S. M.; Anggraeni, D.; Multajam, R.; Subkhi, M. N.; Muttaqien, I.

2017-03-01

In this paper, we design and investigate a biological signal detection of eye movements (Electrooculogram). To detect a signal of Electrooculogram (EOG) used 4 instrument amplifier process; differential instrumentation amplifier, High Pass Filter (HPF) with 3 stage filters, Low Pass Filter (LPF) with 3 stage filters and Level Shifter circuit. The total of amplifying is 1000 times of gain, with frequency range 0.5-30 Hz. IC OP-Amp OP07 was used for all amplifying process. EOG signal will be read as analog input for Arduino microprocessor, and will interfaced with serial communication to PC Monitor using Processing® software. The result of this research show a differences value of eye movements. Differences signal of EOG have been applied to navigation control of the mobile robot. In this research, all communication process using Bluetooth HC-05.

Variable threshold method for ECG R-peak detection.

PubMed

Kew, Hsein-Ping; Jeong, Do-Un

2011-10-01

In this paper, a wearable belt-type ECG electrode worn around the chest by measuring the real-time ECG is produced in order to minimize the inconvenient in wearing. ECG signal is detected using a potential instrument system. The measured ECG signal is transmits via an ultra low power consumption wireless data communications unit to personal computer using Zigbee-compatible wireless sensor node. ECG signals carry a lot of clinical information for a cardiologist especially the R-peak detection in ECG. R-peak detection generally uses the threshold value which is fixed. There will be errors in peak detection when the baseline changes due to motion artifacts and signal size changes. Preprocessing process which includes differentiation process and Hilbert transform is used as signal preprocessing algorithm. Thereafter, variable threshold method is used to detect the R-peak which is more accurate and efficient than fixed threshold value method. R-peak detection using MIT-BIH databases and Long Term Real-Time ECG is performed in this research in order to evaluate the performance analysis.

Theoretical analysis of degradation mechanisms in the formation of morphogen gradients

NASA Astrophysics Data System (ADS)

Bozorgui, Behnaz; Teimouri, Hamid; Kolomeisky, Anatoly B.

2015-07-01

Fundamental biological processes of development of tissues and organs in multicellular organisms are governed by various signaling molecules, which are called morphogens. It is known that spatial and temporal variations in the concentration profiles of signaling molecules, which are frequently referred as morphogen gradients, lead to a cell differentiation via activating specific genes in a concentration-dependent manner. It is widely accepted that the establishment of the morphogen gradients involves multiple biochemical reactions and diffusion processes. One of the critical elements in the formation of morphogen gradients is a degradation of signaling molecules. We develop a new theoretical approach that provides a comprehensive description of the degradation mechanisms. It is based on the idea that the degradation works as an effective potential that drives the signaling molecules away from the source region. Utilizing the method of first-passage processes, the dynamics of the formation of morphogen gradients for various degradation mechanisms is explicitly evaluated. It is found that linear degradation processes lead to a dynamic behavior specified by times to form the morphogen gradients that depend linearly on the distance from the source. This is because the effective potential due to the degradation is quite strong. At the same time, nonlinear degradation mechanisms yield a quadratic scaling in the morphogen gradients formation times since the effective potentials are much weaker. Physical-chemical explanations of these phenomena are presented.

A front-end readout Detector Board for the OpenPET electronics system

NASA Astrophysics Data System (ADS)

Choong, W.-S.; Abu-Nimeh, F.; Moses, W. W.; Peng, Q.; Vu, C. Q.; Wu, J.-Y.

2015-08-01

We present a 16-channel front-end readout board for the OpenPET electronics system. A major task in developing a nuclear medical imaging system, such as a positron emission computed tomograph (PET) or a single-photon emission computed tomograph (SPECT), is the electronics system. While there are a wide variety of detector and camera design concepts, the relatively simple nature of the acquired data allows for a common set of electronics requirements that can be met by a flexible, scalable, and high-performance OpenPET electronics system. The analog signals from the different types of detectors used in medical imaging share similar characteristics, which allows for a common analog signal processing. The OpenPET electronics processes the analog signals with Detector Boards. Here we report on the development of a 16-channel Detector Board. Each signal is digitized by a continuously sampled analog-to-digital converter (ADC), which is processed by a field programmable gate array (FPGA) to extract pulse height information. A leading edge discriminator creates a timing edge that is ``time stamped'' by a time-to-digital converter (TDC) implemented inside the FPGA . This digital information from each channel is sent to an FPGA that services 16 analog channels, and then information from multiple channels is processed by this FPGA to perform logic for crystal lookup, DOI calculation, calibration, etc.

A front-end readout Detector Board for the OpenPET electronics system

DOE PAGES

Choong, W. -S.; Abu-Nimeh, F.; Moses, W. W.; ...

2015-08-12

Here, we present a 16-channel front-end readout board for the OpenPET electronics system. A major task in developing a nuclear medical imaging system, such as a positron emission computed tomograph (PET) or a single-photon emission computed tomograph (SPECT), is the electronics system. While there are a wide variety of detector and camera design concepts, the relatively simple nature of the acquired data allows for a common set of electronics requirements that can be met by a flexible, scalable, and high-performance OpenPET electronics system. The analog signals from the different types of detectors used in medical imaging share similar characteristics, whichmore » allows for a common analog signal processing. The OpenPET electronics processes the analog signals with Detector Boards. Here we report on the development of a 16-channel Detector Board. Each signal is digitized by a continuously sampled analog-to-digital converter (ADC), which is processed by a field programmable gate array (FPGA) to extract pulse height information. A leading edge discriminator creates a timing edge that is "time stamped" by a time-to-digital converter (TDC) implemented inside the FPGA. In conclusion, this digital information from each channel is sent to an FPGA that services 16 analog channels, and then information from multiple channels is processed by this FPGA to perform logic for crystal lookup, DOI calculation, calibration, etc.« less

Integration of digital signal processing technologies with pulsed electron paramagnetic resonance imaging

PubMed Central

Pursley, Randall H.; Salem, Ghadi; Devasahayam, Nallathamby; Subramanian, Sankaran; Koscielniak, Janusz; Krishna, Murali C.; Pohida, Thomas J.

2006-01-01

The integration of modern data acquisition and digital signal processing (DSP) technologies with Fourier transform electron paramagnetic resonance (FT-EPR) imaging at radiofrequencies (RF) is described. The FT-EPR system operates at a Larmor frequency (Lf) of 300 MHz to facilitate in vivo studies. This relatively low frequency Lf, in conjunction with our ~10 MHz signal bandwidth, enables the use of direct free induction decay time-locked subsampling (TLSS). This particular technique provides advantages by eliminating the traditional analog intermediate frequency downconversion stage along with the corresponding noise sources. TLSS also results in manageable sample rates that facilitate the design of DSP-based data acquisition and image processing platforms. More specifically, we utilize a high-speed field programmable gate array (FPGA) and a DSP processor to perform advanced real-time signal and image processing. The migration to a DSP-based configuration offers the benefits of improved EPR system performance, as well as increased adaptability to various EPR system configurations (i.e., software configurable systems instead of hardware reconfigurations). The required modifications to the FT-EPR system design are described, with focus on the addition of DSP technologies including the application-specific hardware, software, and firmware developed for the FPGA and DSP processor. The first results of using real-time DSP technologies in conjunction with direct detection bandpass sampling to implement EPR imaging at RF frequencies are presented. PMID:16243552

A real-time spectrum acquisition system design based on quantum dots-quantum well detector

NASA Astrophysics Data System (ADS)

Zhang, S. H.; Guo, F. M.

2016-01-01

In this paper, we studied the structure characteristics of quantum dots-quantum well photodetector with response wavelength range from 400 nm to 1000 nm. It has the characteristics of high sensitivity, low dark current and the high conductance gain. According to the properties of the quantum dots-quantum well photodetectors, we designed a new type of capacitive transimpedence amplifier (CTIA) readout circuit structure with the advantages of adjustable gain, wide bandwidth and high driving ability. We have implemented the chip packaging between CTIA-CDS structure readout circuit and quantum dots detector and tested the readout response characteristics. According to the timing signals requirements of our readout circuit, we designed a real-time spectral data acquisition system based on FPGA and ARM. Parallel processing mode of programmable devices makes the system has high sensitivity and high transmission rate. In addition, we realized blind pixel compensation and smoothing filter algorithm processing to the real time spectrum data by using C++. Through the fluorescence spectrum measurement of carbon quantum dots and the signal acquisition system and computer software system to realize the collection of the spectrum signal processing and analysis, we verified the excellent characteristics of detector. It meets the design requirements of quantum dot spectrum acquisition system with the characteristics of short integration time, real-time and portability.

The software system development for the TAMU real-time fan beam scatterometer data processors

NASA Technical Reports Server (NTRS)

Clark, B. V.; Jean, B. R.

1980-01-01

A software package was designed and written to process in real-time any one quadrature channel pair of radar scatterometer signals form the NASA L- or C-Band radar scatterometer systems. The software was successfully tested in the C-Band processor breadboard hardware using recorded radar and NERDAS (NASA Earth Resources Data Annotation System) signals as the input data sources. The processor development program and the overall processor theory of operation and design are described. The real-time processor software system is documented and the results of the laboratory software tests, and recommendations for the efficient application of the data processing capabilities are presented.

Ultrafast chirped optical waveform recorder using a time microscope

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

Bennett, Corey Vincent

2015-04-21

A new technique for capturing both the amplitude and phase of an optical waveform is presented. This technique can capture signals with many THz of bandwidths in a single shot (e.g., temporal resolution of about 44 fs), or be operated repetitively at a high rate. That is, each temporal window (or frame) is captured single shot, in real time, but the process may be run repeatedly or single-shot. By also including a variety of possible demultiplexing techniques, this process is scalable to recoding continuous signals.

Use of Mueller and non-Mueller matrices to describe polarization properties of telescope-based polarimeters

NASA Astrophysics Data System (ADS)

Seagraves, P. H.; Elmore, David F.

1994-09-01

Systems using optical elements such as linear polarizers, retarders, and mirrors can be represented by Mueller matrices. Some polarimeters include elements with time-varying polarization properties, multiple light beams, light detectors, and signal processing equipment. Standard Mueller matrix forms describing time-varying retarders, and beam splitters are presented, as well as non-Mueller matrices which describe detection and signal processing. These matrices provide a compact and intuitive mathematical description of polarimeter response which can aid in the refining of instrument designs.

Study of time reversibility/irreversibility of cardiovascular data: theoretical results and application to laser Doppler flowmetry and heart rate variability signals

NASA Astrophysics Data System (ADS)

Humeau-Heurtier, Anne; Mahé, Guillaume; Chapeau-Blondeau, François; Rousseau, David; Abraham, Pierre

2012-07-01

Time irreversibility can be qualitatively defined as the degree of a signal for temporal asymmetry. Recently, a time irreversibility characterization method based on entropies of positive and negative increments has been proposed for experimental signals and applied to heart rate variability (HRV) data (central cardiovascular system (CVS)). The results led to interesting information as a time asymmetry index was found different for young subjects and elderly people or heart disease patients. Nevertheless, similar analyses have not yet been conducted on laser Doppler flowmetry (LDF) signals (peripheral CVS). We first propose to further investigate the above-mentioned characterization method. Then, LDF signals, LDF signals reduced to samples acquired during ECG R peaks (LDF_RECG signals) and HRV recorded simultaneously in healthy subjects are processed. Entropies of positive and negative increments for LDF signals show a nonmonotonic pattern: oscillations—more or less pronounced, depending on subjects—are found with a period matching the one of cardiac activity. However, such oscillations are not found with LDF_RECG nor with HRV. Moreover, the asymmetry index for LDF is markedly different from the ones of LDF_RECG and HRV. The cardiac activity may therefore play a dominant role in the time irreversibility properties of LDF signals.

Vehicle Position Estimation Based on Magnetic Markers: Enhanced Accuracy by Compensation of Time Delays.

PubMed

Byun, Yeun-Sub; Jeong, Rag-Gyo; Kang, Seok-Won

2015-11-13

The real-time recognition of absolute (or relative) position and orientation on a network of roads is a core technology for fully automated or driving-assisted vehicles. This paper presents an empirical investigation of the design, implementation, and evaluation of a self-positioning system based on a magnetic marker reference sensing method for an autonomous vehicle. Specifically, the estimation accuracy of the magnetic sensing ruler (MSR) in the up-to-date estimation of the actual position was successfully enhanced by compensating for time delays in signal processing when detecting the vertical magnetic field (VMF) in an array of signals. In this study, the signal processing scheme was developed to minimize the effects of the distortion of measured signals when estimating the relative positional information based on magnetic signals obtained using the MSR. In other words, the center point in a 2D magnetic field contour plot corresponding to the actual position of magnetic markers was estimated by tracking the errors between pre-defined reference models and measured magnetic signals. The algorithm proposed in this study was validated by experimental measurements using a test vehicle on a pilot network of roads. From the results, the positioning error was found to be less than 0.04 m on average in an operational test.

Vehicle Position Estimation Based on Magnetic Markers: Enhanced Accuracy by Compensation of Time Delays

PubMed Central

Byun, Yeun-Sub; Jeong, Rag-Gyo; Kang, Seok-Won

2015-01-01

The real-time recognition of absolute (or relative) position and orientation on a network of roads is a core technology for fully automated or driving-assisted vehicles. This paper presents an empirical investigation of the design, implementation, and evaluation of a self-positioning system based on a magnetic marker reference sensing method for an autonomous vehicle. Specifically, the estimation accuracy of the magnetic sensing ruler (MSR) in the up-to-date estimation of the actual position was successfully enhanced by compensating for time delays in signal processing when detecting the vertical magnetic field (VMF) in an array of signals. In this study, the signal processing scheme was developed to minimize the effects of the distortion of measured signals when estimating the relative positional information based on magnetic signals obtained using the MSR. In other words, the center point in a 2D magnetic field contour plot corresponding to the actual position of magnetic markers was estimated by tracking the errors between pre-defined reference models and measured magnetic signals. The algorithm proposed in this study was validated by experimental measurements using a test vehicle on a pilot network of roads. From the results, the positioning error was found to be less than 0.04 m on average in an operational test. PMID:26580622

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

PubMed

Terrien, Jérémy; Marque, Catherine; Germain, Guy

2008-05-01

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

NASA Pioneer: Venus reverse playback telemetry program TR 78-2

NASA Technical Reports Server (NTRS)

Modestino, J. W.; Daut, D. G.; Vickers, A. L.; Matis, K. R.

1978-01-01

During the entry of the Pioneer Venus Atmospheric Probes into the Venus atmosphere, there were several events (RF blackout and data rate changes) which caused the ground receiving equipment to lose lock on the signal. This caused periods of data loss immediately following each one of these disturbing events which lasted until all the ground receiving units (receiver, subcarrier demodulator, symbol synchronizer, and sequential decoder) acquired lock once more. A scheme to recover these data by off-line data processing was implemented. This scheme consisted of receiving the S band signals from the probes with an open loop reciever (requiring no lock up on the signal) in parallel with the closed loop receivers of the real time receiving equipment, down converting the signals to baseband, and recording them on an analog recorder. The off-line processing consisted of playing the analog recording in the reverse direction (starting with the end of the tape) up, converting the signal to S-band, feeding the signal into the "real time" receiving system and recording on digital tape, the soft decisions from the symbol synchronizer.

[Image processing system of visual prostheses based on digital signal processor DM642].

PubMed

Xie, Chengcheng; Lu, Yanyu; Gu, Yun; Wang, Jing; Chai, Xinyu

2011-09-01

This paper employed a DSP platform to create the real-time and portable image processing system, and introduced a series of commonly used algorithms for visual prostheses. The results of performance evaluation revealed that this platform could afford image processing algorithms to be executed in real time.

Quantitative multi-color FRET measurements by Fourier lifetime excitation-emission matrix spectroscopy.

PubMed

Zhao, Ming; Huang, Run; Peng, Leilei

2012-11-19

Förster resonant energy transfer (FRET) is extensively used to probe macromolecular interactions and conformation changes. The established FRET lifetime analysis method measures the FRET process through its effect on the donor lifetime. In this paper we present a method that directly probes the time-resolved FRET signal with frequency domain Fourier lifetime excitation-emission matrix (FLEEM) measurements. FLEEM separates fluorescent signals by their different phonon energy pathways from excitation to emission. The FRET process generates a unique signal channel that is initiated by donor excitation but ends with acceptor emission. Time-resolved analysis of the FRET EEM channel allows direct measurements on the FRET process, unaffected by free fluorophores that might be present in the sample. Together with time-resolved analysis on non-FRET channels, i.e. donor and acceptor EEM channels, time resolved EEM analysis allows precise quantification of FRET in the presence of free fluorophores. The method is extended to three-color FRET processes, where quantification with traditional methods remains challenging because of the significantly increased complexity in the three-way FRET interactions. We demonstrate the time-resolved EEM analysis method with quantification of three-color FRET in incompletely hybridized triple-labeled DNA oligonucleotides. Quantitative measurements of the three-color FRET process in triple-labeled dsDNA are obtained in the presence of free single-labeled ssDNA and double-labeled dsDNA. The results establish a quantification method for studying multi-color FRET between multiple macromolecules in biochemical equilibrium.

Quantitative multi-color FRET measurements by Fourier lifetime excitation-emission matrix spectroscopy

PubMed Central

Zhao, Ming; Huang, Run; Peng, Leilei

2012-01-01

Förster resonant energy transfer (FRET) is extensively used to probe macromolecular interactions and conformation changes. The established FRET lifetime analysis method measures the FRET process through its effect on the donor lifetime. In this paper we present a method that directly probes the time-resolved FRET signal with frequency domain Fourier lifetime excitation-emission matrix (FLEEM) measurements. FLEEM separates fluorescent signals by their different phonon energy pathways from excitation to emission. The FRET process generates a unique signal channel that is initiated by donor excitation but ends with acceptor emission. Time-resolved analysis of the FRET EEM channel allows direct measurements on the FRET process, unaffected by free fluorophores that might be present in the sample. Together with time-resolved analysis on non-FRET channels, i.e. donor and acceptor EEM channels, time resolved EEM analysis allows precise quantification of FRET in the presence of free fluorophores. The method is extended to three-color FRET processes, where quantification with traditional methods remains challenging because of the significantly increased complexity in the three-way FRET interactions. We demonstrate the time-resolved EEM analysis method with quantification of three-color FRET in incompletely hybridized triple-labeled DNA oligonucleotides. Quantitative measurements of the three-color FRET process in triple-labeled dsDNA are obtained in the presence of free single-labeled ssDNA and double-labeled dsDNA. The results establish a quantification method for studying multi-color FRET between multiple macromolecules in biochemical equilibrium. PMID:23187535

Enhancement of MS Signal Processing For Improved Cancer Biomarker Discovery

NASA Astrophysics Data System (ADS)

Si, Qian

Technological advances in proteomics have shown great potential in detecting cancer at the earliest stages. One way is to use the time of flight mass spectroscopy to identify biomarkers, or early disease indicators related to the cancer. Pattern analysis of time of flight mass spectra data from blood and tissue samples gives great hope for the identification of potential biomarkers among the complex mixture of biological and chemical samples for the early cancer detection. One of the keys issues is the pre-processing of raw mass spectra data. A lot of challenges need to be addressed: unknown noise character associated with the large volume of data, high variability in the mass spectroscopy measurements, and poorly understood signal background and so on. This dissertation focuses on developing statistical algorithms and creating data mining tools for computationally improved signal processing for mass spectrometry data. I have introduced an advanced accurate estimate of the noise model and a half-supervised method of mass spectrum data processing which requires little knowledge about the data.

Software for a GPS-Reflection Remote-Sensing System

NASA Technical Reports Server (NTRS)

Lowe, Stephen

2003-01-01

A special-purpose software Global Positioning System (GPS) receiver designed for remote sensing with reflected GPS signals is described in Delay/Doppler-Mapping GPS-Reflection Remote-Sensing System (NPO-30385), which appears elsewhere in this issue of NASA Tech Briefs. The input accepted by this program comprises raw (open-loop) digitized GPS signals sampled at a rate of about 20 MHz. The program processes the data samples to perform the following functions: detection of signals; tracking of phases and delays; mapping of delay, Doppler, and delay/Doppler waveforms; dual-frequency processing; coherent integrations as short as 125 s; decoding of navigation messages; and precise time tagging of observable quantities. The software can perform these functions on all detectable satellite signals without dead time. Open-loop data collected over water, land, or ice and processed by this software can be further processed to extract geophysical information. Possible examples include mean sea height, wind speed and direction, and significant wave height (for observations over the ocean); bistatic-radar terrain images and measures of soil moisture and biomass (for observations over land); and estimates of ice age, thickness, and surface density (for observations over ice).

A Two-Stage Process Model of Sensory Discrimination: An Alternative to Drift-Diffusion

PubMed Central

Landy, Michael S.

2016-01-01

Discrimination of the direction of motion of a noisy stimulus is an example of sensory discrimination under uncertainty. For stimuli that are extended in time, reaction time is quicker for larger signal values (e.g., discrimination of opposite directions of motion compared with neighboring orientations) and larger signal strength (e.g., stimuli with higher contrast or motion coherence, that is, lower noise). The standard model of neural responses (e.g., in lateral intraparietal cortex) and reaction time for discrimination is drift-diffusion. This model makes two clear predictions. (1) The effects of signal strength and value on reaction time should interact multiplicatively because the diffusion process depends on the signal-to-noise ratio. (2) If the diffusion process is interrupted, as in a cued-response task, the time to decision after the cue should be independent of the strength of accumulated sensory evidence. In two experiments with human participants, we show that neither prediction holds. A simple alternative model is developed that is consistent with the results. In this estimate-then-decide model, evidence is accumulated until estimation precision reaches a threshold value. Then, a decision is made with duration that depends on the signal-to-noise ratio achieved by the first stage. SIGNIFICANCE STATEMENT Sensory decision-making under uncertainty is usually modeled as the slow accumulation of noisy sensory evidence until a threshold amount of evidence supporting one of the possible decision outcomes is reached. Furthermore, it has been suggested that this accumulation process is reflected in neural responses, e.g., in lateral intraparietal cortex. We derive two behavioral predictions of this model and show that neither prediction holds. We introduce a simple alternative model in which evidence is accumulated until a sufficiently precise estimate of the stimulus is achieved, and then that estimate is used to guide the discrimination decision. This model is consistent with the behavioral data. PMID:27807167

A Two-Stage Process Model of Sensory Discrimination: An Alternative to Drift-Diffusion.

PubMed

Sun, Peng; Landy, Michael S

2016-11-02

Discrimination of the direction of motion of a noisy stimulus is an example of sensory discrimination under uncertainty. For stimuli that are extended in time, reaction time is quicker for larger signal values (e.g., discrimination of opposite directions of motion compared with neighboring orientations) and larger signal strength (e.g., stimuli with higher contrast or motion coherence, that is, lower noise). The standard model of neural responses (e.g., in lateral intraparietal cortex) and reaction time for discrimination is drift-diffusion. This model makes two clear predictions. (1) The effects of signal strength and value on reaction time should interact multiplicatively because the diffusion process depends on the signal-to-noise ratio. (2) If the diffusion process is interrupted, as in a cued-response task, the time to decision after the cue should be independent of the strength of accumulated sensory evidence. In two experiments with human participants, we show that neither prediction holds. A simple alternative model is developed that is consistent with the results. In this estimate-then-decide model, evidence is accumulated until estimation precision reaches a threshold value. Then, a decision is made with duration that depends on the signal-to-noise ratio achieved by the first stage. Sensory decision-making under uncertainty is usually modeled as the slow accumulation of noisy sensory evidence until a threshold amount of evidence supporting one of the possible decision outcomes is reached. Furthermore, it has been suggested that this accumulation process is reflected in neural responses, e.g., in lateral intraparietal cortex. We derive two behavioral predictions of this model and show that neither prediction holds. We introduce a simple alternative model in which evidence is accumulated until a sufficiently precise estimate of the stimulus is achieved, and then that estimate is used to guide the discrimination decision. This model is consistent with the behavioral data. Copyright © 2016 the authors 0270-6474/16/3611259-16$15.00/0.

Study on a Real-Time BEAM System for Diagnosis Assistance Based on a System on Chips Design

PubMed Central

Sung, Wen-Tsai; Chen, Jui-Ho; Chang, Kung-Wei

2013-01-01

As an innovative as well as an interdisciplinary research project, this study performed an analysis of brain signals so as to establish BrainIC as an auxiliary tool for physician diagnosis. Cognition behavior sciences, embedded technology, system on chips (SOC) design and physiological signal processing are integrated in this work. Moreover, a chip is built for real-time electroencephalography (EEG) processing purposes and a Brain Electrical Activity Mapping (BEAM) system, and a knowledge database is constructed to diagnose psychosis and body challenges in learning various behaviors and signals antithesis by a fuzzy inference engine. This work is completed with a medical support system developed for the mentally disabled or the elderly abled. PMID:23681095

A PC-based system for predicting movement from deep brain signals in Parkinson's disease.

PubMed

Loukas, Constantinos; Brown, Peter

2012-07-01

There is much current interest in deep brain stimulation (DBS) of the subthalamic nucleus (STN) for the treatment of Parkinson's disease (PD). This type of surgery has enabled unprecedented access to deep brain signals in the awake human. In this paper we present an easy-to-use computer based system for recording, displaying, archiving, and processing electrophysiological signals from the STN. The system was developed for predicting self-paced hand-movements in real-time via the online processing of the electrophysiological activity of the STN. It is hoped that such a computerised system might have clinical and experimental applications. For example, those sites within the STN most relevant to the processing of voluntary movement could be identified through the predictive value of their activities with respect to the timing of future movement. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

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.

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

PubMed Central

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

2011-01-01

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

Timing performance of phase-locked loops in optical pulse position modulation communication systems

NASA Astrophysics Data System (ADS)

Lafaw, D. A.

In an optical digital communication system, an accurate clock signal must be available at the receiver to provide proper synchronization with the transmitted signal. Phase synchronization is especially critical in M-ary pulse position modulation (PPM) systems where the optimum decision scheme is an energy detector which compares the energy in each of M time slots to decide which of M possible words was sent. A timing error causes energy spillover into adjacent time slots (a form of intersymbol interference) so that only a portion of the signal energy may be attributed to the correct time slot. This effect decreases the effective signal, increases the effective noise, and increases the probability of error. This report simulates a timing subsystem for a satellite-to-satellite optical PPM communication link. The receiver employs direct photodetection, preprocessing of the optical signal, and a phase-locked loop for timing synchronization. The photodetector output is modeled as a filtered, doubly stochastic Poisson shot noise process. The variance of the relative phase error is examined under varying signal strength conditions as an indication of loop performance, and simulation results are compared to theoretical relations.

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

DOEpatents

Qian, S.; Dunham, M.E.

1996-11-12

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

[3D-TV health assessment system by the multi-modal physiological signals].

PubMed

Li, Zhongqiang; Xing, Lidong; Qian, Zhiyu; Wang, Xiao; Yu, Defei; Liu, Baoyu; Jin, Shuai

2014-03-01

In order to meet the requirements of the multi-physiological signal measurement of the 3D-TV health assessment, try to find the suitable biological acquisition chips and design the hardware system which can detect different physiological signals in real time. The systems mainly uses ARM11/S3C6410 microcontroller to control the EEG/EOG acquisition chip RHA2116 and the ECG acquisition chip ADS1298, and then the microcontroller transfer the data collected by the chips to the PC software by the USB port which can display and save the experimental data in real time, then use the Matlab software for further processing of the data, finally make a final health assessment. In the meantime, for the different varieties in the different brain regions of watching 3D-TV, developed the special brain electrode placement and the experimental data processing methods, then effectively disposed the multi-signal data in the multilevel.

Noninvasive Diagnosis of Coronary Artery Disease Using 12-Lead High-Frequency Electrocardiograms

NASA Technical Reports Server (NTRS)

Schlegel, Todd T.; Arenare, Brian

2006-01-01

A noninvasive, sensitive method of diagnosing certain pathological conditions of the human heart involves computational processing of digitized electrocardiographic (ECG) signals acquired from a patient at all 12 conventional ECG electrode positions. In the processing, attention is focused on low-amplitude, high-frequency components of those portions of the ECG signals known in the art as QRS complexes. The unique contribution of this method lies in the utilization of signal features and combinations of signal features from various combinations of electrode positions, not reported previously, that have been found to be helpful in diagnosing coronary artery disease and such related pathological conditions as myocardial ischemia, myocardial infarction, and congestive heart failure. The electronic hardware and software used to acquire the QRS complexes and perform some preliminary analyses of their high-frequency components were summarized in Real-Time, High-Frequency QRS Electrocardiograph (MSC- 23154), NASA Tech Briefs, Vol. 27, No. 7 (July 2003), pp. 26-28. To recapitulate, signals from standard electrocardiograph electrodes are preamplified, then digitized at a sampling rate of 1,000 Hz, then analyzed by the software that detects R waves and QRS complexes and analyzes them from several perspectives. The software includes provisions for averaging signals over multiple beats and for special-purpose nonrecursive digital filters with specific low- and high-frequency cutoffs. These filters, applied to the averaged signal, effect a band-pass operation in the frequency range from 150 to 250 Hz. The output of the bandpass filter is the desired high-frequency QRS signal. Further processing is then performed in real time to obtain the beat-to-beat root mean square (RMS) voltage amplitude of the filtered signal, certain variations of the RMS voltage, and such standard measures as the heart rate and R-R interval at any given time. A key signal feature analyzed in the present method is the presence versus the absence of reduced-amplitude zones (RAZs). In terms that must be simplified for the sake of brevity, an RAZ comprises several cycles of a high-frequency QRS signal during which the amplitude of the high-frequency oscillation in a portion of the signal is abnormally low (see figure). A given signal sample exhibiting an interval of reduced amplitude may or may not be classified as an RAZ, depending on quantitative criteria regarding peaks and troughs within the reduced-amplitude portion of the high-frequency QRS signal. This analysis is performed in all 12 leads in real time.

Method for distinguishing multiple targets using time-reversal acoustics

DOEpatents

Berryman, James G.

2004-06-29

A method for distinguishing multiple targets using time-reversal acoustics. Time-reversal acoustics uses an iterative process to determine the optimum signal for locating a strongly reflecting target in a cluttered environment. An acoustic array sends a signal into a medium, and then receives the returned/reflected signal. This returned/reflected signal is then time-reversed and sent back into the medium again, and again, until the signal being sent and received is no longer changing. At that point, the array has isolated the largest eigenvalue/eigenvector combination and has effectively determined the location of a single target in the medium (the one that is most strongly reflecting). After the largest eigenvalue/eigenvector combination has been determined, to determine the location of other targets, instead of sending back the same signals, the method sends back these time reversed signals, but half of them will also be reversed in sign. There are various possibilities for choosing which half to do sign reversal. The most obvious choice is to reverse every other one in a linear array, or as in a checkerboard pattern in 2D. Then, a new send/receive, send-time reversed/receive iteration can proceed. Often, the first iteration in this sequence will be close to the desired signal from a second target. In some cases, orthogonalization procedures must be implemented to assure the returned signals are in fact orthogonal to the first eigenvector found.

Real-time fMRI processing with physiological noise correction - Comparison with off-line analysis.

PubMed

Misaki, Masaya; Barzigar, Nafise; Zotev, Vadim; Phillips, Raquel; Cheng, Samuel; Bodurka, Jerzy

2015-12-30

While applications of real-time functional magnetic resonance imaging (rtfMRI) are growing rapidly, there are still limitations in real-time data processing compared to off-line analysis. We developed a proof-of-concept real-time fMRI processing (rtfMRIp) system utilizing a personal computer (PC) with a dedicated graphic processing unit (GPU) to demonstrate that it is now possible to perform intensive whole-brain fMRI data processing in real-time. The rtfMRIp performs slice-timing correction, motion correction, spatial smoothing, signal scaling, and general linear model (GLM) analysis with multiple noise regressors including physiological noise modeled with cardiac (RETROICOR) and respiration volume per time (RVT). The whole-brain data analysis with more than 100,000voxels and more than 250volumes is completed in less than 300ms, much faster than the time required to acquire the fMRI volume. Real-time processing implementation cannot be identical to off-line analysis when time-course information is used, such as in slice-timing correction, signal scaling, and GLM. We verified that reduced slice-timing correction for real-time analysis had comparable output with off-line analysis. The real-time GLM analysis, however, showed over-fitting when the number of sampled volumes was small. Our system implemented real-time RETROICOR and RVT physiological noise corrections for the first time and it is capable of processing these steps on all available data at a given time, without need for recursive algorithms. Comprehensive data processing in rtfMRI is possible with a PC, while the number of samples should be considered in real-time GLM. Copyright © 2015 Elsevier B.V. All rights reserved.

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.

Initial Evaluation of Signal-Based Bayesian Monitoring

NASA Astrophysics Data System (ADS)

Moore, D.; Russell, S.

2016-12-01

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

A low-cost biomedical signal transceiver based on a Bluetooth wireless system.

PubMed

Fazel-Rezai, Reza; Pauls, Mark; Slawinski, David

2007-01-01

Most current wireless biomedical signal transceivers use range-limiting communication. This work presents a low-cost biomedical signal transceiver that uses Bluetooth wireless technology. The design is implemented in a modular form to be adaptable to different types of biomedical signals. The signal front end obtains and processes incoming signals, which are then transmitted via a microcontroller and wireless module. Near real-time receive software in LabVIEW was developed to demonstrate the system capability. The completed transmitter prototype successfully transmits ECG signals, and is able to simultaneously send multiple signals. The sampling rate of the transmitter is fast enough to send up to thirteen ECG signals simultaneously, with an error rate below 0.1% for transmission exceeding 65 meters. A low-cost wireless biomedical transceiver has many applications, such as real-time monitoring of patients with a known condition in non-clinical settings.

Audio signal analysis for tool wear monitoring in sheet metal stamping

NASA Astrophysics Data System (ADS)

Ubhayaratne, Indivarie; Pereira, Michael P.; Xiang, Yong; Rolfe, Bernard F.

2017-02-01

Stamping tool wear can significantly degrade product quality, and hence, online tool condition monitoring is a timely need in many manufacturing industries. Even though a large amount of research has been conducted employing different sensor signals, there is still an unmet demand for a low-cost easy to set up condition monitoring system. Audio signal analysis is a simple method that has the potential to meet this demand, but has not been previously used for stamping process monitoring. Hence, this paper studies the existence and the significance of the correlation between emitted sound signals and the wear state of sheet metal stamping tools. The corrupting sources generated by the tooling of the stamping press and surrounding machinery have higher amplitudes compared to that of the sound emitted by the stamping operation itself. Therefore, a newly developed semi-blind signal extraction technique was employed as a pre-processing technique to mitigate the contribution of these corrupting sources. The spectral analysis results of the raw and extracted signals demonstrate a significant qualitative relationship between wear progression and the emitted sound signature. This study lays the basis for employing low-cost audio signal analysis in the development of a real-time industrial tool condition monitoring system.

Distribution and Variability of Satellite-Derived Signals of Isolated Convection Initiation Events Over Central Eastern China

NASA Astrophysics Data System (ADS)

Huang, Yipeng; Meng, Zhiyong; Li, Jing; Li, Wanbiao; Bai, Lanqiang; Zhang, Murong; Wang, Xi

2017-11-01

This study combined measurements from the Chinese operational geostationary satellite Fengyun-2E (FY-2E) and ground-based weather radars to conduct a statistical survey of isolated convection initiation (CI) over central eastern China (CEC). The convective environment in CEC is modulated by the complex topography and monsoon climate. From May to August 2010, a total of 1,630 isolated CI signals were derived from FY-2E using a semiautomated method. The formation of these satellite-derived CI signals peaks in the early afternoon and occurs with high frequency in areas with remarkable terrain inhomogeneity (e.g., mountain, water, and mountain-water areas). The high signal frequency areas shift from northwest CEC (dry, high altitude) in early summer to southeast CEC (humid, low altitude) in midsummer along with an increasing monthly mean frequency. The satellite-derived CI signals tend to have longer lead times (the time difference between satellite-derived signal formation and radar-based CI) in the late morning and afternoon than in the early morning and night. During the early morning and night, the distinction between cloud top signatures and background terrestrial radiation becomes less apparent, resulting in delayed identification of the signals and thus short and even negative lead times. A decline in the lead time is observed from May to August, likely due to the increasing cloud growth rate and warm-rain processes. Results show increasing lead times with increasing landscape elevation, likely due to more warm-rain processes over the coastal sea and plain, along with a decreasing cloud growth rate from hill and mountain to the plateau.

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

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

NASA Astrophysics Data System (ADS)

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

2014-09-01

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

Stanford Hardware Development Program

NASA Technical Reports Server (NTRS)

Peterson, A.; Linscott, I.; Burr, J.

1986-01-01

Architectures for high performance, digital signal processing, particularly for high resolution, wide band spectrum analysis were developed. These developments are intended to provide instrumentation for NASA's Search for Extraterrestrial Intelligence (SETI) program. The real time signal processing is both formal and experimental. The efficient organization and optimal scheduling of signal processing algorithms were investigated. The work is complemented by efforts in processor architecture design and implementation. A high resolution, multichannel spectrometer that incorporates special purpose microcoded signal processors is being tested. A general purpose signal processor for the data from the multichannel spectrometer was designed to function as the processing element in a highly concurrent machine. The processor performance required for the spectrometer is in the range of 1000 to 10,000 million instructions per second (MIPS). Multiple node processor configurations, where each node performs at 100 MIPS, are sought. The nodes are microprogrammable and are interconnected through a network with high bandwidth for neighboring nodes, and medium bandwidth for nodes at larger distance. The implementation of both the current mutlichannel spectrometer and the signal processor as Very Large Scale Integration CMOS chip sets was commenced.

Trends in non-stationary signal processing techniques applied to vibration analysis of wind turbine drive train - A contemporary survey

NASA Astrophysics Data System (ADS)

Uma Maheswari, R.; Umamaheswari, R.

2017-02-01

Condition Monitoring System (CMS) substantiates potential economic benefits and enables prognostic maintenance in wind turbine-generator failure prevention. Vibration Monitoring and Analysis is a powerful tool in drive train CMS, which enables the early detection of impending failure/damage. In variable speed drives such as wind turbine-generator drive trains, the vibration signal acquired is of non-stationary and non-linear. The traditional stationary signal processing techniques are inefficient to diagnose the machine faults in time varying conditions. The current research trend in CMS for drive-train focuses on developing/improving non-linear, non-stationary feature extraction and fault classification algorithms to improve fault detection/prediction sensitivity and selectivity and thereby reducing the misdetection and false alarm rates. In literature, review of stationary signal processing algorithms employed in vibration analysis is done at great extent. In this paper, an attempt is made to review the recent research advances in non-linear non-stationary signal processing algorithms particularly suited for variable speed wind turbines.

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

Jang, Junhwan; Hwang, Sungui; Park, Kyihwan, E-mail: khpark@gist.ac.kr

To utilize a time-of-flight-based laser scanner as a distance measurement sensor, the measurable distance and accuracy are the most important performance parameters to consider. For these purposes, the optical system and electronic signal processing of the laser scanner should be optimally designed in order to reduce a distance error caused by the optical crosstalk and wide dynamic range input. Optical system design for removing optical crosstalk problem is proposed in this work. Intensity control is also considered to solve the problem of a phase-shift variation in the signal processing circuit caused by object reflectivity. The experimental results for optical systemmore » and signal processing design are performed using 3D measurements.« less

Multichannel Baseband Processor for Wideband CDMA

NASA Astrophysics Data System (ADS)

Jalloul, Louay M. A.; Lin, Jim

2005-12-01

The system architecture of the cellular base station modem engine (CBME) is described. The CBME is a single-chip multichannel transceiver capable of processing and demodulating signals from multiple users simultaneously. It is optimized to process different classes of code-division multiple-access (CDMA) signals. The paper will show that through key functional system partitioning, tightly coupled small digital signal processing cores, and time-sliced reuse architecture, CBME is able to achieve a high degree of algorithmic flexibility while maintaining efficiency. The paper will also highlight the implementation and verification aspects of the CBME chip design. In this paper, wideband CDMA is used as an example to demonstrate the architecture concept.

An accuracy aware low power wireless EEG unit with information content based adaptive data compression.

PubMed

Tolbert, Jeremy R; Kabali, Pratik; Brar, Simeranjit; Mukhopadhyay, Saibal

2009-01-01

We present a digital system for adaptive data compression for low power wireless transmission of Electroencephalography (EEG) data. The proposed system acts as a base-band processor between the EEG analog-to-digital front-end and RF transceiver. It performs a real-time accuracy energy trade-off for multi-channel EEG signal transmission by controlling the volume of transmitted data. We propose a multi-core digital signal processor for on-chip processing of EEG signals, to detect signal information of each channel and perform real-time adaptive compression. Our analysis shows that the proposed approach can provide significant savings in transmitter power with minimal impact on the overall signal accuracy.

Smart Sensors: Why and when the origin was and why and where the future will be

NASA Astrophysics Data System (ADS)

Corsi, C.

2013-12-01

Smart Sensors is a technique developed in the 70's when the processing capabilities, based on readout integrated with signal processing, was still far from the complexity needed in advanced IR surveillance and warning systems, because of the enormous amount of noise/unwanted signals emitted by operating scenario especially in military applications. The Smart Sensors technology was kept restricted within a close military environment exploding in applications and performances in the 90's years thanks to the impressive improvements in the integrated signal read-out and processing achieved by CCD-CMOS technologies in FPA. In fact the rapid advances of "very large scale integration" (VLSI) processor technology and mosaic EO detector array technology allowed to develop new generations of Smart Sensors with much improved signal processing by integrating microcomputers and other VLSI signal processors. inside the sensor structure achieving some basic functions of living eyes (dynamic stare, non-uniformity compensation, spatial and temporal filtering). New and future technologies (Nanotechnology, Bio-Organic Electronics, Bio-Computing) are lightning a new generation of Smart Sensors extending the Smartness from the Space-Time Domain to Spectroscopic Functional Multi-Domain Signal Processing. History and future forecasting of Smart Sensors will be reported.

Detection system for high-resolution gamma radiation spectroscopy with neutron time-of-flight filtering

DOEpatents

Dioszegi, Istvan; Salwen, Cynthia; Vanier, Peter

2014-12-30

A .gamma.-radiation detection system that includes at least one semiconductor detector such as HPGe-Detector, a position-sensitive .alpha.-Detector, a TOF Controller, and a Digitizer/Integrator. The Digitizer/Integrator starts to process the energy signals of a .gamma.-radiation sent from the HPGe-Detector instantly when the HPGe-Detector detects the .gamma.-radiation. Subsequently, it is determined whether a coincidence exists between the .alpha.-particles and .gamma.-radiation signal, based on a determination of the time-of-flight of neutrons obtained from the .alpha.-Detector and the HPGe-Detector. If it is determined that the time-of-flight falls within a predetermined coincidence window, the Digitizer/Integrator is allowed to continue and complete the energy signal processing. If, however, there is no coincidence, the Digitizer/Integrator is instructed to be clear and reset its operation instantly.

Inverting dynamic force microscopy: From signals to time-resolved interaction forces

PubMed Central

Stark, Martin; Stark, Robert W.; Heckl, Wolfgang M.; Guckenberger, Reinhard

2002-01-01

Transient forces between nanoscale objects on surfaces govern friction, viscous flow, and plastic deformation, occur during manipulation of matter, or mediate the local wetting behavior of thin films. To resolve transient forces on the (sub) microsecond time and nanometer length scale, dynamic atomic force microscopy (AFM) offers largely unexploited potential. Full spectral analysis of the AFM signal completes dynamic AFM. Inverting the signal formation process, we measure the time course of the force effective at the sensing tip. This approach yields rich insight into processes at the tip and dispenses with a priori assumptions about the interaction, as it relies solely on measured data. Force measurements on silicon under ambient conditions demonstrate the distinct signature of the interaction and reveal that peak forces exceeding 200 nN are applied to the sample in a typical imaging situation. These forces are 2 orders of magnitude higher than those in covalent bonds. PMID:12070341

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.

Eventogram: A Visual Representation of Main Events in Biomedical Signals.

PubMed

Elgendi, Mohamed

2016-09-22

Biomedical signals carry valuable physiological information and many researchers have difficulty interpreting and analyzing long-term, one-dimensional, quasi-periodic biomedical signals. Traditionally, biomedical signals are analyzed and visualized using periodogram, spectrogram, and wavelet methods. However, these methods do not offer an informative visualization of main events within the processed signal. This paper attempts to provide an event-related framework to overcome the drawbacks of the traditional visualization methods and describe the main events within the biomedical signal in terms of duration and morphology. Electrocardiogram and photoplethysmogram signals are used in the analysis to demonstrate the differences between the traditional visualization methods, and their performance is compared against the proposed method, referred to as the " eventogram " in this paper. The proposed method is based on two event-related moving averages that visualizes the main time-domain events in the processed biomedical signals. The traditional visualization methods were unable to find dominant events in processed signals while the eventogram was able to visualize dominant events in signals in terms of duration and morphology. Moreover, eventogram -based detection algorithms succeeded with detecting main events in different biomedical signals with a sensitivity and positive predictivity >95%. The output of the eventogram captured unique patterns and signatures of physiological events, which could be used to visualize and identify abnormal waveforms in any quasi-periodic signal.

Detection and recognition of mechanical, digging and vehicle signals in the optical fiber pre-warning system

NASA Astrophysics Data System (ADS)

Tian, Qing; Yang, Dan; Zhang, Yuan; Qu, Hongquan

2018-04-01

This paper presents detection and recognition method to locate and identify harmful intrusions in the optical fiber pre-warning system (OFPS). Inspired by visual attention architecture (VAA), the process flow is divided into two parts, i.e., data-driven process and task-driven process. At first, data-driven process takes all the measurements collected by the system as input signals, which is handled by detection method to locate the harmful intrusion in both spatial domain and time domain. Then, these detected intrusion signals are taken over by task-driven process. Specifically, we get pitch period (PP) and duty cycle (DC) of the intrusion signals to identify the mechanical and manual digging (MD) intrusions respectively. For the passing vehicle (PV) intrusions, their strong low frequency component can be used as good feature. In generally, since the harmful intrusion signals only account for a small part of whole measurements, the data-driven process reduces the amount of input data for subsequent task-driven process considerably. Furthermore, the task-driven process determines the harmful intrusions orderly according to their severity, which makes a priority mechanism for the system as well as targeted processing for different harmful intrusion. At last, real experiments are performed to validate the effectiveness of this method.

Position sensitive solid-state photomultipliers, systems and methods

DOEpatents

Shah, Kanai S; Christian, James; Stapels, Christopher; Dokhale, Purushottam; McClish, Mickel

2014-11-11

An integrated silicon solid state photomultiplier (SSPM) device includes a pixel unit including an array of more than 2.times.2 p-n photodiodes on a common substrate, a signal division network electrically connected to each photodiode, where the signal division network includes four output connections, a signal output measurement unit, a processing unit configured to identify the photodiode generating a signal or a center of mass of photodiodes generating a signal, and a global receiving unit.

SPICODYN: A Toolbox for the Analysis of Neuronal Network Dynamics and Connectivity from Multi-Site Spike Signal Recordings.

PubMed

Pastore, Vito Paolo; Godjoski, Aleksandar; Martinoia, Sergio; Massobrio, Paolo

2018-01-01

We implemented an automated and efficient open-source software for the analysis of multi-site neuronal spike signals. The software package, named SPICODYN, has been developed as a standalone windows GUI application, using C# programming language with Microsoft Visual Studio based on .NET framework 4.5 development environment. Accepted input data formats are HDF5, level 5 MAT and text files, containing recorded or generated time series spike signals data. SPICODYN processes such electrophysiological signals focusing on: spiking and bursting dynamics and functional-effective connectivity analysis. In particular, for inferring network connectivity, a new implementation of the transfer entropy method is presented dealing with multiple time delays (temporal extension) and with multiple binary patterns (high order extension). SPICODYN is specifically tailored to process data coming from different Multi-Electrode Arrays setups, guarantying, in those specific cases, automated processing. The optimized implementation of the Delayed Transfer Entropy and the High-Order Transfer Entropy algorithms, allows performing accurate and rapid analysis on multiple spike trains from thousands of electrodes.

Processing of Antenna-Array Signals on the Basis of the Interference Model Including a Rank-Deficient Correlation Matrix

NASA Astrophysics Data System (ADS)

Rodionov, A. A.; Turchin, V. I.

2017-06-01

We propose a new method of signal processing in antenna arrays, which is called the Maximum-Likelihood Signal Classification. The proposed method is based on the model in which interference includes a component with a rank-deficient correlation matrix. Using numerical simulation, we show that the proposed method allows one to ensure variance of the estimated arrival angle of the plane wave, which is close to the Cramer-Rao lower boundary and more efficient than the best-known MUSIC method. It is also shown that the proposed technique can be efficiently used for estimating the time dependence of the useful signal.

Combined analysis of cortical (EEG) and nerve stump signals improves robotic hand control.

PubMed

Tombini, Mario; Rigosa, Jacopo; Zappasodi, Filippo; Porcaro, Camillo; Citi, Luca; Carpaneto, Jacopo; Rossini, Paolo Maria; Micera, Silvestro

2012-01-01

Interfacing an amputee's upper-extremity stump nerves to control a robotic hand requires training of the individual and algorithms to process interactions between cortical and peripheral signals. To evaluate for the first time whether EEG-driven analysis of peripheral neural signals as an amputee practices could improve the classification of motor commands. Four thin-film longitudinal intrafascicular electrodes (tf-LIFEs-4) were implanted in the median and ulnar nerves of the stump in the distal upper arm for 4 weeks. Artificial intelligence classifiers were implemented to analyze LIFE signals recorded while the participant tried to perform 3 different hand and finger movements as pictures representing these tasks were randomly presented on a screen. In the final week, the participant was trained to perform the same movements with a robotic hand prosthesis through modulation of tf-LIFE-4 signals. To improve the classification performance, an event-related desynchronization/synchronization (ERD/ERS) procedure was applied to EEG data to identify the exact timing of each motor command. Real-time control of neural (motor) output was achieved by the participant. By focusing electroneurographic (ENG) signal analysis in an EEG-driven time window, movement classification performance improved. After training, the participant regained normal modulation of background rhythms for movement preparation (α/β band desynchronization) in the sensorimotor area contralateral to the missing limb. Moreover, coherence analysis found a restored α band synchronization of Rolandic area with frontal and parietal ipsilateral regions, similar to that observed in the opposite hemisphere for movement of the intact hand. Of note, phantom limb pain (PLP) resolved for several months. Combining information from both cortical (EEG) and stump nerve (ENG) signals improved the classification performance compared with tf-LIFE signals processing alone; training led to cortical reorganization and mitigation of PLP.

Real-time implementations of acoustic signal enhancement techniques for aerial based surveillance and rescue applications

NASA Astrophysics Data System (ADS)

Ramos, Antonio L. L.; Shao, Zhili; Holthe, Aleksander; Sandli, Mathias F.

2017-05-01

The introduction of the System-on-Chip (SoC) technology has brought exciting new opportunities for the development of smart low cost embedded systems spanning a wide range of applications. Currently available SoC devices are capable of performing high speed digital signal processing tasks in software while featuring relatively low development costs and reduced time-to-market. Unmanned aerial vehicles (UAV) are an application example that has shown tremendous potential in an increasing number of scenarios, ranging from leisure to surveillance as well as in search and rescue missions. Video capturing from UAV platforms is a relatively straightforward task that requires almost no preprocessing. However, that does not apply to audio signals, especially in cases where the data is to be used to support real-time decision making. In fact, the enormous amount of acoustic interference from the surroundings, including the noise from the UAVs propellers, becomes a huge problem. This paper discusses a real-time implementation of the NLMS adaptive filtering algorithm applied to enhancing acoustic signals captured from UAV platforms. The model relies on a combination of acoustic sensors and a computational inexpensive algorithm running on a digital signal processor. Given its simplicity, this solution can be incorporated into the main processing system of an UAV using the SoC technology, and run concurrently with other required tasks, such as flight control and communications. Simulations and real-time DSP-based implementations have shown significant signal enhancement results by efficiently mitigating the interference from the noise generated by the UAVs propellers as well as from other external noise sources.

Picosecond time-resolved photoluminescence using picosecond excitation correlation spectroscopy

NASA Astrophysics Data System (ADS)

Johnson, M. B.; McGill, T. C.; Hunter, A. T.

1988-03-01

We present a study of the temporal decay of photoluminescence (PL) as detected by picosecond excitation correlation spectroscopy (PECS). We analyze the correlation signal that is obtained from two simple models; one where radiative recombination dominates, the other where trapping processes dominate. It is found that radiative recombination alone does not lead to a correlation signal. Parallel trapping type processes are found to be required to see a signal. To illustrate this technique, we examine the temporal decay of the PL signal for In-alloyed, semi-insulating GaAs substrates. We find that the PL signal indicates a carrier lifetime of roughly 100 ps, for excitation densities of 1×1016-5×1017 cm-3. PECS is shown to be an easy technique to measure the ultrafast temporal behavior of PL processes because it requires no ultrafast photon detection. It is particularly well suited to measuring carrier lifetimes.

Research on motor rotational speed measurement in regenerative braking system of electric vehicle

NASA Astrophysics Data System (ADS)

Pan, Chaofeng; Chen, Liao; Chen, Long; Jiang, Haobin; Li, Zhongxing; Wang, Shaohua

2016-01-01

Rotational speed signals acquisition and processing techniques are widely used in rotational machinery. In order to realized precise and real-time control of motor drive and regenerative braking process, rotational speed measurement techniques are needed in electric vehicles. Obtaining accurate motor rotational speed signal will contribute to the regenerative braking force control steadily and realized higher energy recovery rate. This paper aims to develop a method that provides instantaneous speed information in the form of motor rotation. It addresses principles of motor rotational speed measurement in the regenerative braking systems of electric vehicle firstly. The paper then presents ideal and actual Hall position sensor signals characteristics, the relation between the motor rotational speed and the Hall position sensor signals is revealed. Finally, Hall position sensor signals conditioning and processing circuit and program for motor rotational speed measurement have been carried out based on measurement error analysis.

SIG: a general-purpose signal processing program

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

Lager, D.; Azevedo, S.

1986-02-01

SIG is a general-purpose signal processing, analysis, and display program. Its main purpose is to perform manipulations on time- and frequency-domain signals. It also accommodates other representations for data such as transfer function polynomials. Signal processing operations include digital filtering, auto/cross spectral density, transfer function/impulse response, convolution, Fourier transform, and inverse Fourier transform. Graphical operations provide display of signals and spectra, including plotting, cursor zoom, families of curves, and multiple viewport plots. SIG provides two user interfaces with a menu mode for occasional users and a command mode for more experienced users. Capability exits for multiple commands per line, commandmore » files with arguments, commenting lines, defining commands, automatic execution for each item in a repeat sequence, etc. SIG is presently available for VAX(VMS), VAX (BERKELEY 4.2 UNIX), SUN (BERKELEY 4.2 UNIX), DEC-20 (TOPS-20), LSI-11/23 (TSX), and DEC PRO 350 (TSX). 4 refs., 2 figs.« less

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

PubMed

Lehle, B; Peinke, J

2015-06-01

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

Sequencing batch-reactor control using Gaussian-process models.

PubMed

Kocijan, Juš; Hvala, Nadja

2013-06-01

This paper presents a Gaussian-process (GP) model for the design of sequencing batch-reactor (SBR) control for wastewater treatment. The GP model is a probabilistic, nonparametric model with uncertainty predictions. In the case of SBR control, it is used for the on-line optimisation of the batch-phases duration. The control algorithm follows the course of the indirect process variables (pH, redox potential and dissolved oxygen concentration) and recognises the characteristic patterns in their time profile. The control algorithm uses GP-based regression to smooth the signals and GP-based classification for the pattern recognition. When tested on the signals from an SBR laboratory pilot plant, the control algorithm provided a satisfactory agreement between the proposed completion times and the actual termination times of the biodegradation processes. In a set of tested batches the final ammonia and nitrate concentrations were below 1 and 0.5 mg L(-1), respectively, while the aeration time was shortened considerably. Copyright © 2013 Elsevier Ltd. All rights reserved.

On the Relationship between the Redundant Signals Effect and Temporal Order Judgments: Parametric Data and a New Model

ERIC Educational Resources Information Center

Schwarz, Wolf

2006-01-01

Paradigms used to study the time course of the redundant signals effect (RSE; J. O. Miller, 1986) and temporal order judgments (TOJs) share many important similarities and address related questions concerning the time course of sensory processing. The author of this article proposes and tests a new aggregate diffusion-based model to quantitatively…

Window and Overlap Processing Effects on Power Estimates from Spectra

NASA Astrophysics Data System (ADS)

Trethewey, M. W.

2000-03-01

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

Real time pressure signal system for a rotary engine

NASA Technical Reports Server (NTRS)

Rice, W. J. (Inventor)

1984-01-01

A real-time IMEP signal which is a composite of those produced in any one chamber of a three-lobed rotary engine is developed by processing the signals of four transducers positioned in a Wankel engine housing such that the rotor overlaps two of the transducers for a brief period during each cycle. During the overlap period of any two transducers, their output is compared and sampled for 10 microseconds per 0.18 degree of rotation by a sampling switch and capacitive circuit. When the switch is closed, the instantaneous difference between the value of the transducer signals is provided while with the switch open the average difference is produced. This combined signal, along with the original signal of the second transducer, is fed through a multiplexer to a pressure output terminal. Timing circuits, controlled by a crank angle encoder on the engine, determine which compared transducer signals are applied to the output terminal and when, as well as the open and closed periods of the switches.

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.

Enhancing Soundtracks From Old Movies

NASA Technical Reports Server (NTRS)

Frazer, Robert E.

1992-01-01

Proposed system enhances soundtracks of old movies. Signal on optical soundtrack of film digitized and processed to reduce noise and improve quality; timing signals added, and signal recorded on compact disk. Digital comparator and voltage-controlled oscillator synchronizes speed of film-drive motor and compact disk motor. Frame-coded detector reads binary frame-identifying marks on film. Digital comparator generates error signal if marks on film do not match those on compact disk.

The high accuracy data processing system of laser interferometry signals based on MSP430

NASA Astrophysics Data System (ADS)

Qi, Yong-yue; Lin, Yu-chi; Zhao, Mei-rong

2009-07-01

Generally speaking there are two orthogonal signals used in single-frequency laser interferometer for differentiating direction and electronic subdivision. However there usually exist three errors with the interferential signals: zero offsets error, unequal amplitude error and quadrature phase shift error. These three errors have a serious impact on subdivision precision. Based on Heydemann error compensation algorithm, it is proposed to achieve compensation of the three errors. Due to complicated operation of the Heydemann mode, a improved arithmetic is advanced to decrease the calculating time effectively in accordance with the special characteristic that only one item of data will be changed in each fitting algorithm operation. Then a real-time and dynamic compensatory circuit is designed. Taking microchip MSP430 as the core of hardware system, two input signals with the three errors are turned into digital quantity by the AD7862. After data processing in line with improved arithmetic, two ideal signals without errors are output by the AD7225. At the same time two original signals are turned into relevant square wave and imported to the differentiating direction circuit. The impulse exported from the distinguishing direction circuit is counted by the timer of the microchip. According to the number of the pulse and the soft subdivision the final result is showed by LED. The arithmetic and the circuit are adopted to test the capability of a laser interferometer with 8 times optical path difference and the measuring accuracy of 12-14nm is achieved.

Error reduction study employing a pseudo-random binary sequence for use in acoustic pyrometry of gases

NASA Astrophysics Data System (ADS)

Ewan, B. C. R.; Ireland, S. N.

2000-12-01

Acoustic pyrometry uses the temperature dependence of sound speed in materials to measure temperature. This is normally achieved by measuring the transit time for a sound signal over a known path length and applying the material relation between temperature and velocity to extract an "average" temperature. Sources of error associated with the measurement of mean transit time are discussed in implementing the technique in gases, one of the principal causes being background noise in typical industrial environments. A number of transmitted signal and processing strategies which can be used in the area are examined and the expected error in mean transit time associated with each technique is quantified. Transmitted signals included pulses, pure frequencies, chirps, and pseudorandom binary sequences (prbs), while processing involves edge detection and correlation. Errors arise through the misinterpretation of the positions of edge arrival or correlation peaks due to instantaneous deviations associated with background noise and these become more severe as signal to noise amplitude ratios decrease. Population errors in the mean transit time are estimated for the different measurement strategies and it is concluded that PRBS combined with correlation can provide the lowest errors when operating in high noise environments. The operation of an instrument based on PRBS transmitted signals is described and test results under controlled noise conditions are presented. These confirm the value of the strategy and demonstrate that measurements can be made with signal to noise amplitude ratios down to 0.5.

Method and apparatus for measuring flow velocity using matched filters

DOEpatents

Raptis, A.C.

1983-09-06

An apparatus and method for measuring the flow velocities of individual phase flow components of a multiphase flow utilizes matched filters. Signals arising from flow noise disturbance are extracted from the flow, at upstream and downstream locations. The signals are processed through pairs of matched filters which are matched to the flow disturbance frequency characteristics of the phase flow component to be measured. The processed signals are then cross-correlated to determine the transit delay time of the phase flow component between sensing positions. 8 figs.

SIG: a general-purpose signal processing program. User's manual. Revision 1

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

Lager, D.; Azevedo, S.

1985-05-09

SIG is a general-purpose signal processing, analysis, and display program. Its main purpose is to perform manipulations on time-domain and frequenccy-domain signals. The manual contains a complete description of the SIG program from the user's stand-point. A brief exercise in using SIG is shown. Complete descriptions are given of each command in the SIG core. General information about the SIG structure, command processor, and graphics options are provided. An example usage of SIG for solving a problem is developed, and error message formats are briefly discussed. (LEW)

Characterization of time dynamical evolution of electroencephalographic epileptic records

NASA Astrophysics Data System (ADS)

Rosso, Osvaldo A.; Mairal, María. Liliana

2002-09-01

Since traditional electrical brain signal analysis is mostly qualitative, the development of new quantitative methods is crucial for restricting the subjectivity in the study of brain signals. These methods are particularly fruitful when they are strongly correlated with intuitive physical concepts that allow a better understanding of the brain dynamics. The processing of information by the brain is reflected in dynamical changes of the electrical activity in time, frequency, and space. Therefore, the concomitant studies require methods capable of describing the qualitative variation of the signal in both time and frequency. The entropy defined from the wavelet functions is a measure of the order/disorder degree present in a time series. In consequence, this entropy evaluates over EEG time series gives information about the underlying dynamical process in the brain, more specifically of the synchrony of the group cells involved in the different neural responses. The total wavelet entropy results independent of the signal energy and becomes a good tool for detecting dynamical changes in the system behavior. In addition the total wavelet entropy has advantages over the Lyapunov exponents, because it is parameter free and independent of the stationarity of the time series. In this work we compared the results of the time evolution of the chaoticity (Lyapunov exponent as a function of time) with the corresponding time evolution of the total wavelet entropy in two different EEG records, one provide by depth electrodes and other by scalp ones.

Multi-Dimensional Signal Processing Research Program

DTIC Science & Technology

1981-09-30

applications to real-time image processing and analysis. A specific long-range application is the automated processing of aerial reconnaissance imagery...Non-supervised image segmentation is a potentially im- portant operation in the automated processing of aerial reconnaissance pho- tographs since it

A self-regulating biomolecular comparator for processing oscillatory signals

PubMed Central

Agrawal, Deepak K.; Franco, Elisa; Schulman, Rebecca

2015-01-01

While many cellular processes are driven by biomolecular oscillators, precise control of a downstream on/off process by a biochemical oscillator signal can be difficult: over an oscillator's period, its output signal varies continuously between its amplitude limits and spends a significant fraction of the time at intermediate values between these limits. Further, the oscillator's output is often noisy, with particularly large variations in the amplitude. In electronic systems, an oscillating signal is generally processed by a downstream device such as a comparator that converts a potentially noisy oscillatory input into a square wave output that is predominantly in one of two well-defined on and off states. The comparator's output then controls downstream processes. We describe a method for constructing a synthetic biochemical device that likewise produces a square-wave-type biomolecular output for a variety of oscillatory inputs. The method relies on a separation of time scales between the slow rate of production of an oscillatory signal molecule and the fast rates of intermolecular binding and conformational changes. We show how to control the characteristics of the output by varying the concentrations of the species and the reaction rates. We then use this control to show how our approach could be applied to process different in vitro and in vivo biomolecular oscillators, including the p53-Mdm2 transcriptional oscillator and two types of in vitro transcriptional oscillators. These results demonstrate how modular biomolecular circuits could, in principle, be combined to build complex dynamical systems. The simplicity of our approach also suggests that natural molecular circuits may process some biomolecular oscillator outputs before they are applied downstream. PMID:26378119

Digital phased array beamforming using single-bit delta-sigma conversion with non-uniform oversampling.

PubMed

Kozak, M; Karaman, M

2001-07-01

Digital beamforming based on oversampled delta-sigma (delta sigma) analog-to-digital (A/D) conversion can reduce the overall cost, size, and power consumption of phased array front-end processing. The signal resampling involved in dynamic delta sigma beamforming, however, disrupts synchronization between the modulators and demodulator, causing significant degradation in the signal-to-noise ratio. As a solution to this, we have explored a new digital beamforming approach based on non-uniform oversampling delta sigma A/D conversion. Using this approach, the echo signals received by the transducer array are sampled at time instants determined by the beamforming timing and then digitized by single-bit delta sigma A/D conversion prior to the coherent beam summation. The timing information involves a non-uniform sampling scheme employing different clocks at each array channel. The delta sigma coded beamsums obtained by adding the delayed 1-bit coded RF echo signals are then processed through a decimation filter to produce final beamforming outputs. The performance and validity of the proposed beamforming approach are assessed by means of emulations using experimental raw RF data.

Autocorrelation-based time synchronous averaging for condition monitoring of planetary gearboxes in wind turbines

NASA Astrophysics Data System (ADS)

Ha, Jong M.; Youn, Byeng D.; Oh, Hyunseok; Han, Bongtae; Jung, Yoongho; Park, Jungho

2016-03-01

We propose autocorrelation-based time synchronous averaging (ATSA) to cope with the challenges associated with the current practice of time synchronous averaging (TSA) for planet gears in planetary gearboxes of wind turbine (WT). An autocorrelation function that represents physical interactions between the ring, sun, and planet gears in the gearbox is utilized to define the optimal shape and range of the window function for TSA using actual kinetic responses. The proposed ATSA offers two distinctive features: (1) data-efficient TSA processing and (2) prevention of signal distortion during the TSA process. It is thus expected that an order analysis with the ATSA signals significantly improves the efficiency and accuracy in fault diagnostics of planet gears in planetary gearboxes. Two case studies are presented to demonstrate the effectiveness of the proposed method: an analytical signal from a simulation and a signal measured from a 2 kW WT testbed. It can be concluded from the results that the proposed method outperforms conventional TSA methods in condition monitoring of the planetary gearbox when the amount of available stationary data is limited.

SIG-VISA: Signal-based Vertically Integrated Seismic Monitoring

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

Receiver psychology turns 20: is it time for a broader approach?

PubMed Central

Miller, Cory T.; Bee, Mark A.

2013-01-01

Twenty years ago, a new conceptual paradigm known as ‘receiver psychology’ was introduced to explain the evolution of animal communication systems. This paradigm advanced the idea that psychological processes in the receiver's nervous system influence a signal's detectability, discriminability and memorability, and thereby serve as powerful sources of selection shaping signal design. While advancing our understanding of signal diversity, more recent studies make clear that receiver psychology, as a paradigm, has been structured too narrowly and does not incorporate many of the perceptual and cognitive processes of signal reception that operate between sensory transduction and a receiver's response. Consequently, the past two decades of research on receiver psychology have emphasized considerations of signal evolution but failed to ask key questions about the mechanisms of signal reception and their evolution. The primary aim of this essay is to advocate for a broader receiver psychology paradigm that more explicitly includes a research focus on receivers' psychological landscapes. We review recent experimental studies of hearing and sound communication to illustrate how considerations of several general perceptual and cognitive processes will facilitate future research on animal signalling systems. We also emphasize how a rigorous comparative approach to receiver psychology is critical to explicating the full range of perceptual and cognitive processes involved in receiving and responding to signals. PMID:24013277

Dual Key Speech Encryption Algorithm Based Underdetermined BSS

PubMed Central

Zhao, Huan; Chen, Zuo; Zhang, Xixiang

2014-01-01

When the number of the mixed signals is less than that of the source signals, the underdetermined blind source separation (BSS) is a significant difficult problem. Due to the fact that the great amount data of speech communications and real-time communication has been required, we utilize the intractability of the underdetermined BSS problem to present a dual key speech encryption method. The original speech is mixed with dual key signals which consist of random key signals (one-time pad) generated by secret seed and chaotic signals generated from chaotic system. In the decryption process, approximate calculation is used to recover the original speech signals. The proposed algorithm for speech signals encryption can resist traditional attacks against the encryption system, and owing to approximate calculation, decryption becomes faster and more accurate. It is demonstrated that the proposed method has high level of security and can recover the original signals quickly and efficiently yet maintaining excellent audio quality. PMID:24955430

Digital Audio Signal Processing and Nde: AN Unlikely but Valuable Partnership

NASA Astrophysics Data System (ADS)

Gaydecki, Patrick

2008-02-01

In the Digital Signal Processing (DSP) group, within the School of Electrical and Electronic Engineering at The University of Manchester, research is conducted into two seemingly distinct and disparate subjects: instrumentation for nondestructive evaluation, and DSP systems & algorithms for digital audio. We have often found that many of the hardware systems and algorithms employed to recover, extract or enhance audio signals may also be applied to signals provided by ultrasonic or magnetic NDE instruments. Furthermore, modern DSP hardware is so fast (typically performing hundreds of millions of operations per second), that much of the processing and signal reconstruction may be performed in real time. Here, we describe some of the hardware systems we have developed, together with algorithms that can be implemented both in real time and offline. A next generation system has now been designed, which incorporates a processor operating at 0.55 Giga MMACS, six input and eight output analogue channels, digital input/output in the form of S/PDIF, a JTAG and a USB interface. The software allows the user, with no knowledge of filter theory or programming, to design and run standard or arbitrary FIR, IIR and adaptive filters. Using audio as a vehicle, we can demonstrate the remarkable properties of modern reconstruction algorithms when used in conjunction with such hardware; applications in NDE include signal enhancement and recovery in acoustic, ultrasonic, magnetic and eddy current modalities.

Gravitational wave searches with pulsar timing arrays: Cancellation of clock and ephemeris noises

NASA Astrophysics Data System (ADS)

Tinto, Massimo

2018-04-01

We propose a data processing technique to cancel monopole and dipole noise sources (such as clock and ephemeris noises, respectively) in pulsar timing array searches for gravitational radiation. These noises are the dominant sources of correlated timing fluctuations in the lower-part (≈10-9-10-8 Hz ) of the gravitational wave band accessible by pulsar timing experiments. After deriving the expressions that reconstruct these noises from the timing data, we estimate the gravitational wave sensitivity of our proposed processing technique to single-source signals to be at least one order of magnitude higher than that achievable by directly processing the timing data from an equal-size array. Since arrays can generate pairs of clock and ephemeris-free timing combinations that are no longer affected by correlated noises, we implement with them the cross-correlation statistic to search for an isotropic stochastic gravitational wave background. We find the resulting optimal signal-to-noise ratio to be more than one order of magnitude larger than that obtainable by correlating pairs of timing data from arrays of equal size.

Attentional bias between modalities: effect on the internal clock, memory, and decision stages used in animal time discrimination.

PubMed

Meck, W H

1984-01-01

Both the presentation of unbalanced stimulus probabilities and the insertion of a predictive cue prior to the signal on each trial apparently induces a strong bias to use a particular stimulus modality in order to select a temporal criterion and response rule. This attentional bias toward one modality is apparently independent of the modality of the stimulus being timed and is strongly influenced by stimulus probabilities or prior warning cues. These techniques may be useful to control trial-by-trial sequential effects that influence a subject's perceptual and response biases when signals from more than one modality are used in duration discrimination tasks. Cross-procedural generality of the effects of attentional bias was observed. An asymmetrical modality effect on the latency to begin timing was observed with both the temporal bisection and the peak procedure. The latency to begin timing light signals, but not the latency to begin timing sound signals, was increased when the signal modality was unexpected. This asymmetrical effect was explained with the assumption that sound signals close the mode switch automatically, but that light signals close the mode switch only if attention is directed to the light. The time required to switch attention is reflected in a reduction of the number of pulses from the pacemaker that enter the accumulator. One positive aspect of this work is the demonstration that procedures similar to those used to study human cognition can be used with animal subjects with similar results. Perhaps these similarities will stimulate animal research on the physiological basis of various cognitive capacities. Animal subjects would be preferred for such physiological experimentation if it were established that they possessed some of the cognitive processes described by investigators of human information processing. One of the negative aspects of this work is that only one combination of modalities was used and variables such as stimulus intensity, stimulus probability, and range of signal durations have not been adequately investigated at present. Future work might test additional combinations of modalities and vary stimulus intensity and stimulus probability within a signal detection theory (SDT) framework to determine the effects of these variables on attentional bias.

Wake acoustic analysis and image decomposition via beamforming of microphone signal projections on wavelet subspaces

DOT National Transportation Integrated Search

2006-05-08

This paper describes the integration of wavelet analysis and time-domain beamforming : of microphone array output signals for analyzing the acoustic emissions from airplane : generated wake vortices. This integrated process provides visual and quanti...

The Timing and Effort of Lexical Access in Natural and Degraded Speech

PubMed Central

Wagner, Anita E.; Toffanin, Paolo; Başkent, Deniz

2016-01-01

Understanding speech is effortless in ideal situations, and although adverse conditions, such as caused by hearing impairment, often render it an effortful task, they do not necessarily suspend speech comprehension. A prime example of this is speech perception by cochlear implant users, whose hearing prostheses transmit speech as a significantly degraded signal. It is yet unknown how mechanisms of speech processing deal with such degraded signals, and whether they are affected by effortful processing of speech. This paper compares the automatic process of lexical competition between natural and degraded speech, and combines gaze fixations, which capture the course of lexical disambiguation, with pupillometry, which quantifies the mental effort involved in processing speech. Listeners’ ocular responses were recorded during disambiguation of lexical embeddings with matching and mismatching durational cues. Durational cues were selected due to their substantial role in listeners’ quick limitation of the number of lexical candidates for lexical access in natural speech. Results showed that lexical competition increased mental effort in processing natural stimuli in particular in presence of mismatching cues. Signal degradation reduced listeners’ ability to quickly integrate durational cues in lexical selection, and delayed and prolonged lexical competition. The effort of processing degraded speech was increased overall, and because it had its sources at the pre-lexical level this effect can be attributed to listening to degraded speech rather than to lexical disambiguation. In sum, the course of lexical competition was largely comparable for natural and degraded speech, but showed crucial shifts in timing, and different sources of increased mental effort. We argue that well-timed progress of information from sensory to pre-lexical and lexical stages of processing, which is the result of perceptual adaptation during speech development, is the reason why in ideal situations speech is perceived as an undemanding task. Degradation of the signal or the receiver channel can quickly bring this well-adjusted timing out of balance and lead to increase in mental effort. Incomplete and effortful processing at the early pre-lexical stages has its consequences on lexical processing as it adds uncertainty to the forming and revising of lexical hypotheses. PMID:27065901

Emotion regulation during threat: Parsing the time course and consequences of safety signal processing

PubMed Central

HEFNER, KATHRYN R.; VERONA, EDELYN; CURTIN, JOHN. J.

2017-01-01

Improved understanding of fear inhibition processes can inform the etiology and treatment of anxiety disorders. Safety signals can reduce fear to threat, but precise mechanisms remain unclear. Safety signals may acquire attentional salience and affective properties (e.g., relief) independent of the threat; alternatively, safety signals may only hold affective value in the presence of simultaneous threat. To clarify such mechanisms, an experimental paradigm assessed independent processing of threat and safety cues. Participants viewed a series of red and green words from two semantic categories. Shocks were administered following red words (cue+). No shocks followed green words (cue−). Words from one category were defined as safety signals (SS); no shocks were administered on cue+ trials. Words from the other (control) category did not provide information regarding shock administration. Threat (cue+ vs. cue−) and safety (SS+ vs. SS−) were fully crossed. Startle response and ERPs were recorded. Startle response was increased during cue+ versus cue−. Safety signals reduced startle response during cue+, but had no effect on startle response during cue−. ERP analyses (PD130 and P3) suggested that participants parsed threat and safety signal information in parallel. Motivated attention was not associated with safety signals in the absence of threat. Overall, these results confirm that fear can be reduced by safety signals. Furthermore, safety signals do not appear to hold inherent hedonic salience independent of their effect during threat. Instead, safety signals appear to enable participants to engage in effective top-down emotion regulatory processes. PMID:27088643

Digitally Enhanced Heterodyne Interferometry

NASA Technical Reports Server (NTRS)

Shaddock, Daniel; Ware, Brent; Lay, Oliver; Dubovitsky, Serge

2010-01-01

Spurious interference limits the performance of many interferometric measurements. Digitally enhanced interferometry (DEI) improves measurement sensitivity by augmenting conventional heterodyne interferometry with pseudo-random noise (PRN) code phase modulation. DEI effectively changes the measurement problem from one of hardware (optics, electronics), which may deteriorate over time, to one of software (modulation, digital signal processing), which does not. DEI isolates interferometric signals based on their delay. Interferometric signals are effectively time-tagged by phase-modulating the laser source with a PRN code. DEI improves measurement sensitivity by exploiting the autocorrelation properties of the PRN to isolate only the signal of interest and reject spurious interference. The properties of the PRN code determine the degree of isolation.

Evaluation of cardiac signals using discrete wavelet transform with MATLAB graphical user interface.

PubMed

John, Agnes Aruna; Subramanian, Aruna Priyadharshni; Jaganathan, Saravana Kumar; Sethuraman, Balasubramanian

2015-01-01

To process the electrocardiogram (ECG) signals using MATLAB-based graphical user interface (GUI) and to classify the signals based on heart rate. The subject condition was identified using R-peak detection based on discrete wavelet transform followed by a Bayes classifier that classifies the ECG signals. The GUI was designed to display the ECG signal plot. Obtained from MIT database 18 patients had normal heart rate and 9 patients had abnormal heart rate; 14.81% of the patients suffered from tachycardia and 18.52% of the patients have bradycardia. The proposed GUI display was found useful to analyze the digitized ECG signal by a non-technical user and may help in diagnostics. Further improvement can be done by employing field programmable gate array for the real time processing of cardiac signals. Copyright © 2015 Cardiological Society of India. Published by Elsevier B.V. All rights reserved.

Noise reduction methods for nucleic acid and macromolecule sequencing

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

Schuller, Ivan K.; Di Ventra, Massimiliano; Balatsky, Alexander

Methods, systems, and devices are disclosed for processing macromolecule sequencing data with substantial noise reduction. In one aspect, a method for reducing noise in a sequential measurement of a macromolecule comprising serial subunits includes cross-correlating multiple measured signals of a physical property of subunits of interest of the macromolecule, the multiple measured signals including the time data associated with the measurement of the signal, to remove or at least reduce signal noise that is not in the same frequency and in phase with the systematic signal contribution of the measured signals.

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.

Ultra-high throughput real-time instruments for capturing fast signals and rare events

NASA Astrophysics Data System (ADS)

Buckley, Brandon Walter

Wide-band signals play important roles in the most exciting areas of science, engineering, and medicine. To keep up with the demands of exploding internet traffic, modern data centers and communication networks are employing increasingly faster data rates. Wide-band techniques such as pulsed radar jamming and spread spectrum frequency hopping are used on the battlefield to wrestle control of the electromagnetic spectrum. Neurons communicate with each other using transient action potentials that last for only milliseconds at a time. And in the search for rare cells, biologists flow large populations of cells single file down microfluidic channels, interrogating them one-by-one, tens of thousands of times per second. Studying and enabling such high-speed phenomena pose enormous technical challenges. For one, parasitic capacitance inherent in analog electrical components limits their response time. Additionally, converting these fast analog signals to the digital domain requires enormous sampling speeds, which can lead to significant jitter and distortion. State-of-the-art imaging technologies, essential for studying biological dynamics and cells in flow, are limited in speed and sensitivity by finite charge transfer and read rates, and by the small numbers of photo-electrons accumulated in short integration times. And finally, ultra-high throughput real-time digital processing is required at the backend to analyze the streaming data. In this thesis, I discuss my work in developing real-time instruments, employing ultrafast optical techniques, which overcome some of these obstacles. In particular, I use broadband dispersive optics to slow down fast signals to speeds accessible to high-bit depth digitizers and signal processors. I also apply telecommunication multiplexing techniques to boost the speeds of confocal fluorescence microscopy. The photonic time stretcher (TiSER) uses dispersive Fourier transformation to slow down analog signals before digitization and processing. The act of time-stretching effectively boosts the performance of the back-end electronics and digital signal processors. The slowed down signals reach the back-end electronics with reduced bandwidth, and are therefore less affected by high-frequency roll-off and distortion. Time-stretching also increases the effective sampling rate of analog-to-digital converters and reduces aperture jitter, thereby improving resolution. Finally, the instantaneous throughputs of digital signal processors are enhanced by the stretch factor to otherwise unattainable speeds. Leveraging these unique capabilities, TiSER becomes the ideal tool for capturing high-speed signals and characterizing rare phenomena. For this thesis, I have developed techniques to improve the spectral efficiency, bandwidth, and resolution of TiSER using polarization multiplexing, all-optical modulation, and coherent dispersive Fourier transformation. To reduce the latency and improve the data handling capacity, I have also designed and implemented a real-time digital signal processing electronic backend, achieving 1.5 tera-bit per second instantaneous processing throughput. Finally, I will present results from experiments highlighting TiSER's impact in real-world applications. Confocal fluorescence microscopy is the most widely used method for unveiling the molecular composition of biological specimens. However, the weak optical emission of fluorescent probes and the tradeoff between imaging speed and sensitivity is problematic for acquiring blur-free images of fast phenomena and cells flowing at high speed. Here I introduce a new fluorescence imaging modality, which leverages techniques from wireless communication to reach record pixel and frame rates. Termed Fluorescence Imaging using Radio-frequency tagged Emission (FIRE), this new imaging modality is capable of resolving never before seen dynamics in living cells - such as action potentials in neurons and metabolic waves in astrocytes - as well as performing high-content image assays of cells and particles in high-speed flow.

Development of a real time bistatic radar receiver using signals of opportunity

NASA Astrophysics Data System (ADS)

Rainville, Nicholas

Passive bistatic radar remote sensing offers a novel method of monitoring the Earth's surface by observing reflected signals of opportunity. The Global Positioning System (GPS) has been used as a source of signals for these observations and the scattering properties of GPS signals from rough surfaces are well understood. Recent work has extended GPS signal reflection observations and scattering models to include communications signals such as XM radio signals. However the communication signal reflectometry experiments to date have relied on collecting raw, high data-rate signals which are then post-processed after the end of the experiment. This thesis describes the development of a communication signal bistatic radar receiver which computes a real time correlation waveform, which can be used to retrieve measurements of the Earth's surface. The real time bistatic receiver greatly reduces the quantity of data that must be stored to perform the remote sensing measurements, as well as offering immediate feedback. This expands the applications for the receiver to include space and bandwidth limited platforms such as aircraft and satellites. It also makes possible the adjustment of flight plans to the observed conditions. This real time receiver required the development of an FGPA based signal processor, along with the integration of commercial Satellite Digital Audio Radio System (SDARS) components. The resulting device was tested both in a lab environment as well on NOAA WP-3D and NASA WB-57 aircraft.

High-resolution (>5 800 time-bandwidth product) shear mode TeO2 deflector

NASA Astrophysics Data System (ADS)

Soos, Jolanta I.; Caviris, Nicholas P.; Phuvan, Sonlinh

1992-12-01

Acousto-optic deflectors play an important role in optical signal processing systems due to their real time processing capabilities, as well as their conversion capabilities of a function of time to a function of space and time. In this work Brimrose investigated the design and fabrication of state-of-the-art, very large time-bandwidth acousto-optic devices from TeO2 single crystals.

The time course of corticospinal excitability during a simple reaction time task.

PubMed

Kennefick, Michael; Maslovat, Dana; Carlsen, Anthony N

2014-01-01

The production of movement in a simple reaction time task can be separated into two time periods: the foreperiod, which is thought to include preparatory processes, and the reaction time interval, which includes initiation processes. To better understand these processes, transcranial magnetic stimulation has been used to probe corticospinal excitability at various time points during response preparation and initiation. Previous research has shown that excitability decreases prior to the "go" stimulus and increases following the "go"; however these two time frames have been examined independently. The purpose of this study was to measure changes in CE during both the foreperiod and reaction time interval in a single experiment, relative to a resting baseline level. Participants performed a button press movement in a simple reaction time task and excitability was measured during rest, the foreperiod, and the reaction time interval. Results indicated that during the foreperiod, excitability levels quickly increased from baseline with the presentation of the warning signal, followed by a period of stable excitability leading up to the "go" signal, and finally a rapid increase in excitability during the reaction time interval. This excitability time course is consistent with neural activation models that describe movement preparation and response initiation.

Selection signature in domesticated animals.

PubMed

Pan, Zhang-yuan; He, Xiao-yun; Wang, Xiang-yu; Guo, Xiao-fei; Cao, Xiao-han; Hu, Wen-ping; Di, Ran; Liu, Qiu-yue; Chu, Ming-xing

2016-12-20

Domesticated animals play an important role in the life of humanity. All these domesticated animals undergo same process, first domesticated from wild animals, then after long time natural and artificial selection, formed various breeds that adapted to the local environment and human needs. In this process, domestication, natural and artificial selection will leave the selection signal in the genome. The research on these selection signals can find functional genes directly, is one of the most important strategies in screening functional genes. The current studies of selection signal have been performed in pigs, chickens, cattle, sheep, goats, dogs and other domestic animals, and found a great deal of functional genes. This paper provided an overview of the types and the detected methods of selection signal, and outlined researches of selection signal in domestic animals, and discussed the key issues in selection signal analysis and its prospects.

Artifact Noise Removal Techniques on Seismocardiogram Using Two Tri-Axial Accelerometers

PubMed Central

Luu, Loc; Dinh, Anh

2018-01-01

The aim of this study is on the investigation of motion noise removal techniques using two-accelerometer sensor system and various placements of the sensors on gentle movement and walking of the patients. A Wi-Fi based data acquisition system and a framework on Matlab are developed to collect and process data while the subjects are in motion. The tests include eight volunteers who have no record of heart disease. The walking and running data on the subjects are analyzed to find the minimal-noise bandwidth of the SCG signal. This bandwidth is used to design filters in the motion noise removal techniques and peak signal detection. There are two main techniques of combining signals from the two sensors to mitigate the motion artifact: analog processing and digital processing. The analog processing comprises analog circuits performing adding or subtracting functions and bandpass filter to remove artifact noises before entering the data acquisition system. The digital processing processes all the data using combinations of total acceleration and z-axis only acceleration. The two techniques are tested on three placements of accelerometer sensors including horizontal, vertical, and diagonal on gentle motion and walking. In general, the total acceleration and z-axis acceleration are the best techniques to deal with gentle motion on all sensor placements which improve average systolic signal-noise-ratio (SNR) around 2 times and average diastolic SNR around 3 times comparing to traditional methods using only one accelerometer. With walking motion, ADDER and z-axis acceleration are the best techniques on all placements of the sensors on the body which enhance about 7 times of average systolic SNR and about 11 times of average diastolic SNR comparing to only one accelerometer method. Among the sensor placements, the performance of horizontal placement of the sensors is outstanding comparing with other positions on all motions. PMID:29614821

Robust real-time extraction of respiratory signals from PET list-mode data

NASA Astrophysics Data System (ADS)

Salomon, André; Zhang, Bin; Olivier, Patrick; Goedicke, Andreas

2018-06-01

Respiratory motion, which typically cannot simply be suspended during PET image acquisition, affects lesions’ detection and quantitative accuracy inside or in close vicinity to the lungs. Some motion compensation techniques address this issue via pre-sorting (‘binning’) of the acquired PET data into a set of temporal gates, where each gate is assumed to be minimally affected by respiratory motion. Tracking respiratory motion is typically realized using dedicated hardware (e.g. using respiratory belts and digital cameras). Extracting respiratory signals directly from the acquired PET data simplifies the clinical workflow as it avoids handling additional signal measurement equipment. We introduce a new data-driven method ‘combined local motion detection’ (CLMD). It uses the time-of-flight (TOF) information provided by state-of-the-art PET scanners in order to enable real-time respiratory signal extraction without additional hardware resources. CLMD applies center-of-mass detection in overlapping regions based on simple back-positioned TOF event sets acquired in short time frames. Following a signal filtering and quality-based pre-selection step, the remaining extracted individual position information over time is then combined to generate a global respiratory signal. The method is evaluated using seven measured FDG studies from single and multiple scan positions of the thorax region, and it is compared to other software-based methods regarding quantitative accuracy and statistical noise stability. Correlation coefficients around 90% between the reference and the extracted signal have been found for those PET scans where motion affected features such as tumors or hot regions were present in the PET field-of-view. For PET scans with a quarter of typically applied radiotracer doses, the CLMD method still provides similar high correlation coefficients which indicates its robustness to noise. Each CLMD processing needed less than 0.4 s in total on a standard multi-core CPU and thus provides a robust and accurate approach enabling real-time processing capabilities using standard PC hardware.

Robust high-resolution quantification of time signals encoded by in vivo magnetic resonance spectroscopy

NASA Astrophysics Data System (ADS)

Belkić, Dževad; Belkić, Karen

2018-01-01

This paper on molecular imaging emphasizes improving specificity of magnetic resonance spectroscopy (MRS) for early cancer diagnostics by high-resolution data analysis. Sensitivity of magnetic resonance imaging (MRI) is excellent, but specificity is insufficient. Specificity is improved with MRS by going beyond morphology to assess the biochemical content of tissue. This is contingent upon accurate data quantification of diagnostically relevant biomolecules. Quantification is spectral analysis which reconstructs chemical shifts, amplitudes and relaxation times of metabolites. Chemical shifts inform on electronic shielding of resonating nuclei bound to different molecular compounds. Oscillation amplitudes in time signals retrieve the abundance of MR sensitive nuclei whose number is proportional to metabolite concentrations. Transverse relaxation times, the reciprocal of decay probabilities of resonances, arise from spin-spin coupling and reflect local field inhomogeneities. In MRS single voxels are used. For volumetric coverage, multi-voxels are employed within a hybrid of MRS and MRI called magnetic resonance spectroscopic imaging (MRSI). Common to MRS and MRSI is encoding of time signals and subsequent spectral analysis. Encoded data do not provide direct clinical information. Spectral analysis of time signals can yield the quantitative information, of which metabolite concentrations are the most clinically important. This information is equivocal with standard data analysis through the non-parametric, low-resolution fast Fourier transform and post-processing via fitting. By applying the fast Padé transform (FPT) with high-resolution, noise suppression and exact quantification via quantum mechanical signal processing, advances are made, presented herein, focusing on four areas of critical public health importance: brain, prostate, breast and ovarian cancers.

Acousto-Optic Tunable Filter for Time-Domain Processing of Ultra-Short Optical Pulses,

DTIC Science & Technology

The application of acousto - optic tunable filters for shaping of ultra-fast pulses in the time domain is analyzed and demonstrated. With the rapid...advance of acousto - optic tunable filter (AOTF) technology, the opportunity for sophisticated signal processing capabilities arises. AOTFs offer unique

Nonlinear time-series analysis of current signal in cathodic contact glow discharge electrolysis

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

Allagui, Anis, E-mail: aallagui@sharjah.ac.ae; Abdelkareem, Mohammad Ali; Rojas, Andrea Espinel

In the standard two-electrode configuration employed in electrolytic process, when the control dc voltage is brought to a critical value, the system undergoes a transition from conventional electrolysis to contact glow discharge electrolysis (CGDE), which has also been referred to as liquid-submerged micro-plasma, glow discharge plasma electrolysis, electrode effect, electrolytic plasma, etc. The light-emitting process is associated with the development of an irregular and erratic current time-series which has been arbitrarily labelled as “random,” and thus dissuaded further research in this direction. Here, we examine the current time-series signals measured in cathodic CGDE configuration in a concentrated KOH solution atmore » different dc bias voltages greater than the critical voltage. We show that the signals are, in fact, not random according to the NIST SP. 800-22 test suite definition. We also demonstrate that post-processing low-pass filtered sequences requires less time than the native as-measured sequences, suggesting a superposition of low frequency chaotic fluctuations and high frequency behaviors (which may be produced by more than one possible source of entropy). Using an array of nonlinear time-series analyses for dynamical systems, i.e., the computation of largest Lyapunov exponents and correlation dimensions, and re-construction of phase portraits, we found that low-pass filtered datasets undergo a transition from quasi-periodic to chaotic to quasi-hyper-chaotic behavior, and back again to chaos when the voltage controlling-parameter is increased. The high frequency part of the signals is discussed in terms of highly nonlinear turbulent motion developed around the working electrode.« less

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

PubMed Central

Mobli, Mehdi; Hoch, Jeffrey C.

2017-01-01

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

A New High-Resolution Direction Finding Architecture Using Photonics and Neural Network Signal Processing for Miniature Air Vehicle Applications

DTIC Science & Technology

2015-09-01

3 4. Probability of Intercept .................................................................3 5. Superresolution ...intercept. This alignment gives the shortest mean-time-to-intercept and can be less than one second. 4 5. Superresolution For single signals...at each antenna element. For multiple signals, superresolution DF techniques are often used. These techniques can be broken down into beamforming

Detector signal correction method and system

DOEpatents

Carangelo, Robert M.; Duran, Andrew J.; Kudman, Irwin

1995-07-11

Corrective factors are applied so as to remove anomalous features from the signal generated by a photoconductive detector, and to thereby render the output signal highly linear with respect to the energy of incident, time-varying radiation. The corrective factors may be applied through the use of either digital electronic data processing means or analog circuitry, or through a combination of those effects.

Detector signal correction method and system

DOEpatents

Carangelo, R.M.; Duran, A.J.; Kudman, I.

1995-07-11

Corrective factors are applied so as to remove anomalous features from the signal generated by a photoconductive detector, and to thereby render the output signal highly linear with respect to the energy of incident, time-varying radiation. The corrective factors may be applied through the use of either digital electronic data processing means or analog circuitry, or through a combination of those effects. 5 figs.

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

NASA Astrophysics Data System (ADS)

Sherlock, Barry G.; Kakad, Yogendra P.

2001-10-01

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

A Real-Time Capable Software-Defined Receiver Using GPU for Adaptive Anti-Jam GPS Sensors

PubMed Central

Seo, Jiwon; Chen, Yu-Hsuan; De Lorenzo, David S.; Lo, Sherman; Enge, Per; Akos, Dennis; Lee, Jiyun

2011-01-01

Due to their weak received signal power, Global Positioning System (GPS) signals are vulnerable to radio frequency interference. Adaptive beam and null steering of the gain pattern of a GPS antenna array can significantly increase the resistance of GPS sensors to signal interference and jamming. Since adaptive array processing requires intensive computational power, beamsteering GPS receivers were usually implemented using hardware such as field-programmable gate arrays (FPGAs). However, a software implementation using general-purpose processors is much more desirable because of its flexibility and cost effectiveness. This paper presents a GPS software-defined radio (SDR) with adaptive beamsteering capability for anti-jam applications. The GPS SDR design is based on an optimized desktop parallel processing architecture using a quad-core Central Processing Unit (CPU) coupled with a new generation Graphics Processing Unit (GPU) having massively parallel processors. This GPS SDR demonstrates sufficient computational capability to support a four-element antenna array and future GPS L5 signal processing in real time. After providing the details of our design and optimization schemes for future GPU-based GPS SDR developments, the jamming resistance of our GPS SDR under synthetic wideband jamming is presented. Since the GPS SDR uses commercial-off-the-shelf hardware and processors, it can be easily adopted in civil GPS applications requiring anti-jam capabilities. PMID:22164116

A review of channel selection algorithms for EEG signal processing

NASA Astrophysics Data System (ADS)

Alotaiby, Turky; El-Samie, Fathi E. Abd; Alshebeili, Saleh A.; Ahmad, Ishtiaq

2015-12-01

Digital processing of electroencephalography (EEG) signals has now been popularly used in a wide variety of applications such as seizure detection/prediction, motor imagery classification, mental task classification, emotion classification, sleep state classification, and drug effects diagnosis. With the large number of EEG channels acquired, it has become apparent that efficient channel selection algorithms are needed with varying importance from one application to another. The main purpose of the channel selection process is threefold: (i) to reduce the computational complexity of any processing task performed on EEG signals by selecting the relevant channels and hence extracting the features of major importance, (ii) to reduce the amount of overfitting that may arise due to the utilization of unnecessary channels, for the purpose of improving the performance, and (iii) to reduce the setup time in some applications. Signal processing tools such as time-domain analysis, power spectral estimation, and wavelet transform have been used for feature extraction and hence for channel selection in most of channel selection algorithms. In addition, different evaluation approaches such as filtering, wrapper, embedded, hybrid, and human-based techniques have been widely used for the evaluation of the selected subset of channels. In this paper, we survey the recent developments in the field of EEG channel selection methods along with their applications and classify these methods according to the evaluation approach.

A real-time capable software-defined receiver using GPU for adaptive anti-jam GPS sensors.

PubMed

Seo, Jiwon; Chen, Yu-Hsuan; De Lorenzo, David S; Lo, Sherman; Enge, Per; Akos, Dennis; Lee, Jiyun

2011-01-01

Due to their weak received signal power, Global Positioning System (GPS) signals are vulnerable to radio frequency interference. Adaptive beam and null steering of the gain pattern of a GPS antenna array can significantly increase the resistance of GPS sensors to signal interference and jamming. Since adaptive array processing requires intensive computational power, beamsteering GPS receivers were usually implemented using hardware such as field-programmable gate arrays (FPGAs). However, a software implementation using general-purpose processors is much more desirable because of its flexibility and cost effectiveness. This paper presents a GPS software-defined radio (SDR) with adaptive beamsteering capability for anti-jam applications. The GPS SDR design is based on an optimized desktop parallel processing architecture using a quad-core Central Processing Unit (CPU) coupled with a new generation Graphics Processing Unit (GPU) having massively parallel processors. This GPS SDR demonstrates sufficient computational capability to support a four-element antenna array and future GPS L5 signal processing in real time. After providing the details of our design and optimization schemes for future GPU-based GPS SDR developments, the jamming resistance of our GPS SDR under synthetic wideband jamming is presented. Since the GPS SDR uses commercial-off-the-shelf hardware and processors, it can be easily adopted in civil GPS applications requiring anti-jam capabilities.

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

DOEpatents

Qian, Shie; Dunham, Mark E.

1996-01-01

A system and method for constructing a bank of filters which detect the presence of signals whose frequency content varies with time. The present invention includes a novel system and method for developing one or more time templates designed to match the received signals of interest and the bank of matched filters use the one or more time templates to detect the received signals. Each matched filter compares the received signal x(t) with a respective, unique time template that has been designed to approximate a form of the signals of interest. The robust time domain template is assumed to be of the order of w(t)=A(t)cos{2.pi..phi.(t)} and the present invention uses the trajectory of a joint time-frequency representation of x(t) as an approximation of the instantaneous frequency function {.phi.'(t). First, numerous data samples of the received signal x(t) are collected. A joint time frequency representation is then applied to represent the signal, preferably using the time frequency distribution series (also known as the Gabor spectrogram). The joint time-frequency transformation represents the analyzed signal energy at time t and frequency .function., P(t,f), which is a three-dimensional plot of time vs. frequency vs. signal energy. Then P(t,f) is reduced to a multivalued function f(t), a two dimensional plot of time vs. frequency, using a thresholding process. Curve fitting steps are then performed on the time/frequency plot, preferably using Levenberg-Marquardt curve fitting techniques, to derive a general instantaneous frequency function .phi.'(t) which best fits the multivalued function f(t), a trajectory of the joint time-frequency domain representation of x(t). Integrating .phi.'(t) along t yields .phi.(t), which is then inserted into the form of the time template equation. A suitable amplitude A(t) is also preferably determined. Once the time template has been determined, one or more filters are developed which each use a version or form of the time template.

Signal Processing for Time-Series Functions on a Graph

DTIC Science & Technology

2018-02-01

as filtering to functions supported on graphs. These methods can be applied to scalar functions with a domain that can be described by a fixed...classical signal processing such as filtering to account for the graph domain. This work essentially divides into 2 basic approaches: graph Laplcian...based filtering and weighted adjacency matrix-based filtering . In Shuman et al.,11 and elaborated in Bronstein et al.,13 filtering operators are

Real-time nondestructive monitoring of the gas tungsten arc welding (GTAW) process by combined airborne acoustic emission and non-contact ultrasonics

NASA Astrophysics Data System (ADS)

Zhang, Lu; Basantes-Defaz, Alexandra-Del-Carmen; Abbasi, Zeynab; Yuhas, Donald; Ozevin, Didem; Indacochea, Ernesto

2018-03-01

Welding is a key manufacturing process for many industries and may introduce defects into the welded parts causing significant negative impacts, potentially ruining high-cost pieces. Therefore, a real-time process monitoring method is important to implement for avoiding producing a low-quality weld. Due to high surface temperature and possible contamination of surface by contact transducers, the welding process should be monitored via non-contact transducers. In this paper, airborne acoustic emission (AE) transducers tuned at 60 kHz and non-contact ultrasonic testing (UT) transducers tuned at 500 kHz are implemented for real time weld monitoring. AE is a passive nondestructive evaluation method that listens for the process noise, and provides information about the uniformity of manufacturing process. UT provides more quantitative information about weld defects. One of the most common weld defects as burn-through is investigated. The influences of weld defects on AE signatures (time-driven data) and UT signals (received signal energy, change in peak frequency) are presented. The level of burn-through damage is defined by using single method or combine AE/UT methods.

Model of the best-of-N nest-site selection process in honeybees.

PubMed

Reina, Andreagiovanni; Marshall, James A R; Trianni, Vito; Bose, Thomas

2017-05-01

The ability of a honeybee swarm to select the best nest site plays a fundamental role in determining the future colony's fitness. To date, the nest-site selection process has mostly been modeled and theoretically analyzed for the case of binary decisions. However, when the number of alternative nests is larger than two, the decision-process dynamics qualitatively change. In this work, we extend previous analyses of a value-sensitive decision-making mechanism to a decision process among N nests. First, we present the decision-making dynamics in the symmetric case of N equal-quality nests. Then, we generalize our findings to a best-of-N decision scenario with one superior nest and N-1 inferior nests, previously studied empirically in bees and ants. Whereas previous binary models highlighted the crucial role of inhibitory stop-signaling, the key parameter in our new analysis is the relative time invested by swarm members in individual discovery and in signaling behaviors. Our new analysis reveals conflicting pressures on this ratio in symmetric and best-of-N decisions, which could be solved through a time-dependent signaling strategy. Additionally, our analysis suggests how ecological factors determining the density of suitable nest sites may have led to selective pressures for an optimal stable signaling ratio.

Performance analysis of gamma ray spectrometric parameters on digital signal and analog signal processing based MCA systems using NaI(Tl) detector.

PubMed

Kukreti, B M; Sharma, G K

2012-05-01

Accurate and speedy estimations of ppm range uranium and thorium in the geological and rock samples are most useful towards ongoing uranium investigations and identification of favorable radioactive zones in the exploration field areas. In this study with the existing 5 in. × 4 in. NaI(Tl) detector setup, prevailing background and time constraints, an enhanced geometrical setup has been worked out to improve the minimum detection limits for primordial radioelements K(40), U(238) and Th(232). This geometrical setup has been integrated with the newly introduced, digital signal processing based MCA system for the routine spectrometric analysis of low concentration rock samples. Stability performance, during the long counting hours, for digital signal processing MCA system and its predecessor NIM bin based MCA system has been monitored, using the concept of statistical process control. Monitored results, over a time span of few months, have been quantified in terms of spectrometer's parameters such as Compton striping constants and Channel sensitivities, used for evaluating primordial radio element concentrations (K(40), U(238) and Th(232)) in geological samples. Results indicate stable dMCA performance, with a tendency of higher relative variance, about mean, particularly for Compton stripping constants. Copyright © 2012 Elsevier Ltd. All rights reserved.

Model of the best-of-N nest-site selection process in honeybees

NASA Astrophysics Data System (ADS)

Reina, Andreagiovanni; Marshall, James A. R.; Trianni, Vito; Bose, Thomas

2017-05-01

The ability of a honeybee swarm to select the best nest site plays a fundamental role in determining the future colony's fitness. To date, the nest-site selection process has mostly been modeled and theoretically analyzed for the case of binary decisions. However, when the number of alternative nests is larger than two, the decision-process dynamics qualitatively change. In this work, we extend previous analyses of a value-sensitive decision-making mechanism to a decision process among N nests. First, we present the decision-making dynamics in the symmetric case of N equal-quality nests. Then, we generalize our findings to a best-of-N decision scenario with one superior nest and N -1 inferior nests, previously studied empirically in bees and ants. Whereas previous binary models highlighted the crucial role of inhibitory stop-signaling, the key parameter in our new analysis is the relative time invested by swarm members in individual discovery and in signaling behaviors. Our new analysis reveals conflicting pressures on this ratio in symmetric and best-of-N decisions, which could be solved through a time-dependent signaling strategy. Additionally, our analysis suggests how ecological factors determining the density of suitable nest sites may have led to selective pressures for an optimal stable signaling ratio.

Stepped-frequency GPR for utility line detection using polarization-dependent scattering

NASA Astrophysics Data System (ADS)

Jensen, Ole K.; Gregersen, Ole G.

2000-04-01

A GPR for detection of buried cables and pipes is developed by Ekko Dane Production in cooperation with Aalborg University. The appearance is a 'lawn mower' model including antennas, electronics and on-line data processing. A successful result is obtained by combining dedicated hardware and signal processing. The inherent signal to clutter ratio is bad, but making measurements at many polarization angles and subsequent signal processing improves the ratio. A simple model of the polarization dependence of the scattering from the target is used. The method is improved by combining the polarization filtering with averaging over small horizontal displacements. A stepped frequency measurement system is used. The method often implies long measurement times, but this problem is overcome by development of fast RF-electronics. Standard signal processors are used for real-time data processing. Several antenna array configurations are tested and optimized for low coupling between transmitter and receiver and for a short impulse response. A large number of tests have been made for different targets, e.g. metal cables and plastic pipes filled with air or water. Tests have been made under realistic ground conditions, including sand, wet clay, pavements and grass covered soil. The results show reliable detection even when the conditions are difficult.

Comparative of signal processing techniques for micro-Doppler signature extraction with automotive radar systems

NASA Astrophysics Data System (ADS)

Rodriguez-Hervas, Berta; Maile, Michael; Flores, Benjamin C.

2014-05-01

In recent years, the automotive industry has experienced an evolution toward more powerful driver assistance systems that provide enhanced vehicle safety. These systems typically operate in the optical and microwave regions of the electromagnetic spectrum and have demonstrated high efficiency in collision and risk avoidance. Microwave radar systems are particularly relevant due to their operational robustness under adverse weather or illumination conditions. Our objective is to study different signal processing techniques suitable for extraction of accurate micro-Doppler signatures of slow moving objects in dense urban environments. Selection of the appropriate signal processing technique is crucial for the extraction of accurate micro-Doppler signatures that will lead to better results in a radar classifier system. For this purpose, we perform simulations of typical radar detection responses in common driving situations and conduct the analysis with several signal processing algorithms, including short time Fourier Transform, continuous wavelet or Kernel based analysis methods. We take into account factors such as the relative movement between the host vehicle and the target, and the non-stationary nature of the target's movement. A comparison of results reveals that short time Fourier Transform would be the best approach for detection and tracking purposes, while the continuous wavelet would be the best suited for classification purposes.

Frequency Domain Multiplexing for Use With NaI[Tl] Detectors

NASA Astrophysics Data System (ADS)

Belling, Samuel; Coherent Collaboration

2017-09-01

A process used in many forms of signal communication known as multiplexing is adapted for the purpose of combining signals from NaI[Tl] detectors so that fewer digitizer channels can be used to process the signal information from large experiments within the COHERENT collaboration. Each signal is passed through a ringing circuit to modulate it with a characteristic frequency. Information about the signal can be extracted from its amplitude, frequency, and phase. Simulations in LTSpice show that an operational amplifier circuit with a parallel LRC feedback loop can serve as the modulating circuit. Several such circuits can be constructed and housed compactly in a unit, and fed to an inverting, summing amplifier with tunable gain, such that the signals are carried by one cable. The signals are analyzed based on a Fourier transform after being digitized. The results show that the energy, channel, and time of the original interaction can be recovered by this process. In some cases it is possible through filtering and deconvolution to recover the shape of the original signal. The effort is ongoing, but with the design presented it is possible to multiplex 10 detectors into a single digitizer channel. NSF REU Program at Duke University.

Investigation on the coloured noise in GPS-derived position with time-varying seasonal signals

NASA Astrophysics Data System (ADS)

Gruszczynska, Marta; Klos, Anna; Bos, Machiel Simon; Bogusz, Janusz

2016-04-01

The seasonal signals in the GPS-derived time series arise from real geophysical signals related to tidal (residual) or non-tidal (loadings from atmosphere, ocean and continental hydrosphere, thermo elastic strain, etc.) effects and numerical artefacts including aliasing from mismodelling in short periods or repeatability of the GPS satellite constellation with respect to the Sun (draconitics). Singular Spectrum Analysis (SSA) is a method for investigation of nonlinear dynamics, suitable to either stationary or non-stationary data series without prior knowledge about their character. The aim of SSA is to mathematically decompose the original time series into a sum of slowly varying trend, seasonal oscillations and noise. In this presentation we will explore the ability of SSA to subtract the time-varying seasonal signals in GPS-derived North-East-Up topocentric components and show properties of coloured noise from residua. For this purpose we used data from globally distributed IGS (International GNSS Service) permanent stations processed by the JPL (Jet Propulsion Laboratory) in a PPP (Precise Point Positioning) mode. After introducing a threshold of 13 years, 264 stations left with a maximum length reaching 23 years. The data was initially pre-processed for outliers, offsets and gaps. The SSA was applied to pre-processed series to estimate the time-varying seasonal signals. We adopted a 3-years window as the optimal dimension of its size determined with the Akaike's Information Criteria (AIC) values. A Fisher-Snedecor test corrected for the presence of temporal correlation was used to determine the statistical significance of reconstructed components. This procedure showed that first four components describing annual and semi-annual signals, are significant at a 99.7% confidence level, which corresponds to 3-sigma criterion. We compared the non-parametric SSA approach with a commonly chosen parametric Least-Squares Estimation that assumes constant amplitudes and phases over time. We noticed a maximum difference in seasonal oscillation of 3.5 mm and a maximum change in velocity of 0.15 mm/year for Up component (YELL, Yellowknife, Canada), when SSA and LSE are compared. The annual signal has the greatest influence on data variability in time series, while the semi-annual signal in Up component has much smaller contribution in the total variance of data. For some stations more than 35% of the total variance is explained by annual signal. According to the Power Spectral Densities (PSD) we proved that SSA has the ability to properly subtract the seasonals changing in time with almost no influence on power-law character of stochastic part. Then, the modified Maximum Likelihood Estimation (MLE) in Hector software was applied to SSA-filtered time series. We noticed a significant improvement in spectral indices and power-law amplitudes in comparison to classically determined ones with LSE, which will be the main subject of this presentation.

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.

An FPGA-based High Speed Parallel Signal Processing System for Adaptive Optics Testbed

NASA Astrophysics Data System (ADS)

Kim, H.; Choi, Y.; Yang, Y.

In this paper a state-of-the-art FPGA (Field Programmable Gate Array) based high speed parallel signal processing system (SPS) for adaptive optics (AO) testbed with 1 kHz wavefront error (WFE) correction frequency is reported. The AO system consists of Shack-Hartmann sensor (SHS) and deformable mirror (DM), tip-tilt sensor (TTS), tip-tilt mirror (TTM) and an FPGA-based high performance SPS to correct wavefront aberrations. The SHS is composed of 400 subapertures and the DM 277 actuators with Fried geometry, requiring high speed parallel computing capability SPS. In this study, the target WFE correction speed is 1 kHz; therefore, it requires massive parallel computing capabilities as well as strict hard real time constraints on measurements from sensors, matrix computation latency for correction algorithms, and output of control signals for actuators. In order to meet them, an FPGA based real-time SPS with parallel computing capabilities is proposed. In particular, the SPS is made up of a National Instrument's (NI's) real time computer and five FPGA boards based on state-of-the-art Xilinx Kintex 7 FPGA. Programming is done with NI's LabView environment, providing flexibility when applying different algorithms for WFE correction. It also facilitates faster programming and debugging environment as compared to conventional ones. One of the five FPGA's is assigned to measure TTS and calculate control signals for TTM, while the rest four are used to receive SHS signal, calculate slops for each subaperture and correction signal for DM. With this parallel processing capabilities of the SPS the overall closed-loop WFE correction speed of 1 kHz has been achieved. System requirements, architecture and implementation issues are described; furthermore, experimental results are also given.

Ultrafast chirped optical waveform recording using referenced heterodyning and a time microscope

DOEpatents

Bennett, Corey Vincent

2010-06-15

A new technique for capturing both the amplitude and phase of an optical waveform is presented. This technique can capture signals with many THz of bandwidths in a single shot (e.g., temporal resolution of about 44 fs), or be operated repetitively at a high rate. That is, each temporal window (or frame) is captured single shot, in real time, but the process may be run repeatedly or single-shot. This invention expands upon previous work in temporal imaging by adding heterodyning, which can be self-referenced for improved precision and stability, to convert frequency chirp (the second derivative of phase with respect to time) into a time varying intensity modulation. By also including a variety of possible demultiplexing techniques, this process is scalable to recoding continuous signals.

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.

Ultrafast chirped optical waveform recorder using referenced heterodyning and a time microscope

DOEpatents

Bennett, Corey Vincent [Livermore, CA

2011-11-22

A new technique for capturing both the amplitude and phase of an optical waveform is presented. This technique can capture signals with many THz of bandwidths in a single shot (e.g., temporal resolution of about 44 fs), or be operated repetitively at a high rate. That is, each temporal window (or frame) is captured single shot, in real time, but the process may be run repeatedly or single-shot. This invention expands upon previous work in temporal imaging by adding heterodyning, which can be self-referenced for improved precision and stability, to convert frequency chirp (the second derivative of phase with respect to time) into a time varying intensity modulation. By also including a variety of possible demultiplexing techniques, this process is scalable to recoding continuous signals.

Two-dimensional wavelet analysis based classification of gas chromatogram differential mobility spectrometry signals.

PubMed

Zhao, Weixiang; Sankaran, Shankar; Ibáñez, Ana M; Dandekar, Abhaya M; Davis, Cristina E

2009-08-04

This study introduces two-dimensional (2-D) wavelet analysis to the classification of gas chromatogram differential mobility spectrometry (GC/DMS) data which are composed of retention time, compensation voltage, and corresponding intensities. One reported method to process such large data sets is to convert 2-D signals to 1-D signals by summing intensities either across retention time or compensation voltage, but it can lose important signal information in one data dimension. A 2-D wavelet analysis approach keeps the 2-D structure of original signals, while significantly reducing data size. We applied this feature extraction method to 2-D GC/DMS signals measured from control and disordered fruit and then employed two typical classification algorithms to testify the effects of the resultant features on chemical pattern recognition. Yielding a 93.3% accuracy of separating data from control and disordered fruit samples, 2-D wavelet analysis not only proves its feasibility to extract feature from original 2-D signals but also shows its superiority over the conventional feature extraction methods including converting 2-D to 1-D and selecting distinguishable pixels from training set. Furthermore, this process does not require coupling with specific pattern recognition methods, which may help ensure wide applications of this method to 2-D spectrometry data.

The integration of familiarity and recollection information in short-term recognition: modeling speed-accuracy trade-off functions.

PubMed

Göthe, Katrin; Oberauer, Klaus

2008-05-01

Dual process models postulate familiarity and recollection as the basis of the recognition process. We investigated the time-course of integration of the two information sources to one recognition judgment in a working memory task. We tested 24 subjects with a response signal variant of the modified Sternberg recognition task (Oberauer, 2001) to isolate the time course of three different probe types indicating different combinations of familiarity and source information. We compared two mathematical models implementing different ways of integrating familiarity and recollection. Within each model, we tested three assumptions about the nature of the familiarity signal, with familiarity having (a) only positive values, indicating similarity of the probe with the memory list, (b) only negative values, indicating novelty, or (c) both positive and negative values. Both models provided good fits to the data. A model combining the outputs of both processes additively (Integration Model) gave an overall better fit to the data than a model based on a continuous familiarity signal and a probabilistic all-or-none recollection process (Dominance Model).

Interpretation of the auto-mutual information rate of decrease in the context of biomedical signal analysis. Application to electroencephalogram recordings.

PubMed

Escudero, Javier; Hornero, Roberto; Abásolo, Daniel

2009-02-01

The mutual information (MI) is a measure of both linear and nonlinear dependences. It can be applied to a time series and a time-delayed version of the same sequence to compute the auto-mutual information function (AMIF). Moreover, the AMIF rate of decrease (AMIFRD) with increasing time delay in a signal is correlated with its entropy and has been used to characterize biomedical data. In this paper, we aimed at gaining insight into the dependence of the AMIFRD on several signal processing concepts and at illustrating its application to biomedical time series analysis. Thus, we have analysed a set of synthetic sequences with the AMIFRD. The results show that the AMIF decreases more quickly as bandwidth increases and that the AMIFRD becomes more negative as there is more white noise contaminating the time series. Additionally, this metric detected changes in the nonlinear dynamics of a signal. Finally, in order to illustrate the analysis of real biomedical signals with the AMIFRD, this metric was applied to electroencephalogram (EEG) signals acquired with eyes open and closed and to ictal and non-ictal intracranial EEG recordings.

Comparison of sEMG-Based Feature Extraction and Motion Classification Methods for Upper-Limb Movement

PubMed Central

Guo, Shuxiang; Pang, Muye; Gao, Baofeng; Hirata, Hideyuki; Ishihara, Hidenori

2015-01-01

The surface electromyography (sEMG) technique is proposed for muscle activation detection and intuitive control of prostheses or robot arms. Motion recognition is widely used to map sEMG signals to the target motions. One of the main factors preventing the implementation of this kind of method for real-time applications is the unsatisfactory motion recognition rate and time consumption. The purpose of this paper is to compare eight combinations of four feature extraction methods (Root Mean Square (RMS), Detrended Fluctuation Analysis (DFA), Weight Peaks (WP), and Muscular Model (MM)) and two classifiers (Neural Networks (NN) and Support Vector Machine (SVM)), for the task of mapping sEMG signals to eight upper-limb motions, to find out the relation between these methods and propose a proper combination to solve this issue. Seven subjects participated in the experiment and six muscles of the upper-limb were selected to record sEMG signals. The experimental results showed that NN classifier obtained the highest recognition accuracy rate (88.7%) during the training process while SVM performed better in real-time experiments (85.9%). For time consumption, SVM took less time than NN during the training process but needed more time for real-time computation. Among the four feature extraction methods, WP had the highest recognition rate for the training process (97.7%) while MM performed the best during real-time tests (94.3%). The combination of MM and NN is recommended for strict real-time applications while a combination of MM and SVM will be more suitable when time consumption is not a key requirement. PMID:25894941

Classical analysis of time behavior of radiation fields associated with biophoton signals.

PubMed

Choi, Jeong Ryeol; Kim, Daeyeoul; Menouar, Salah; Sever, Ramazan; Abdalla, M Sebawe

2016-04-29

Propagation of photon signals in biological systems, such as neurons, accompanies the production of biophotons. The role of biophotons in a cell deserves special attention because it can be applied to diverse optical systems. This work has been aimed to investigate the time behavior of biophoton signals emitted from living systems in detail, by introducing a Hamiltonian that describes the process. The ratio of the energy loss during signal dissipation will also be investigated. To see the adiabatic properties of the biophoton signal, we introduced an adiabatic invariant of the system according to the method of its basic formulation. The energy of the released biophoton dissipates over time in a somewhat intricate way when t is small. However, after a sufficient long time, it dissipates in proportion (1+λ_0t)^2 to where λ_0 is a constant that is relevant to the degree of dissipation. We have confirmed that the energy of the biophoton signal oscillates in a particular way while it dissipates. This research clarifies the characteristics of radiation fields associated with biophotons on the basis of Hamiltonian dynamics which describes phenomenological aspects of biophotons signals.

Response Inhibition Is Facilitated by a Change to Red Over Green in the Stop Signal Paradigm

PubMed Central

Blizzard, Shawn; Fierro-Rojas, Adriela; Fallah, Mazyar

2017-01-01

Actions are informed by the complex interactions of response execution and inhibition networks. These networks integrate sensory information with internal states and behavioral goals to produce an appropriate action or to update an ongoing action. Recent investigations have shown that, behaviorally, attention is captured through a hierarchy of colors. These studies showed how the color hierarchy affected visual processing. To determine whether the color hierarchy can be extended to higher level executive functions such as response execution and inhibition, we conducted several experiments using the stop-signal task (SST). In the first experiment, we modified the classic paradigm so that the go signals could vary in task-irrelevant color, with an auditory stop signal. We found that the task-irrelevant color of the go signals did not differentially affect response times. In the second experiment we determined that making the color of the go signal relevant for response selection still did not affect reaction times(RTs) and, thus, execution. In the third experiment, we modified the paradigm so that the stop signal was a task relevant change in color of the go signal. The mean RT to the red stop signal was approximately 25 ms faster than to the green stop signal. In other words, red stop signals facilitated response inhibition more than green stop signals, however, there was no comparative facilitation of response execution. These findings suggest that response inhibition, but not execution, networks are sensitive to differences in color salience. They also suggest that the color hierarchy is based on attentional networks and not simply on early sensory processing. PMID:28101011

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.

Narrow field electromagnetic sensor system and method

DOEpatents

McEwan, Thomas E.

1996-01-01

A narrow field electromagnetic sensor system and method of sensing a characteristic of an object provide the capability to realize a characteristic of an object such as density, thickness, or presence, for any desired coordinate position on the object. One application is imaging. The sensor can also be used as an obstruction detector or an electronic trip wire with a narrow field without the disadvantages of impaired performance when exposed to dirt, snow, rain, or sunlight. The sensor employs a transmitter for transmitting a sequence of electromagnetic signals in response to a transmit timing signal, a receiver for sampling only the initial direct RF path of the electromagnetic signal while excluding all other electromagnetic signals in response to a receive timing signal, and a signal processor for processing the sampled direct RF path electromagnetic signal and providing an indication of the characteristic of an object. Usually, the electromagnetic signal is a short RF burst and the obstruction must provide a substantially complete eclipse of the direct RF path. By employing time-of-flight techniques, a timing circuit controls the receiver to sample only the initial direct RF path of the electromagnetic signal while not sampling indirect path electromagnetic signals. The sensor system also incorporates circuitry for ultra-wideband spread spectrum operation that reduces interference to and from other RF services while allowing co-location of multiple electronic sensors without the need for frequency assignments.

Narrow field electromagnetic sensor system and method

DOEpatents

McEwan, T.E.

1996-11-19

A narrow field electromagnetic sensor system and method of sensing a characteristic of an object provide the capability to realize a characteristic of an object such as density, thickness, or presence, for any desired coordinate position on the object. One application is imaging. The sensor can also be used as an obstruction detector or an electronic trip wire with a narrow field without the disadvantages of impaired performance when exposed to dirt, snow, rain, or sunlight. The sensor employs a transmitter for transmitting a sequence of electromagnetic signals in response to a transmit timing signal, a receiver for sampling only the initial direct RF path of the electromagnetic signal while excluding all other electromagnetic signals in response to a receive timing signal, and a signal processor for processing the sampled direct RF path electromagnetic signal and providing an indication of the characteristic of an object. Usually, the electromagnetic signal is a short RF burst and the obstruction must provide a substantially complete eclipse of the direct RF path. By employing time-of-flight techniques, a timing circuit controls the receiver to sample only the initial direct RF path of the electromagnetic signal while not sampling indirect path electromagnetic signals. The sensor system also incorporates circuitry for ultra-wideband spread spectrum operation that reduces interference to and from other RF services while allowing co-location of multiple electronic sensors without the need for frequency assignments. 12 figs.

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

PubMed

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

2009-01-01

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

Timing Recovery Strategies in Magnetic Recording Systems

NASA Astrophysics Data System (ADS)

Kovintavewat, Piya

At some point in a digital communications receiver, the received analog signal must be sampled. Good performance requires that these samples be taken at the right times. The process of synchronizing the sampler with the received analog waveform is known as timing recovery. Conventional timing recovery techniques perform well only when operating at high signal-to-noise ratio (SNR). Nonetheless, iterative error-control codes allow reliable communication at very low SNR, where conventional techniques fail. This paper provides a detailed review on the timing recovery strategies based on per-survivor processing (PSP) that are capable of working at low SNR. We also investigate their performance in magnetic recording systems because magnetic recording is a primary method of storage for a variety of applications, including desktop, mobile, and server systems. Results indicate that the timing recovery strategies based on PSP perform better than the conventional ones and are thus worth being employed in magnetic recording systems.

Reward alters the perception of time.

PubMed

Failing, Michel; Theeuwes, Jan

2016-03-01

Recent findings indicate that monetary rewards have a powerful effect on cognitive performance. In order to maximize overall gain, the prospect of earning reward biases visual attention to specific locations or stimulus features improving perceptual sensitivity and processing. The question we addressed in this study is whether the prospect of reward also affects the subjective perception of time. Here, participants performed a prospective timing task using temporal oddballs. The results show that temporal oddballs, displayed for varying durations, presented in a sequence of standard stimuli were perceived to last longer when they signaled a relatively high reward compared to when they signaled no or low reward. When instead of the oddball the standards signaled reward, the perception of the temporal oddball remained unaffected. We argue that by signaling reward, a stimulus becomes subjectively more salient thereby modulating its attentional deployment and distorting how it is perceived in time. Copyright © 2015 Elsevier B.V. All rights reserved.

A customizable system for real-time image processing using the Blackfin DSProcessor and the MicroC/OS-II real-time kernel

NASA Astrophysics Data System (ADS)

Coffey, Stephen; Connell, Joseph

2005-06-01

This paper presents a development platform for real-time image processing based on the ADSP-BF533 Blackfin processor and the MicroC/OS-II real-time operating system (RTOS). MicroC/OS-II is a completely portable, ROMable, pre-emptive, real-time kernel. The Blackfin Digital Signal Processors (DSPs), incorporating the Analog Devices/Intel Micro Signal Architecture (MSA), are a broad family of 16-bit fixed-point products with a dual Multiply Accumulate (MAC) core. In addition, they have a rich instruction set with variable instruction length and both DSP and MCU functionality thus making them ideal for media based applications. Using the MicroC/OS-II for task scheduling and management, the proposed system can capture and process raw RGB data from any standard 8-bit greyscale image sensor in soft real-time and then display the processed result using a simple PC graphical user interface (GUI). Additionally, the GUI allows configuration of the image capture rate and the system and core DSP clock rates thereby allowing connectivity to a selection of image sensors and memory devices. The GUI also allows selection from a set of image processing algorithms based in the embedded operating system.

Radar wideband digital beamforming based on time delay and phase compensation

NASA Astrophysics Data System (ADS)

Fu, Wei; Jiang, Defu

2018-07-01

In conventional phased array radars, analogue time delay devices and phase shifters have been used for wideband beamforming. These methods suffer from insertion losses, gain mismatches and delay variations, and they occupy a large chip area. To solve these problems, a compact architecture of digital array antennas based on subarrays was considered. In this study, the receiving beam patterns of wideband linear frequency modulation (LFM) signals were constructed by applying analogue stretch processing via mixing with delayed reference signals at the subarray level. Subsequently, narrowband digital time delaying and phase compensation of the tone signals were implemented with reduced arithmetic complexity. Due to the differences in amplitudes, phases and time delays between channels, severe performance degradation of the beam patterns occurred without corrections. To achieve good beamforming performance, array calibration was performed in each channel to adjust the amplitude, frequency and phase of the tone signal. Using a field-programmable gate array, wideband LFM signals and finite impulse response filters with continuously adjustable time delays were implemented in a polyphase structure. Simulations and experiments verified the feasibility and effectiveness of the proposed digital beamformer.

Real-Time Visualization of Tissue Ischemia

NASA Technical Reports Server (NTRS)

Bearman, Gregory H. (Inventor); Chrien, Thomas D. (Inventor); Eastwood, Michael L. (Inventor)

2000-01-01

A real-time display of tissue ischemia which comprises three CCD video cameras, each with a narrow bandwidth filter at the correct wavelength is discussed. The cameras simultaneously view an area of tissue suspected of having ischemic areas through beamsplitters. The output from each camera is adjusted to give the correct signal intensity for combining with, the others into an image for display. If necessary a digital signal processor (DSP) can implement algorithms for image enhancement prior to display. Current DSP engines are fast enough to give real-time display. Measurement at three, wavelengths, combined into a real-time Red-Green-Blue (RGB) video display with a digital signal processing (DSP) board to implement image algorithms, provides direct visualization of ischemic areas.

Computational problems and signal processing in SETI

NASA Technical Reports Server (NTRS)

Deans, Stanley R.; Cullers, D. K.; Stauduhar, Richard

1991-01-01

The Search for Extraterrestrial Intelligence (SETI), currently being planned at NASA, will require that an enormous amount of data (on the order of 10 exp 11 distinct signal paths for a typical observation) be analyzed in real time by special-purpose hardware. Even though the SETI system design is not based on maximum entropy and Bayesian methods (partly due to the real-time processing constraint), it is expected that enough data will be saved to be able to apply these and other methods off line where computational complexity is not an overriding issue. Interesting computational problems that relate directly to the system design for processing such an enormous amount of data have emerged. Some of these problems are discussed, along with the current status on their solution.

Using Seismic Signals to Forecast Volcanic Processes

NASA Astrophysics Data System (ADS)

Salvage, R.; Neuberg, J. W.

2012-04-01

Understanding seismic signals generated during volcanic unrest have the ability to allow scientists to more accurately predict and understand active volcanoes since they are intrinsically linked to rock failure at depth (Voight, 1988). In particular, low frequency long period signals (LP events) have been related to the movement of fluid and the brittle failure of magma at depth due to high strain rates (Hammer and Neuberg, 2009). This fundamentally relates to surface processes. However, there is currently no physical quantitative model for determining the likelihood of an eruption following precursory seismic signals, or the timing or type of eruption that will ensue (Benson et al., 2010). Since the beginning of its current eruptive phase, accelerating LP swarms (< 10 events per hour) have been a common feature at Soufriere Hills volcano, Montserrat prior to surface expressions such as dome collapse or eruptions (Miller et al., 1998). The dynamical behaviour of such swarms can be related to accelerated magma ascent rates since the seismicity is thought to be a consequence of magma deformation as it rises to the surface. In particular, acceleration rates can be successfully used in collaboration with the inverse material failure law; a linear relationship against time (Voight, 1988); in the accurate prediction of volcanic eruption timings. Currently, this has only been investigated for retrospective events (Hammer and Neuberg, 2009). The identification of LP swarms on Montserrat and analysis of their dynamical characteristics allows a better understanding of the nature of the seismic signals themselves, as well as their relationship to surface processes such as magma extrusion rates. Acceleration and deceleration rates of seismic swarms provide insights into the plumbing system of the volcano at depth. The application of the material failure law to multiple LP swarms of data allows a critical evaluation of the accuracy of the method which further refines current understanding of the relationship between seismic signals and volcanic eruptions. It is hoped that such analysis will assist the development of real time forecasting models.

Nonparametric Simulation of Signal Transduction Networks with Semi-Synchronized Update

PubMed Central

Nassiri, Isar; Masoudi-Nejad, Ali; Jalili, Mahdi; Moeini, Ali

2012-01-01

Simulating signal transduction in cellular signaling networks provides predictions of network dynamics by quantifying the changes in concentration and activity-level of the individual proteins. Since numerical values of kinetic parameters might be difficult to obtain, it is imperative to develop non-parametric approaches that combine the connectivity of a network with the response of individual proteins to signals which travel through the network. The activity levels of signaling proteins computed through existing non-parametric modeling tools do not show significant correlations with the observed values in experimental results. In this work we developed a non-parametric computational framework to describe the profile of the evolving process and the time course of the proportion of active form of molecules in the signal transduction networks. The model is also capable of incorporating perturbations. The model was validated on four signaling networks showing that it can effectively uncover the activity levels and trends of response during signal transduction process. PMID:22737250

Communication system with adaptive noise suppression

NASA Technical Reports Server (NTRS)

Kozel, David (Inventor); Devault, James A. (Inventor); Birr, Richard B. (Inventor)

2007-01-01

A signal-to-noise ratio dependent adaptive spectral subtraction process eliminates noise from noise-corrupted speech signals. The process first pre-emphasizes the frequency components of the input sound signal which contain the consonant information in human speech. Next, a signal-to-noise ratio is determined and a spectral subtraction proportion adjusted appropriately. After spectral subtraction, low amplitude signals can be squelched. A single microphone is used to obtain both the noise-corrupted speech and the average noise estimate. This is done by determining if the frame of data being sampled is a voiced or unvoiced frame. During unvoiced frames an estimate of the noise is obtained. A running average of the noise is used to approximate the expected value of the noise. Spectral subtraction may be performed on a composite noise-corrupted signal, or upon individual sub-bands of the noise-corrupted signal. Pre-averaging of the input signal's magnitude spectrum over multiple time frames may be performed to reduce musical noise.

Non-stationary least-squares complex decomposition for microseismic noise attenuation

NASA Astrophysics Data System (ADS)

Chen, Yangkang

2018-06-01

Microseismic data processing and imaging are crucial for subsurface real-time monitoring during hydraulic fracturing process. Unlike the active-source seismic events or large-scale earthquake events, the microseismic event is usually of very small magnitude, which makes its detection challenging. The biggest trouble of microseismic data is the low signal-to-noise ratio issue. Because of the small energy difference between effective microseismic signal and ambient noise, the effective signals are usually buried in strong random noise. I propose a useful microseismic denoising algorithm that is based on decomposing a microseismic trace into an ensemble of components using least-squares inversion. Based on the predictive property of useful microseismic event along the time direction, the random noise can be filtered out via least-squares fitting of multiple damping exponential components. The method is flexible and almost automated since the only parameter needed to be defined is a decomposition number. I use some synthetic and real data examples to demonstrate the potential of the algorithm in processing complicated microseismic data sets.

Acoustic Data Processing and Transient Signal Analysis for the Hybrid Wing Body 14- by 22-Foot Subsonic Wind Tunnel Test

NASA Technical Reports Server (NTRS)

Bahr, Christopher J.; Brooks, Thomas F.; Humphreys, William M.; Spalt, Taylor B.; Stead, Daniel J.

2014-01-01

An advanced vehicle concept, the HWB N2A-EXTE aircraft design, was tested in NASA Langley's 14- by 22-Foot Subsonic Wind Tunnel to study its acoustic characteristics for var- ious propulsion system installation and airframe con gurations. A signi cant upgrade to existing data processing systems was implemented, with a focus on portability and a re- duction in turnaround time. These requirements were met by updating codes originally written for a cluster environment and transferring them to a local workstation while en- abling GPU computing. Post-test, additional processing of the time series was required to remove transient hydrodynamic gusts from some of the microphone time series. A novel automated procedure was developed to analyze and reject contaminated blocks of data, under the assumption that the desired acoustic signal of interest was a band-limited sta- tionary random process, and of lower variance than the hydrodynamic contamination. The procedure is shown to successfully identify and remove contaminated blocks of data and retain the desired acoustic signal. Additional corrections to the data, mainly background subtraction, shear layer refraction calculations, atmospheric attenuation and microphone directivity corrections, were all necessary for initial analysis and noise assessments. These were implemented for the post-processing of spectral data, and are shown to behave as expected.

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.

FIBER AND INTEGRATED OPTICS. OTHER TOPICS IN QUANTUM ELECTRONICS: Investigation of an electrooptic multichannel-waveguide modulator as a controlled transparency

NASA Astrophysics Data System (ADS)

Bykovskiĭ, Yu A.; Zheregi, V. G.; Kulchin, Yurii N.; Poryadin, Yu D.; Smirnov, V. L.; Fomichev, N. N.

1990-05-01

An investigation was made of a multichannel LiNbO3 waveguide modulator of light in space and time, suitable for processing of analog and digital signals. This modulator had 26 channels and the half-wave control voltage was 4.5 V. A theoretical analysis and an experimental study were made of the functional performance of this modulator depending on the channel interconnections and on the nature of the signals applied to the modulator. The feasibility of processing analog and digital signals was studied.

Real-time wideband cylindrical holographic surveillance system

DOEpatents

Sheen, David M.; McMakin, Douglas L.; Hall, Thomas E.; Severtsen, Ronald H.

1999-01-01

A wideband holographic cylindrical surveillance system including a transceiver for generating a plurality of electromagnetic waves; antenna for transmitting the electromagnetic waves toward a target at a plurality of predetermined positions in space; the transceiver also receiving and converting electromagnetic waves reflected from the target to electrical signals at a plurality of predetermined positions in space; a computer for processing the electrical signals to obtain signals corresponding to a holographic reconstruction of the target; and a display for displaying the processed information to determine nature of the target. The computer has instructions to apply Fast Fourier Transforms and obtain a three dimensional cylindrical image.

Parallel demodulation system and signal-processing method for extrinsic Fabry-Perot interferometer and fiber Bragg grating sensors.

PubMed

Jiang, Junfeng; Liu, Tiegen; Zhang, Yimo; Liu, Lina; Zha, Ying; Zhang, Fan; Wang, Yunxin; Long, Pin

2005-03-15

A parallel demodulation system for extrinsic Fabry-Perot interferometer (EFPI) and fiber Bragg grating (FBG) sensors is presented that is based on a Michelson interferometer and combines the methods of low-coherence interference and Fourier transform spectrum. Signals from EFPI and FBG sensors are obtained simultaneously by scanning one arm of a Michelson interferometer, and an algorithm model is established to process the signals and retrieve both the wavelength of the FBG and the cavity length of the EFPI at the same time, which are then used to determine the strain and temperature.

Real-time wideband holographic surveillance system

DOEpatents

Sheen, David M.; Collins, H. Dale; Hall, Thomas E.; McMakin, Douglas L.; Gribble, R. Parks; Severtsen, Ronald H.; Prince, James M.; Reid, Larry D.

1996-01-01

A wideband holographic surveillance system including a transceiver for generating a plurality of electromagnetic waves; antenna for transmitting the electromagnetic waves toward a target at a plurality of predetermined positions in space; the transceiver also receiving and converting electromagnetic waves reflected from the target to electrical signals at a plurality of predetermined positions in space; a computer for processing the electrical signals to obtain signals corresponding to a holographic reconstruction of the target; and a display for displaying the processed information to determine nature of the target. The computer has instructions to apply a three dimensional backward wave algorithm.

Real-time wideband holographic surveillance system

DOEpatents

Sheen, D.M.; Collins, H.D.; Hall, T.E.; McMakin, D.L.; Gribble, R.P.; Severtsen, R.H.; Prince, J.M.; Reid, L.D.

1996-09-17

A wideband holographic surveillance system including a transceiver for generating a plurality of electromagnetic waves; antenna for transmitting the electromagnetic waves toward a target at a plurality of predetermined positions in space; the transceiver also receiving and converting electromagnetic waves reflected from the target to electrical signals at a plurality of predetermined positions in space; a computer for processing the electrical signals to obtain signals corresponding to a holographic reconstruction of the target; and a display for displaying the processed information to determine nature of the target. The computer has instructions to apply a three dimensional backward wave algorithm. 28 figs.

Superconducting active impedance converter

DOEpatents

Ginley, David S.; Hietala, Vincent M.; Martens, Jon S.

1993-01-01

A transimpedance amplifier for use with high temperature superconducting, other superconducting, and conventional semiconductor allows for appropriate signal amplification and impedance matching to processing electronics. The amplifier incorporates the superconducting flux flow transistor into a differential amplifier configuration which allows for operation over a wide temperature range, and is characterized by high gain, relatively low noise, and response times less than 200 picoseconds over at least a 10-80 K. temperature range. The invention is particularly useful when a signal derived from either far-IR focal plane detectors or from Josephson junctions is to be processed by higher signal/higher impedance electronics, such as conventional semiconductor technology.

Optimal causal filtering for 1 /fα-type noise in single-electrode EEG signals.

PubMed

Paris, Alan; Atia, George; Vosoughi, Azadeh; Berman, Stephen A

2016-08-01

Understanding the mode of generation and the statistical structure of neurological noise is one of the central problems of biomedical signal processing. We have developed a broad class of abstract biological noise sources we call hidden simplicial tissues. In the simplest cases, such tissue emits what we have named generalized van der Ziel-McWhorter (GVZM) noise which has a roughly 1/fα spectral roll-off. Our previous work focused on the statistical structure of GVZM frequency spectra. However, causality of processing operations (i.e., dependence only on the past) is an essential requirement for real-time applications to seizure detection and brain-computer interfacing. In this paper we outline the theoretical background for optimal causal time-domain filtering of deterministic signals embedded in GVZM noise. We present some of our early findings concerning the optimal filtering of EEG signals for the detection of steady-state visual evoked potential (SSVEP) responses and indicate the next steps in our ongoing research.

Acoustic emission evolution during sliding friction of Hadfield steel single crystal

NASA Astrophysics Data System (ADS)

Lychagin, D. V.; Novitskaya, O. S.; Kolubaev, A. V.; Sizova, O. V.

2017-12-01

Friction is a complex dynamic process. Direct observation of processes occurring in the friction zone is impossible due to a small size of a real contact area and, as a consequence, requires various additional methods applicable to monitor a tribological contact state. One of such methods consists in the analysis of acoustic emission data of a tribological contact. The use of acoustic emission entails the problem of interpreting physical sources of signals. In this paper, we analyze the evolution of acoustic emission signal frames in friction of Hadfield steel single crystals. The chosen crystallographic orientation of single crystals enables to identify four stages related to friction development as well as acoustic emission signals inherent in these stages. Acoustic emission signal parameters are studied in more detail by the short-time Fourier transform used to determine the time variation of the median frequency and its power spectrum. The results obtained will facilitate the development of a more precise method to monitor the tribological contact based on the acoustic emission method.

Frequency Domain Analysis of Sensor Data for Event Classification in Real-Time Robot Assisted Deburring

PubMed Central

Pappachan, Bobby K; Caesarendra, Wahyu; Tjahjowidodo, Tegoeh; Wijaya, Tomi

2017-01-01

Process monitoring using indirect methods relies on the usage of sensors. Using sensors to acquire vital process related information also presents itself with the problem of big data management and analysis. Due to uncertainty in the frequency of events occurring, a higher sampling rate is often used in real-time monitoring applications to increase the chances of capturing and understanding all possible events related to the process. Advanced signal processing methods are used to further decipher meaningful information from the acquired data. In this research work, power spectrum density (PSD) of sensor data acquired at sampling rates between 40–51.2 kHz was calculated and the corelation between PSD and completed number of cycles/passes is presented. Here, the progress in number of cycles/passes is the event this research work intends to classify and the algorithm used to compute PSD is Welch’s estimate method. A comparison between Welch’s estimate method and statistical methods is also discussed. A clear co-relation was observed using Welch’s estimate to classify the number of cycles/passes. The paper also succeeds in classifying vibration signal generated by the spindle from the vibration signal acquired during finishing process. PMID:28556809

Multibeam Gpu Transient Pipeline for the Medicina BEST-2 Array

NASA Astrophysics Data System (ADS)

Magro, A.; Hickish, J.; Adami, K. Z.

2013-09-01

Radio transient discovery using next generation radio telescopes will pose several digital signal processing and data transfer challenges, requiring specialized high-performance backends. Several accelerator technologies are being considered as prototyping platforms, including Graphics Processing Units (GPUs). In this paper we present a real-time pipeline prototype capable of processing multiple beams concurrently, performing Radio Frequency Interference (RFI) rejection through thresholding, correcting for the delay in signal arrival times across the frequency band using brute-force dedispersion, event detection and clustering, and finally candidate filtering, with the capability of persisting data buffers containing interesting signals to disk. This setup was deployed at the BEST-2 SKA pathfinder in Medicina, Italy, where several benchmarks and test observations of astrophysical transients were conducted. These tests show that on the deployed hardware eight 20 MHz beams can be processed simultaneously for 640 Dispersion Measure (DM) values. Furthermore, the clustering and candidate filtering algorithms employed prove to be good candidates for online event detection techniques. The number of beams which can be processed increases proportionally to the number of servers deployed and number of GPUs, making it a viable architecture for current and future radio telescopes.

Digital Radar-Signal Processors Implemented in FPGAs

NASA Technical Reports Server (NTRS)

Berkun, Andrew; Andraka, Ray

2004-01-01

High-performance digital electronic circuits for onboard processing of return signals in an airborne precipitation- measuring radar system have been implemented in commercially available field-programmable gate arrays (FPGAs). Previously, it was standard practice to downlink the radar-return data to a ground station for postprocessing a costly practice that prevents the nearly-real-time use of the data for automated targeting. In principle, the onboard processing could be performed by a system of about 20 personal- computer-type microprocessors; relative to such a system, the present FPGA-based processor is much smaller and consumes much less power. Alternatively, the onboard processing could be performed by an application-specific integrated circuit (ASIC), but in comparison with an ASIC implementation, the present FPGA implementation offers the advantages of (1) greater flexibility for research applications like the present one and (2) lower cost in the small production volumes typical of research applications. The generation and processing of signals in the airborne precipitation measuring radar system in question involves the following especially notable steps: The system utilizes a total of four channels two carrier frequencies and two polarizations at each frequency. The system uses pulse compression: that is, the transmitted pulse is spread out in time and the received echo of the pulse is processed with a matched filter to despread it. The return signal is band-limited and digitally demodulated to a complex baseband signal that, for each pulse, comprises a large number of samples. Each complex pair of samples (denoted a range gate in radar terminology) is associated with a numerical index that corresponds to a specific time offset from the beginning of the radar pulse, so that each such pair represents the energy reflected from a specific range. This energy and the average echo power are computed. The phase of each range bin is compared to the previous echo by complex conjugate multiplication to obtain the mean Doppler shift (and hence the mean and variance of the velocity of precipitation) of the echo at that range.

EARLINET Single Calculus Chain - technical - Part 1: Pre-processing of raw lidar data

NASA Astrophysics Data System (ADS)

D'Amico, G.; Amodeo, A.; Mattis, I.; Freudenthaler, V.; Pappalardo, G.

2015-10-01

In this paper we describe an automatic tool for the pre-processing of lidar data called ELPP (EARLINET Lidar Pre-Processor). It is one of two calculus modules of the EARLINET Single Calculus Chain (SCC), the automatic tool for the analysis of EARLINET data. The ELPP is an open source module that executes instrumental corrections and data handling of the raw lidar signals, making the lidar data ready to be processed by the optical retrieval algorithms. According to the specific lidar configuration, the ELPP automatically performs dead-time correction, atmospheric and electronic background subtraction, gluing of lidar signals, and trigger-delay correction. Moreover, the signal-to-noise ratio of the pre-processed signals can be improved by means of configurable time integration of the raw signals and/or spatial smoothing. The ELPP delivers the statistical uncertainties of the final products by means of error propagation or Monte Carlo simulations. During the development of the ELPP module, particular attention has been payed to make the tool flexible enough to handle all lidar configurations currently used within the EARLINET community. Moreover, it has been designed in a modular way to allow an easy extension to lidar configurations not yet implemented. The primary goal of the ELPP module is to enable the application of quality-assured procedures in the lidar data analysis starting from the raw lidar data. This provides the added value of full traceability of each delivered lidar product. Several tests have been performed to check the proper functioning of the ELPP module. The whole SCC has been tested with the same synthetic data sets, which were used for the EARLINET algorithm inter-comparison exercise. The ELPP module has been successfully employed for the automatic near-real-time pre-processing of the raw lidar data measured during several EARLINET inter-comparison campaigns as well as during intense field campaigns.

ISLE (Image and Signal Processing LISP Environment) reference manual

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

Sherwood, R.J.; Searfus, R.M.

1990-01-01

ISLE is a rapid prototyping system for performing image and signal processing. It is designed to meet the needs of a person doing development of image and signal processing algorithms in a research environment. The image and signal processing modules in ISLE form a very capable package in themselves. They also provide a rich environment for quickly and easily integrating user-written software modules into the package. ISLE is well suited to applications in which there is a need to develop a processing algorithm in an interactive manner. It is straightforward to develop the algorithms, load it into ISLE, apply themore » algorithm to an image or signal, display the results, then modify the algorithm and repeat the develop-load-apply-display cycle. ISLE consists of a collection of image and signal processing modules integrated into a cohesive package through a standard command interpreter. ISLE developer elected to concentrate their effort on developing image and signal processing software rather than developing a command interpreter. A COMMON LISP interpreter was selected for the command interpreter because it already has the features desired in a command interpreter, it supports dynamic loading of modules for customization purposes, it supports run-time parameter and argument type checking, it is very well documented, and it is a commercially supported product. This manual is intended to be a reference manual for the ISLE functions The functions are grouped into a number of categories and briefly discussed in the Function Summary chapter. The full descriptions of the functions and all their arguments are given in the Function Descriptions chapter. 6 refs.« less

Sensor, signal, and image informatics - state of the art and current topics.

PubMed

Lehmann, T M; Aach, T; Witte, H

2006-01-01

The number of articles published annually in the fields of biomedical signal and image acquisition and processing is increasing. Based on selected examples, this survey aims at comprehensively demonstrating the recent trends and developments. Four articles are selected for biomedical data acquisition covering topics such as dose saving in CT, C-arm X-ray imaging systems for volume imaging, and the replacement of dose-intensive CT-based diagnostic with harmonic ultrasound imaging. Regarding biomedical signal analysis (BSA), the four selected articles discuss the equivalence of different time-frequency approaches for signal analysis, an application to Cochlea implants, where time-frequency analysis is applied for controlling the replacement system, recent trends for fusion of different modalities, and the role of BSA as part of a brain machine interfaces. To cover the broad spectrum of publications in the field of biomedical image processing, six papers are focused. Important topics are content-based image retrieval in medical applications, automatic classification of tongue photographs from traditional Chinese medicine, brain perfusion analysis in single photon emission computed tomography (SPECT), model-based visualization of vascular trees, and virtual surgery, where enhanced visualization and haptic feedback techniques are combined with a sphere-filled model of the organ. The selected papers emphasize the five fields forming the chain of biomedical data processing: (1) data acquisition, (2) data reconstruction and pre-processing, (3) data handling, (4) data analysis, and (5) data visualization. Fields 1 and 2 form the sensor informatics, while fields 2 to 5 form signal or image informatics with respect to the nature of the data considered. Biomedical data acquisition and pre-processing, as well as data handling, analysis and visualization aims at providing reliable tools for decision support that improve the quality of health care. Comprehensive evaluation of the processing methods and their reliable integration in routine applications are future challenges in the field of sensor, signal and image informatics.

Multimodal neuroelectric interface development

NASA Technical Reports Server (NTRS)

Trejo, Leonard J.; Wheeler, Kevin R.; Jorgensen, Charles C.; Rosipal, Roman; Clanton, Sam T.; Matthews, Bryan; Hibbs, Andrew D.; Matthews, Robert; Krupka, Michael

2003-01-01

We are developing electromyographic and electroencephalographic methods, which draw control signals for human-computer interfaces from the human nervous system. We have made progress in four areas: 1) real-time pattern recognition algorithms for decoding sequences of forearm muscle activity associated with control gestures; 2) signal-processing strategies for computer interfaces using electroencephalogram (EEG) signals; 3) a flexible computation framework for neuroelectric interface research; and d) noncontact sensors, which measure electromyogram or EEG signals without resistive contact to the body.

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

Application of the wavelet packet transform to vibration signals for surface roughness monitoring in CNC turning operations

NASA Astrophysics Data System (ADS)

García Plaza, E.; Núñez López, P. J.

2018-01-01

The wavelet packet transform method decomposes a time signal into several independent time-frequency signals called packets. This enables the temporary location of transient events occurring during the monitoring of the cutting processes, which is advantageous in monitoring condition and fault diagnosis. This paper proposes the monitoring of surface roughness using a single low cost sensor that is easily implemented in numerical control machine tools in order to make on-line decisions on workpiece surface finish quality. Packet feature extraction in vibration signals was applied to correlate the sensor signals to measured surface roughness. For the successful application of the WPT method, mother wavelets, packet decomposition level, and appropriate packet selection methods should be considered, but are poorly understood aspects in the literature. In this novel contribution, forty mother wavelets, optimal decomposition level, and packet reduction methods were analysed, as well as identifying the effective frequency range providing the best packet feature extraction for monitoring surface finish. The results show that mother wavelet biorthogonal 4.4 in decomposition level L3 with the fusion of the orthogonal vibration components (ax + ay + az) were the best option in the vibration signal and surface roughness correlation. The best packets were found in the medium-high frequency DDA (6250-9375 Hz) and high frequency ADA (9375-12500 Hz) ranges, and the feed acceleration component ay was the primary source of information. The packet reduction methods forfeited packets with relevant features to the signal, leading to poor results for the prediction of surface roughness. WPT is a robust vibration signal processing method for the monitoring of surface roughness using a single sensor without other information sources, satisfactory results were obtained in comparison to other processing methods with a low computational cost.

Method and system for photoconductive detector signal correction

DOEpatents

Carangelo, Robert M.; Hamblen, David G.; Brouillette, Carl R.

1992-08-04

A corrective factor is applied so as to remove anomalous features from the signal generated by a photoconductive detector, and to thereby render the output signal highly linear with respect to the energy of incident, time-varying radiation. The corrective factor may be applied through the use of either digital electronic data processing means or analog circuitry, or through a combination of those effects.

Method and system for photoconductive detector signal correction

DOEpatents

Carangelo, R.M.; Hamblen, D.G.; Brouillette, C.R.

1992-08-04

A corrective factor is applied so as to remove anomalous features from the signal generated by a photoconductive detector, and to thereby render the output signal highly linear with respect to the energy of incident, time-varying radiation. The corrective factor may be applied through the use of either digital electronic data processing means or analog circuitry, or through a combination of those effects. 5 figs.

Method of Laser Vibration Defect Analysis

DTIC Science & Technology

2010-06-04

415. In one embodiment, the frequencies from the reflected ultrasonic wave 430 are sensed and transformed to an electrical signal by transducer...actuator and sensor patches, respectively. Then, a process module loads sensor signal data to identify wave modes, determine the time of arrival of...conditions. An interrogation system includes at least one wave generator for generating a wave signal and optical fiber sensors applied to a structure

Real-time optical signal processors employing optical feedback: amplitude and phase control.

PubMed

Gallagher, N C

1976-04-01

The development of real-time coherent optical signal processors has increased the appeal of optical computing techniques in signal processing applications. A major limitation of these real-time systems is the. fact that the optical processing material is generally of a phase-only type. The result is that the spatial filters synthesized with these systems must be either phase-only filters or amplitude-only filters. The main concern of this paper is the application of optical feedback techniques to obtain simultaneous and independent amplitude and phase control of the light passing through the system. It is shown that optical feedback techniques may be employed with phase-only spatial filters to obtain this amplitude and phase control. The feedback system with phase-only filters is compared with other feedback systems that employ combinations of phase-only and amplitude-only filters; it is found that the phase-only system is substantially more flexible than the other two systems investigated.

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

NASA Astrophysics Data System (ADS)

Wang, Yuhua; Cheng, Xiang; Tan, Haishu

2016-01-01

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

A non-contact method based on multiple signal classification algorithm to reduce the measurement time for accurately heart rate detection

NASA Astrophysics Data System (ADS)

Bechet, P.; Mitran, R.; Munteanu, M.

2013-08-01

Non-contact methods for the assessment of vital signs are of great interest for specialists due to the benefits obtained in both medical and special applications, such as those for surveillance, monitoring, and search and rescue. This paper investigates the possibility of implementing a digital processing algorithm based on the MUSIC (Multiple Signal Classification) parametric spectral estimation in order to reduce the observation time needed to accurately measure the heart rate. It demonstrates that, by proper dimensioning the signal subspace, the MUSIC algorithm can be optimized in order to accurately assess the heart rate during an 8-28 s time interval. The validation of the processing algorithm performance was achieved by minimizing the mean error of the heart rate after performing simultaneous comparative measurements on several subjects. In order to calculate the error the reference value of heart rate was measured using a classic measurement system through direct contact.

Method and apparatus for combinatorial logic signal processor in a digitally based high speed x-ray spectrometer

DOEpatents

Warburton, William K.; Zhou, Zhiquing

1999-01-01

A high speed, digitally based, signal processing system which accepts a digitized input signal and detects the presence of step-like pulses in the this data stream, extracts filtered estimates of their amplitudes, inspects for pulse pileup, and records input pulse rates and system livetime. The system has two parallel processing channels: a slow channel, which filters the data stream with a long time constant trapezoidal filter for good energy resolution; and a fast channel which filters the data stream with a short time constant trapezoidal filter, detects pulses, inspects for pileups, and captures peak values from the slow channel for good events. The presence of a simple digital interface allows the system to be easily integrated with a digital processor to produce accurate spectra at high count rates and allow all spectrometer functions to be fully automated. Because the method is digitally based, it allows pulses to be binned based on time related values, as well as on their amplitudes, if desired.

Fast contactless vibrating structure characterization using real time field programmable gate array-based digital signal processing: demonstrations with a passive wireless acoustic delay line probe and vision.

PubMed

Goavec-Mérou, G; Chrétien, N; Friedt, J-M; Sandoz, P; Martin, G; Lenczner, M; Ballandras, S

2014-01-01

Vibrating mechanical structure characterization is demonstrated using contactless techniques best suited for mobile and rotating equipments. Fast measurement rates are achieved using Field Programmable Gate Array (FPGA) devices as real-time digital signal processors. Two kinds of algorithms are implemented on FPGA and experimentally validated in the case of the vibrating tuning fork. A first application concerns in-plane displacement detection by vision with sampling rates above 10 kHz, thus reaching frequency ranges above the audio range. A second demonstration concerns pulsed-RADAR cooperative target phase detection and is applied to radiofrequency acoustic transducers used as passive wireless strain gauges. In this case, the 250 ksamples/s refresh rate achieved is only limited by the acoustic sensor design but not by the detection bandwidth. These realizations illustrate the efficiency, interest, and potentialities of FPGA-based real-time digital signal processing for the contactless interrogation of passive embedded probes with high refresh rates.

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