Science.gov

Sample records for signal processing correlation

  1. Correlation theory-based signal processing method for CMF signals

    NASA Astrophysics Data System (ADS)

    Shen, Yan-lin; Tu, Ya-qing

    2016-06-01

    Signal processing precision of Coriolis mass flowmeter (CMF) signals affects measurement accuracy of Coriolis mass flowmeters directly. To improve the measurement accuracy of CMFs, a correlation theory-based signal processing method for CMF signals is proposed, which is comprised of the correlation theory-based frequency estimation method and phase difference estimation method. Theoretical analysis shows that the proposed method eliminates the effect of non-integral period sampling signals on frequency and phase difference estimation. The results of simulations and field experiments demonstrate that the proposed method improves the anti-interference performance of frequency and phase difference estimation and has better estimation performance than the adaptive notch filter, discrete Fourier transform and autocorrelation methods in terms of frequency estimation and the data extension-based correlation, Hilbert transform, quadrature delay estimator and discrete Fourier transform methods in terms of phase difference estimation, which contributes to improving the measurement accuracy of Coriolis mass flowmeters.

  2. 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.

  3. 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.

  4. Optical signal processing - Fourier transforms and convolution/correlation

    NASA Astrophysics Data System (ADS)

    Rhodes, William T.

    The application of Fourier techniques and linear-systems theory to the analysis and synthesis of optical systems is described in a theoretical review, and Fourier-based optical signal-processing methods are considered. Topics examined include monochromatic wave fields and their phasor representation, wave propagation, Fourier-transform and spectrum analysis with a spherical lens, coherent and incoherent imaging and spatial filtering, and a channelized spectrum analyzer (using both spherical and cylindrical lenses) for multiple one-dimensional input signals.

  5. Signals of strong electronic correlation in ion scattering processes

    NASA Astrophysics Data System (ADS)

    Bonetto, F.; Gonzalez, C.; Goldberg, E. C.

    2016-05-01

    Previous measurements of neutral atom fractions for S r+ scattered by gold polycrystalline surfaces show a singular dependence with the target temperature. There is still not a theoretical model that can properly describe the magnitude and the temperature dependence of the neutralization probabilities found. Here, we applied a first-principles quantum-mechanical theoretical formalism to describe the time-dependent scattering process. Three different electronic correlation approaches consistent with the system analyzed are used: (i) the spinless approach, where two charge channels are considered (S r0 and S r+ ) and the spin degeneration is neglected; (ii) the infinite-U approach, with the same charge channels (S r0 and S r+ ) but considering the spin degeneration; and (iii) the finite-U approach, where the first ionization and second ionization energy levels are considered very, but finitely, separated. Neutral fraction magnitudes and temperature dependence are better described by the finite-U approach, indicating that e -correlation plays a significant role in charge-transfer processes. However, none of them is able to explain the nonmonotonous temperature dependence experimentally obtained. Here, we suggest that small changes in the surface work function introduced by the target heating, and possibly not detected by experimental standard methods, could be responsible for that singular behavior. Additionally, we apply the same theoretical model using the infinite-U approximation for the Mg-Au system, obtaining an excellent description of the experimental neutral fractions measured.

  6. Study of photon correlation techniques for processing of laser velocimeter signals

    NASA Technical Reports Server (NTRS)

    Mayo, W. T., Jr.

    1977-01-01

    The objective was to provide the theory and a system design for a new type of photon counting processor for low level dual scatter laser velocimeter (LV) signals which would be capable of both the first order measurements of mean flow and turbulence intensity and also the second order time statistics: cross correlation auto correlation, and related spectra. A general Poisson process model for low level LV signals and noise which is valid from the photon-resolved regime all the way to the limiting case of nonstationary Gaussian noise was used. Computer simulation algorithms and higher order statistical moment analysis of Poisson processes were derived and applied to the analysis of photon correlation techniques. A system design using a unique dual correlate and subtract frequency discriminator technique is postulated and analyzed. Expectation analysis indicates that the objective measurements are feasible.

  7. Modified Multilook Cross Correlation technique for Doppler centroid estimation in SAR image signal processing

    NASA Astrophysics Data System (ADS)

    Bee Cheng, Sew

    Synthetic Aperture Radar (SAR) is one of the widely used remote sensing sensors which produces high resolution image by using advance signal processing technique. SAR managed to operate in all sorts of weather and cover wide range of area. To produce a high-quality image, accurate parameters such as Doppler centroid are required for precise SAR signal processing. In the azimuth matched filtering of SAR signal processing, Doppler centroid is an important azimuth parameter that helps to focus the image pixels. Doppler centroid has always been overlooked during SAR signal processing. It is due to the fact that estimation of Doppler centroid involved complicated calculation and increased computational load. Therefore, researcher used to apply only the approximate Doppler value which is not precise and cause defocus effort in the generated SAR image. In this study, several conventional Doppler centroid estimation algorithms are reviewed and developed using Matlab software program to extract the Doppler parameter from received SAR data, namely Spectrum Fit Algorithm, Wavelength Diversity Algorithm (WDA), Multilook Cross Correlation Algorithm (MLCC), and Multilook Beat Frequency Algorithm (MLBF). Two sets of SAR data are employed to evaluate the performance of each estimator, i.e. simulated point target data and RADARSAT-1 Vancouver scene raw data. These experiments gave a sense of accuracy for the estimated results together with computational time consumption. Point target is simulated to generate ideal case SAR data with pre-defined SAR system parameters.

  8. Digital Signal Processing Using Stream High Performance Computing: A 512-Input Broadband Correlator for Radio Astronomy

    NASA Astrophysics Data System (ADS)

    Kocz, J.; Greenhill, L. J.; Barsdell, B. R.; Price, D.; Bernardi, G.; Bourke, S.; Clark, M. A.; Craig, J.; Dexter, M.; Dowell, J.; Eftekhari, T.; Ellingson, S.; Hallinan, G.; Hartman, J.; Jameson, A.; MacMahon, D.; Taylor, G.; Schinzel, F.; Werthimer, D.

    2015-03-01

    A "large-N" correlator that makes use of Field Programmable Gate Arrays and Graphics Processing Units has been deployed as the digital signal processing system for the Long Wavelength Array station at Owens Valley Radio Observatory (LWA-OV), to enable the Large Aperture Experiment to Detect the Dark Ages (LEDA). The system samples a ˜ 100 MHz baseband and processes signals from 512 antennas (256 dual polarization) over a ˜ 58 MHz instantaneous sub-band, achieving 16.8 Tops s-1 and 0.236 Tbit s-1 throughput in a 9 kW envelope and single rack footprint. The output data rate is 260 MB s-1 for 9-s time averaging of cross-power and 1 s averaging of total power data. At deployment, the LWA-OV correlator was the largest in production in terms of N and is the third largest in terms of complex multiply accumulations, after the Very Large Array and Atacama Large Millimeter Array. The correlator's comparatively fast development time and low cost establish a practical foundation for the scalability of a modular, heterogeneous, computing architecture.

  9. Cross-Correlation: An fMRI Signal-Processing Strategy

    PubMed Central

    Hyde, James S.; Jesmanowicz, Andrzej

    2011-01-01

    The discovery of functional MRI (fMRI), with the first papers appearing in 1992, gave rise to new categories of data that drove the development of new signal-processing strategies. Workers in the field were confronted with image time courses, which could be reshuffled to form pixel time courses. The waveform in an active pixel time-course was determined not only by the task sequence but also by the hemodynamic response function. Reference waveforms could be cross-correlated with pixel time courses to form an array of cross-correlation coefficients. From this array of numbers, colorized images could be created and overlaid on anatomical images. An early paper from the authors’ laboratory is extensively reviewed here (Bandettini et al. 1993. Magn. Reson. Med. 30:161–173). That work was carried out using the vocabulary of vector algebra. Cross-correlation methodology was central to the discovery of functional connectivity MRI (fcMRI) by Biswal et al. (1995. Magn. Reson. Med. 34:537–541). In this method, a whole volume time course of images is collected while the brain is nominally at rest and connectivity is studied by cross-correlation of pixel time courses. PMID:22051223

  10. Optical signal processing

    NASA Technical Reports Server (NTRS)

    Casasent, D.

    1978-01-01

    The article discusses several optical configurations used for signal processing. Electronic-to-optical transducers are outlined, noting fixed window transducers and moving window acousto-optic transducers. Folded spectrum techniques are considered, with reference to wideband RF signal analysis, fetal electroencephalogram analysis, engine vibration analysis, signal buried in noise, and spatial filtering. Various methods for radar signal processing are described, such as phased-array antennas, the optical processing of phased-array data, pulsed Doppler and FM radar systems, a multichannel one-dimensional optical correlator, correlations with long coded waveforms, and Doppler signal processing. Means for noncoherent optical signal processing are noted, including an optical correlator for speech recognition and a noncoherent optical correlator.

  11. An adaptive line enhancement method for UWB proximity fuze signal processing based on correlation matrix estimation with time delay factor

    NASA Astrophysics Data System (ADS)

    Li, Meng; Huang, Zhonghua

    2016-10-01

    Signal processing for an ultra-wideband radio fuze receiver involves some challenges: it requires high real-time performance; the output signal is mixed with broadband noise; and the signal-to-noise ratio (SNR) decreases with increased detection range. The adaptive line enhancement method is used to filter the output signal of the ultra-wideband radio fuze receiver, and thus suppress the wideband noise from the output signal of the receiver and extract the target characteristic signal. The filter input correlation matrix estimation algorithm is based on the delay factor of an adaptive line enhancer. The proposed adaptive algorithm was used to filter and reduce noise in the output signal from the fuze receiver. Simulation results showed that the SNR of the output signal after adaptive noise reduction was improved by 20 dB, which was higher than the SNR of the output signal after finite impulse response (FIR) filtering of around 10 dB.

  12. Signal Processing

    DTIC Science & Technology

    1989-03-01

    ORGANIZATION Univ of Minnesota (f*fto U. S. Army Research Office 6c. ADDRESS (City, State, and ZIP Code) 7b. ADDRESS (Wiy Stat, and ZIP Code...Minneapolis, MN 55455 P. 0. Box 12211 Research Triangle Park, NC 27709-2211 Sa. NAME Of FUNDING ISPONSORING Sb. OFFICE SYMBOL 9. PROCUREMENT INSTRUMENT...PROJECT ITASK jWORK UNIT Research Triangle Park, NC 27709-2211 EMNTO.I NO NO CESOIO 11. TITLE (Incudt Security Classifiratio") Signal Processing of, he auth

  13. Signal processing

    NASA Astrophysics Data System (ADS)

    Norman, David M.

    The application of signal processing technology to conventional weapons systems can lower operator workloads and enhance kill probabilities, while automating wide-area surveillance, target search and classification, target tracking, and aimpoint selection. Immediate opportunities exist for automatic target cueing in underwater and over-the-horizon targeting, as well as for airborne multiple-target fire control. By embedding the transit/receive electronics into conformal aircraft sensor arrays, a 'smart' skin can be created. Electronically scanned phased arrays can be used to yield accurate azimuthal and elevation positions while nullifying EW threats. Attention is given to major development thrusts in algorithm design.

  14. Multigigahertz range-Doppler correlative signal processing in optical memory crystals.

    PubMed

    Harris, Todd L; Merkel, Kristian D; Mohan, R Krishna; Chang, Tiejun; Cole, Zachary; Olson, Andy; Babbitt, Wm Randall

    2006-01-10

    Analog optical signal processing of complex radio-frequency signals for range-Doppler radar information is theoretically described and experimentally demonstrated using crystalline optical memory materials and off-the-shelf photonic components. A model of the range-Doppler processing capability of the memory material for the case of single-target detection is presented. Radarlike signals were emulated and processed by the memory material; they consisted of broadband (> 1 GHz), spread-spectrum, pseudorandom noise sequences of 512 bits in length, which were binary phase-shift keyed on a 1.9 GHz carrier and repeated at 100 kHz over 7.5 ms. Delay (range) resolution of 8 ns and Doppler resolution of 130 Hz over 100 kHz were demonstrated.

  15. Automatic parameter optimization in epsilon-filter for acoustical signal processing utilizing correlation coefficient.

    PubMed

    Abe, Tomomi; Hashimoto, Shuji; Matsumoto, Mitsuharu

    2010-02-01

    epsilon-filter can reduce most kinds of noise from a single-channel noisy signal while preserving signals that vary drastically such as speech signals. It can reduce not only stationary noise but also nonstationary noise. However, it has some parameters whose values are set empirically. So far, there have been few studies to evaluate the appropriateness of the parameter settings for epsilon-filter. This paper employs the correlation coefficient of the filter output and the difference between the filter input and output as the evaluation function of the parameter setting. This paper also describes the algorithm to set the optimal parameter value of epsilon-filter automatically. To evaluate the adequateness of the obtained parameter, the mean absolute error is calculated. The experimental results show that the adequate parameter in epsilon-filter can be obtained automatically by using the proposed method.

  16. A signal processing method based on a homotopic correlation product applied to speech recognition problems

    NASA Astrophysics Data System (ADS)

    Bianchi, F.; Pocci, P.; Prina-Ricotti, L.

    1981-02-01

    The assumptions used to formulate the processing method, the proposed algorithm, and phoneme recognition test results of a homotopic signal processing method are presented. The hearing system is considered as a box with one imput, that applies a signal whose information content = 500 Kbit/sec, and many thousand outputs, the nerve fibers, having a transmission rate variable between 30 and 400 bit/sec. The signal transmitted by any one fiber is a series of equal impulse. Homotopic representation of a phoneme is available in steady state after 2 to 3 msec. The phoneme patterns are very different, although patterns for the same phoneme from different speakers are similar. Transition patterns between phonemes change rapidly. Recognition rate, using a minicomputer, of all possible combinations of 'a', 'e', 'r' and 'm' is 95.2%.

  17. Performance analysis and acceleration of cross-correlation computation using FPGA implementation for digital signal processing

    NASA Astrophysics Data System (ADS)

    Selma, R.

    2016-09-01

    Paper describes comparison of cross-correlation computation speed of most commonly used computation platforms (CPU, GPU) with an FPGA-based design. It also describes the structure of cross-correlation unit implemented for testing purposes. Speedup of computations was achieved using FPGA-based design, varying between 16 and 5400 times compared to CPU computations and between 3 and 175 times compared to GPU computations.

  18. Acoustic Signal Processing

    NASA Astrophysics Data System (ADS)

    Hartmann, William M.; Candy, James V.

    Signal processing refers to the acquisition, storage, display, and generation of signals - also to the extraction of information from signals and the re-encoding of information. As such, signal processing in some form is an essential element in the practice of all aspects of acoustics. Signal processing algorithms enable acousticians to separate signals from noise, to perform automatic speech recognition, or to compress information for more efficient storage or transmission. Signal processing concepts are the building blocks used to construct models of speech and hearing. Now, in the 21st century, all signal processing is effectively digital signal processing. Widespread access to high-speed processing, massive memory, and inexpensive software make signal processing procedures of enormous sophistication and power available to anyone who wants to use them. Because advanced signal processing is now accessible to everybody, there is a need for primers that introduce basic mathematical concepts that underlie the digital algorithms. The present handbook chapter is intended to serve such a purpose.

  19. Signal Processing, Analysis, & Display

    SciTech Connect

    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 signals 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.

  20. Digital signal processing

    NASA Astrophysics Data System (ADS)

    Oppenheim, A. V.; Baggeroer, A. B.; Lim, J. S.; Musicus, B. R.; Mook, D. R.; Duckworth, G. L.; Bordley, T. E.; Curtis, S. R.; Deadrick, D. S.; Dove, W. P.

    1984-01-01

    Signal and image processing research projects are described. Topics include: (1) modeling underwater acoustic propagation; (2) image restoration; (3) signal reconstruction; (4) speech enhancement; (5) pitch detection; (6) spectral analysis; (7) speech synthesis; (8) speech enhancement; (9) autoregressive spectral estimation; (10) knowledge based array processing; (11) speech analysis; (12) estimating the degree of coronary stenosis with image processing; (13) automatic target detection; and (14) video conferencing.

  1. High-resolution optical refractometer based on a long-period grating Michelson interferometer using a cross-correlation signal-processing method

    NASA Astrophysics Data System (ADS)

    Zhou, Xinlei; Chen, Ke; Mao, Xuefeng; Peng, Wei; Yu, Qingxu

    2015-12-01

    We report a high-resolution optical refractometer based on the long-period grating Michelson interferometer. The interferometer phase shift depends on the refractive index that surrounds the fiber probe. A cross-correlation signal-processing method is used to demodulate the interferometer phase shift. Experimental results show that a resolution of 3×10-6 refractive index unit (RIU) can be obtained using this cross-correlation signal processing method. In addition, a measurement sensitivity up to 3×103 deg/RIU is showed as the surrounding refractive index changing from 1.33 to 1.42. Such high-resolution and low-cost optical refractometers would find more applications in chemical or biochemical sensing fields.

  2. Array signal processing

    SciTech Connect

    Haykin, S.; Justice, J.H.; Owsley, N.L.; Yen, J.L.; Kak, A.C.

    1985-01-01

    This is the first book to be devoted completely to array signal processing, a subject that has become increasingly important in recent years. The book consists of six chapters. Chapter 1, which is introductory, reviews some basic concepts in wave propagation. The remaining five chapters deal with the theory and applications of array signal processing in (a) exploration seismology, (b) passive sonar, (c) radar, (d) radio astronomy, and (e) tomographic imaging. The various chapters of the book are self-contained. The book is written by a team of five active researchers, who are specialists in the individual fields covered by the pertinent chapters.

  3. Correlation between the shape of the ion mobility signals and the stepwise folding process of polylactide ions.

    PubMed

    Duez, Q; Josse, T; Lemaur, V; Chirot, F; Choi, C M; Dubois, P; Dugourd, P; Cornil, J; Gerbaux, P; De Winter, J

    2017-03-01

    In the field of polymer characterization, the use of ion mobility mass spectrometry (IMMS) remains mainly devoted to the temporal separation of cationized oligomers according to their charge states, molecular masses and macromolecular architectures in order to probe the presence of different structures. When analyzing multiply charged polymer ions by IMMS, the most striking feature is the observation of breaking points in the evolution of the average collision cross sections with the number of monomer units. Those breaking points are associated to the folding of the polymer chain around the cationizing agents. Here, we scrutinize the shape of the arrival time distribution (ATD) of polylactide ions and associate the broadening as well as the loss of symmetry of the ATD signals to the coexistence of different populations of ions attributed to the transition from opened to folded stable structures. The observation of distinct distributions reveals the absence of folded/extended structure interconversion on the ion mobility time scale (1-10 ms) and then on the lifetime of ions within the mass spectrometer at room temperature. In order to obtain information on the possible interconversion between the different observed populations upon ion activation, we performed IM-IM-MS experiments (tandem ion mobility measurements). To do so, mobility-selected ions were activated by collisions before a second mobility measurement. Interestingly, the conversion by collisional activation from a globular structure into a (partially) extended structure, i.e. the gas phase unfolding of the ions, was not observed in the energetic regime available with the used experimental setup. The absence of folded/extended interconversion, even upon collisional activation, points to the fact that the polylactide ions are 'frozen' in their specific 3D structure during the desolvation/ionization electrospray processes. Copyright © 2017 John Wiley & Sons, Ltd.

  4. Microsystem for signal processing applications

    NASA Astrophysics Data System (ADS)

    Frankenstein, B.; Froehlich, K.-J.; Hentschel, D.; Reppe, G.

    2005-05-01

    Acoustic monitoring of technological processes requires methods that eliminate noise as much as possible. Sensor-near signal evaluation can contribute substantially. Frequently, a further necessity exists to integrate the measuring technique in the monitored structure. The solution described contains components for analog preprocessing of acoustic signals, their digitization, algorithms for data reduction, and digital communication. The core component is a digital signal processor (DSP). Digital signal processors perform the algorithms necessary for filtering, down sampling, FFT computation and correlation of spectral components particularly effective. A compact, sensor-near signal processing structure was realized. It meets the Match-X standard, which as specified by the German Association for Mechanical and Plant Engineering (VDMA) for development of micro-technical modules, which can be combined to applicaiton specific systems. The solution is based on AL2O3 ceramic components including different signal processing modules as ADC, as well as memory and power supply. An arbitrary waveform generator has been developed and combined with a power amplifier for piezoelectric transducers in a special module. A further module interfaces to these transducers. It contains a multi-channel preamplifier, some high-pass filters for analog signal processing and an ADC-driver. A Bluetooth communication chip for wireless data transmission and a DiscOnChip module are under construction. As a first application, the combustion behavior of safety-relevant contacts is monitored. A special waveform up to 5MHz is produced and sent to the monitored object. The resulting signal form is evaluated with special algorithms, which extract significant parameters of the signal, and transmitted via CAN-bus.

  5. Telemetry Ranging: Signal Processing

    NASA Astrophysics Data System (ADS)

    Hamkins, J.; Kinman, P.; Xie, H.; Vilnrotter, V.; Dolinar, S.

    2016-02-01

    This article describes the details of the signal processing used in a telemetry ranging system in which timing information is extracted from the downlink telemetry signal in order to compute spacecraft range. A previous article describes telemetry ranging concepts and architecture, which are a slight variation of a scheme published earlier. As in that earlier work, the telemetry ranging concept eliminates the need for a dedicated downlink ranging signal to communicate the necessary timing information. The present article describes the operation and performance of the major receiver functions on the spacecraft and the ground --- many of which are standard tracking loops already in use in JPL's flight and ground radios --- and how they can be used to provide the relevant information for making a range measurement. It also describes the implementation of these functions in software, and performance of an end-to-end software simulation of the telemetry ranging system.

  6. Adaptive Signal Processing Testbed

    NASA Astrophysics Data System (ADS)

    Parliament, Hugh A.

    1991-09-01

    The design and implementation of a system for the acquisition, processing, and analysis of signal data is described. The initial application for the system is the development and analysis of algorithms for excision of interfering tones from direct sequence spread spectrum communication systems. The system is called the Adaptive Signal Processing Testbed (ASPT) and is an integrated hardware and software system built around the TMS320C30 chip. The hardware consists of a radio frequency data source, digital receiver, and an adaptive signal processor implemented on a Sun workstation. The software components of the ASPT consists of a number of packages including the Sun driver package; UNIX programs that support software development on the TMS320C30 boards; UNIX programs that provide the control, user interaction, and display capabilities for the data acquisition, processing, and analysis components of the ASPT; and programs that perform the ASPT functions including data acquisition, despreading, and adaptive filtering. The performance of the ASPT system is evaluated by comparing actual data rates against their desired values. A number of system limitations are identified and recommendations are made for improvements.

  7. Multipoint multirate signal processing

    NASA Astrophysics Data System (ADS)

    Claypoole, Roger L., Jr.

    1994-12-01

    This thesis provides a fundamentally new, systematic study of multipoint multirate signal processing systems. The multipoint multirate operators are analyzed via equivalent circuits comprised entirely of conventional multirate operators. Interconnections of the operators are demonstrated, and the multipoint noble identities are derived. The multipoint polyphase representation is presented, and the M channel multipoint multirate system with vector length N is presented as an MN channel multipoint polyphase system. The conditions sufficient for perfect reconstruction in the multipoint multirate system are derived. These conditions constrain the multipoint filter banks to be composed of comb filters generated from paraunitary sets of conventional filters. The perfect reconstruction multipoint multirate system is then combined with the multiresolution wavelet decomposition to form the generalized wavelet decomposition with varying vector decimation length at each level. The generalized wavelet decomposition is used as an algorithm to redistribute the energy of a signal throughout the levels of the decomposition. It is shown that, for band pass and high pass signals, significant improvements can be made in the energy distribution. It is recommended that this algorithm be studied as a front end to a vector quantizer for data compression applications.

  8. [Signal Processing Suite Design

    NASA Technical Reports Server (NTRS)

    Sahr, John D.; Mir, Hasan; Morabito, Andrew; Grossman, Matthew

    2003-01-01

    Our role in this project was to participate in the design of the signal processing suite to analyze plasma density measurements on board a small constellation (3 or 4) satellites in Low Earth Orbit. As we are new to space craft experiments, one of the challenges was to simply gain understanding of the quantity of data which would flow from the satellites, and possibly to interact with the design teams in generating optimal sampling patterns. For example, as the fleet of satellites were intended to fly through the same volume of space (displaced slightly in time and space), the bulk plasma structure should be common among the spacecraft. Therefore, an optimal, limited bandwidth data downlink would take advantage of this commonality. Also, motivated by techniques in ionospheric radar, we hoped to investigate the possibility of employing aperiodic sampling in order to gain access to a wider spatial spectrum without suffering aliasing in k-space.

  9. Neural Network Communications Signal Processing

    DTIC Science & Technology

    1994-08-01

    This final technical report describes the research and development- results of the Neural Network Communications Signal Processing (NNCSP) Program...The objectives of the NNCSP program are to: (1) develop and implement a neural network and communications signal processing simulation system for the...purpose of exploring the applicability of neural network technology to communications signal processing; (2) demonstrate several configurations of the

  10. Multifunction nonlinear signal processor - Deconvolution and correlation

    NASA Astrophysics Data System (ADS)

    Javidi, Bahram; Horner, Joseph L.

    1989-08-01

    A multifuncional nonlinear optical signal processor is described that allows different types of operations, such as image deconvolution and nonlinear correlation. In this technique, the joint power spectrum of the input signal is thresholded with varying nonlinearity to produce different specific operations. In image deconvolution, the joint power spectrum is modified and hard-clip thresholded to remove the amplitude distortion effects and to restore the correct phase of the original image. In optical correlation, the Fourier transform interference intensity is thresholded to provide higher correlation peak intensity and a better-defined correlation spot. Various types of correlation signals can be produced simply by varying the severity of the nonlinearity, without the need for synthesis of specific matched filter. An analysis of the nonlinear processor for image deconvolution is presented.

  11. An ultrasonic pseudorandom signal-correlation system

    NASA Astrophysics Data System (ADS)

    Elias, C. M.

    1980-01-01

    A working ultrasonic pseudorandom signal-correlation system is described which, unlike ultrasonic random signal-correlation systems, does not require an acoustic delay line. Elimination of the delay line allows faster data acquisition and better range resolution. The system uses two identical shift-register type generators to produce pseudonoise bursts which are subsequences of a 65 535-bit complementary m-sequence. One generator produces the transmitted bursts while the other generates identical reference bursts which start at a variable correlation delay time after the transmitted bursts. The reference bursts are cross-correlated with the received echoes to obtain the approximate impulse response of the transducer/specimen system under test. Range sidelobes are reduced by transmitting and correlating many bursts at a given correlation delay before incrementing the delay. Signal-to-sidelobe ratios of greater than 47 dB have been obtained using this method. Limitations of the system due to sampling constraints and the pseudonoise power spectrum are discussed, and the system design and implementation are outlined. Results of experimental characterization of the system show that the pseudorandom signal-correlation system has approximately the same range resolution as a conventional pulse-echo system but can yield a significant increase in signal-to-noise ratio (SNR).

  12. Optical Signal Processing

    DTIC Science & Technology

    1990-02-28

    compatible with the laser cation in the on-line inspection of products such as source. Thus, if the laser wavelength is z850 nm, hypodermic needles ...content for cw signals, short pulse signals, and evolving pulse signals - - the most difficult ones to analyze. We performed an extensive analysis on a...agreer.nt with the theory , and support our claims concerning the high performance level of our acousto-optir. architecture. We recognized the opportunity to

  13. Multidimensional signal processing for ultrasonic signal classification

    NASA Astrophysics Data System (ADS)

    Kim, J.; Ramuhalli, P.; Udpa, L.; Udpa, S.

    2001-04-01

    Neural network based signal classification systems are being used increasingly in the analysis of large volumes of data obtained in NDE applications. One example is in the interpretation on ultrasonic signals obtained from inspection of welds where signals can be due to porosity, slag, lack of fusion and cracks in the weld region. Standard techniques rely on differences in individual A-scans to classify the signals. This paper proposes an ultrasonic signal classification technique based on the information in a group of signals and examining the statistical characteristics of the signals. The method was 2-dimensional signal processing algorithms to analyze the information in B- and B'-scan images. In this paper, 2-dimensional transform based coefficients of the images are used as features and a multilayer perceptron is used to classify them. These results are then combined to get the final classification for the inspected region. Results of applying the technique to data obtained from the inspection of welds are presented.

  14. Optimum combining of residual carrier array signals in correlated noises

    NASA Technical Reports Server (NTRS)

    Liang, R.; Suen, P. H.; Tan, H. H.

    1996-01-01

    An array feed combining system for the recovery of signal-to-noise ratio (SNR) loss due to antenna reflector deformation has been implemented and is currently being evaluated on the Jet Propulsion Laboratory 34-m DSS-13 antenna. The current signal-combining system operates under the assumption that the white Gaussian noise processes in the received signals from different array elements are mutually uncorrelated. However, experimental data at DSS 13 indicate that these noise processes are indeed mutually correlated. The objective of this work is to develop a signal-combining system optimized to account for the mutual correlations between these noise processes. The set of optimum combining weight coefficients that maximizes the combined signal SNR in the correlated noises environment is determined. These optimum weights depend on unknown signal and noise covariance parameters. A maximum-likelihood approach is developed to estimate these unknown parameters to obtain estimates of the optimum weight coefficients based on residual carrier signal samples. The actual combined signal SNR using the estimated weight coefficients is derived and shown to converge to the maximum achievable SNR as the number of signal samples increases. These results are also verified by simulation. A numerical example shows a significant improvement in SNR performance can be obtained, especially when the amount of correlation increases.

  15. Optimum Combining of Residual Carrier Array Signals in Correlated Noises

    NASA Technical Reports Server (NTRS)

    Tan, H. H.; Liang, R.; Suen, P.-H.

    1996-01-01

    An array feed combining system for the recovery of signal-to-noise ratio (SNR) loss due to antenna reflector deformation has been implemented and is currently being evaluated on the Jet Propulsion Laboratory 34-m DSS-13 antenna. The current signal-combining system operates under the assumption that the white Gaussian noise processes in the received signals from different array elements are mutually uncorrelated. However, experimental data at DSS 13 indicate that these noise processes are indeed mutually correlated. The objective of this work is to develop a signal-combining system optimized to account for the mutual correlations between these noise processes. The set of optimum combining weight coefficients that maximizes the combined signal SNR in the correlated noises environment is determined. These optimum weights depend on unknown signal and noise covariance parameters. A maximum-likelihood approach is developed to estimate these unknown parameters to obtain estimates of the optimum weight coefficients based on residual carrier signal samples. The actual combined signal SNR using the estimated weight coefficients is derived and shown to converge to the maximum achievable SNR as the number of signal samples increases. These results are also verified by simulation. A numerical example shows a significant improvement in SNR performance can be obtained, especially when the amount of correlation increases.

  16. Signal processing in SETI

    NASA Technical Reports Server (NTRS)

    Cullers, D. K.; Linscott, I. R.; Oliver, B. M.

    1985-01-01

    It is believed that the Galaxy might contain ten billion potential life sites. In view of the physical inaccessibility of extraterrestrial life on account of the vast distances involved, a logical first step in a search for extraterrestrial intelligence (SETI) appears to be an attempt to detect signals already being radiated. The characteristics of the signals to be expected are discussed together with the search strategy of a NASA program. It is pointed out that all presently planned searches will use existing radio-astronomy antennas. If no extraterrestrial intelligence signals are discovered, society will have to decide whether SETI justifies a dedicated facility of much greater collecting area. Attention is given to a multichannel spectrum analyzer, CW signal detection, pulse detection, the pattern detector, and details of SETI system operation.

  17. Nanotubes for noisy signal processing

    NASA Astrophysics Data System (ADS)

    Lee, Ian Yenyin

    Nanotubes can process noisy signals. We present two central results in support of this general thesis and make an informed extrapolation that uses nanotubes to improve body armor. The first result is that noise can help nanotubes detect weak signals. The finding confirmed a stochastic-resonance theoretical prediction that noise can enhance detection at the nano-level. Laboratory experiments with nanotubes showed that three types of noise improved three measures of detection. Small amounts of Gaussian, uniform, and Cauchy additive white noise increased mutual-information, cross-correlation, and bit-error-rate measures before degrading them with further increases in noise. Nanotubes can apply this noise-enhancement and nanotube electrical and mechanical properties to improve signal processing. Similar noise enhancement may benefit a proposed nanotube-array cochlear-model spectral processing. The second result is that nanotube antennas can directly detect narrowband electromagnetic (EM) signals. The finding showed that nanotube and thin-wire dipoles are similar: They are resonant and narrowband and can implement linear-array designs if the EM waves in the nanotubes propagate at or near the free-space velocity of light. The nanotube-antenna prediction is based on a Fresnel-zone or near-zone analysis of antenna impedance using a quantum-conductor model. The analysis also predicts a failure to resonate if the nanotube EM-wave propagation is much slower than free-space light propagation. We extrapolate based on applied and theoretical analysis of body armor. Field experiments used a baseball comparison and statistical and other techniques to model body-armor bruising effects. A baseball comparison showed that a large caliber handgun bullet can hit an armored chest as hard as a fast baseball can hit a bare chest. Adaptive fuzzy systems learned to predict a bruise profile directly from the experimental data and also from statistical analysis of the data. Nanotube signal

  18. Signal Processing Circuit Development.

    DTIC Science & Technology

    1986-07-01

    Simplified active filter circuit 64 42. Video output amplifier 66 43. 64/128 gated clock circuitry 68 44. Two pole Sallen-Key active filters 7!1 45. Switched...four quadrant multiplier, log compression, multiple pole active video filtering and black level control. In what follows in this report an attempt...chip is shown in Fiqu-e 5. This is the master synch chip which generates all of the control signals necessary for TV monitor presentation of video data

  19. Multidimensional Signal Processing

    DTIC Science & Technology

    1988-06-01

    6C ADDRESS (City, State, and ZIP Code) 7b. ADDRESS (City. State, and ZIP Code) Dept of Elec Engr & Computer Science Ecbolten NJ 07030 Griffiss AF~3...product extends over all r~i (2.Al) PropIerty 2.B9: If a is a polynomial and degi(a+a) < degia for some i, then (a+a) must contain the factor zi...information processing, surveillance sensors, intelligence data collection and handling, solid state sciences , elect romagnetics, and propagation, and electronic reliability/maintainability and compatibiit,.

  20. Signal processing for semiconductor detectors

    SciTech Connect

    Goulding, F.S.; Landis, D.A.

    1982-02-01

    A balanced perspective is provided on the processing of signals produced by semiconductor detectors. The general problems of pulse shaping to optimize resolution with constraints imposed by noise, counting rate and rise time fluctuations are discussed.

  1. Electron quantum optics as quantum signal processing

    NASA Astrophysics Data System (ADS)

    Roussel, B.; Cabart, C.; Fève, G.; Thibierge, E.; Degiovanni, P.

    2017-03-01

    The recent developments of electron quantum optics in quantum Hall edge channels have given us new ways to probe the behavior of electrons in quantum conductors. It has brought new quantities called electronic coherences under the spotlight. In this paper, we explore the relations between electron quantum optics and signal processing through a global review of the various methods for accessing single- and two-electron coherences in electron quantum optics. We interpret electron quantum optics interference experiments as analog signal processing converting quantum signals into experimentally observable quantities such as current averages and correlations. This point of view also gives us a procedure to obtain quantum information quantities from electron quantum optics coherences. We illustrate these ideas by discussing two mode entanglement in electron quantum optics. We also sketch how signal processing ideas may open new perspectives for representing electronic coherences in quantum conductors and understand the properties of the underlying many-body electronic state.

  2. Biomedical signal and image processing.

    PubMed

    Cerutti, Sergio; Baselli, Giuseppe; Bianchi, Anna; Caiani, Enrico; Contini, Davide; Cubeddu, Rinaldo; Dercole, Fabio; Rienzo, Luca; Liberati, Diego; Mainardi, Luca; Ravazzani, Paolo; Rinaldi, Sergio; Signorini, Maria; Torricelli, Alessandro

    2011-01-01

    Generally, physiological modeling and biomedical signal processing constitute two important paradigms of biomedical engineering (BME): their fundamental concepts are taught starting from undergraduate studies and are more completely dealt with in the last years of graduate curricula, as well as in Ph.D. courses. Traditionally, these two cultural aspects were separated, with the first one more oriented to physiological issues and how to model them and the second one more dedicated to the development of processing tools or algorithms to enhance useful information from clinical data. A practical consequence was that those who did models did not do signal processing and vice versa. However, in recent years,the need for closer integration between signal processing and modeling of the relevant biological systems emerged very clearly [1], [2]. This is not only true for training purposes(i.e., to properly prepare the new professional members of BME) but also for the development of newly conceived research projects in which the integration between biomedical signal and image processing (BSIP) and modeling plays a crucial role. Just to give simple examples, topics such as brain–computer machine or interfaces,neuroengineering, nonlinear dynamical analysis of the cardiovascular (CV) system,integration of sensory-motor characteristics aimed at the building of advanced prostheses and rehabilitation tools, and wearable devices for vital sign monitoring and others do require an intelligent fusion of modeling and signal processing competences that are certainly peculiar of our discipline of BME.

  3. Cognitive Algorithms for Signal Processing

    DTIC Science & Technology

    2011-03-18

    63] L. I. Perlovsky and R. Kozma. Eds. Neurodynamics of Higher-Level Cognition and Consciousness. Heidelberg, Germany: Springer-Verlag, 2007. [64...AFRL-RY-HS-TR-2011-0013 ________________________________________________________________________ Cognitive Algorithms for Signal Processing...in more details in [46]. ..................................... 16  1 Abstract Processes in the mind: perception, cognition

  4. Optical Fiber Delay Line Signal Processing.

    NASA Astrophysics Data System (ADS)

    Newton, Steven Arthur

    The delay line transversal filter is a basic component in analog signal processing systems. Unfortunately, conventional delay line devices, such as those that use surface acoustic waves, are largely limited to operation at frequencies of several hundred megahertz and below. In this work, single-mode optical fiber has been used as a delay medium to make transversal filters that extend this kind of signal processing to frequencies of one gigahertz and above. Single-mode optical fiber is an excellent delay medium because it exhibits extremely low loss and dispersion. By efficiently collecting, weighting, and combining signals extracted from a fiber delay line, single-mode fiber can be used, not only to transmit broadband signals, but to process them as well. The goals of the work have been to study efficient tapping mechanisms, and to construct fiber transversal filters capable of performing some basic signal processing functions. Several different tapped and recirculating delay line prototypes have been fabricated using a variety of tapping techniques, including macrobending and evanescent field coupling. These devices have been used to demonstrate basic signal processing functions, such as code generation, convolution, correlation, and frequency filtering, at frequencies that exceed those possible using conventional delay line technologies. Fiber recirculating delay line loops have also been demonstrated as transient memories for the temporary storage of signals and as a means of time division multiplexing via data rate transformation. These devices are the building blocks that are necessary to make systems capable of performing complex signal processing functions. With the recent development of high speed optical sources and detectors to interface with fiber systems of this kind, the real time processing of signals having bandwidths of tens of gigahertz is envisioned.

  5. 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.

  6. [Anesthesia in the Signal Processing Methods].

    PubMed

    Gu, Jiajun; Huang, Yan; Ye, Jilun; Wang, Kaijun; Zhang, Meimei

    2015-09-01

    Anesthesia plays an essential role in clinical operations. Guiding anesthesia by EEG signals is one of the most promising methods at present and it has obtained good results. The analysis and process of the EEG signals in anesthesia can provide clean signal for further research. This paper used variance threshold method to remove the mutation fast and large interfering signals; and used notch filter to remove frequency interference, smoothing filter to remove baseline drift and Butterworth low-pass filter to remove high frequency noise at the same time. In addition to this, the translation invariant wavelet method to remove interference noise on the signals which was after the classical filter and retained non-stationary characteristics was used to evaluate parameter calculation. By comparing the calculated parameters from treated signal using this paper's methods and untreated signal and standard signal, the standard deviation and correlation has been improved, particularly the major parameters BetaR, which provides better signal for integration of multi-parameter to evaluate depth of anesthesia index for the latter.

  7. Acoustic signal processing toolbox for array processing

    NASA Astrophysics Data System (ADS)

    Pham, Tien; Whipps, Gene T.

    2003-08-01

    The US Army Research Laboratory (ARL) has developed an acoustic signal processing toolbox (ASPT) for acoustic sensor array processing. The intent of this document is to describe the toolbox and its uses. The ASPT is a GUI-based software that is developed and runs under MATLAB. The current version, ASPT 3.0, requires MATLAB 6.0 and above. ASPT contains a variety of narrowband (NB) and incoherent and coherent wideband (WB) direction-of-arrival (DOA) estimation and beamforming algorithms that have been researched and developed at ARL. Currently, ASPT contains 16 DOA and beamforming algorithms. It contains several different NB and WB versions of the MVDR, MUSIC and ESPRIT algorithms. In addition, there are a variety of pre-processing, simulation and analysis tools available in the toolbox. The user can perform simulation or real data analysis for all algorithms with user-defined signal model parameters and array geometries.

  8. SAR processing using SHARC signal processing systems

    NASA Astrophysics Data System (ADS)

    Huxtable, Barton D.; Jackson, Christopher R.; Skaron, Steve A.

    1998-09-01

    Synthetic aperture radar (SAR) is uniquely suited to help solve the Search and Rescue problem since it can be utilized either day or night and through both dense fog or thick cloud cover. Other papers in this session, and in this session in 1997, describe the various SAR image processing algorithms that are being developed and evaluated within the Search and Rescue Program. All of these approaches to using SAR data require substantial amounts of digital signal processing: for the SAR image formation, and possibly for the subsequent image processing. In recognition of the demanding processing that will be required for an operational Search and Rescue Data Processing System (SARDPS), NASA/Goddard Space Flight Center and NASA/Stennis Space Center are conducting a technology demonstration utilizing SHARC multi-chip modules from Boeing to perform SAR image formation processing.

  9. 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.

  10. 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.

  11. EEG Correlates of Self-Referential Processing

    PubMed Central

    Knyazev, Gennady G.

    2013-01-01

    Self-referential processing has been principally investigated using functional magnetic resonance imaging (fMRI). However, understanding of the brain functioning is not possible without careful comparison of the evidence coming from different methodological domains. This paper aims to review electroencephalographic (EEG) studies of self-referential processing and to evaluate how they correspond, complement, or contradict the existing fMRI evidence. There are potentially two approaches to the study of EEG correlates of self-referential processing. Firstly, because simultaneous registration of EEG and fMRI has become possible, the degree of overlap between these two signals in brain regions related to self-referential processing could be determined. Second and more direct approach would be the study of EEG correlates of self-referential processing per se. In this review, I discuss studies, which employed both these approaches and show that in line with fMRI evidence, EEG correlates of self-referential processing are most frequently found in brain regions overlapping with the default network, particularly in the medial prefrontal cortex. In the time domain, the discrimination of self- and others-related information is mostly associated with the P300 ERP component, but sometimes is observed even earlier. In the frequency domain, different frequency oscillations have been shown to contribute to self-referential processing, with spontaneous self-referential mentation being mostly associated with the alpha frequency band. PMID:23761757

  12. 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.

  13. Neural correlates of success and failure signals during neurofeedback learning.

    PubMed

    Radua, Joaquim; Stoica, Teodora; Scheinost, Dustin; Pittenger, Christopher; Hampson, Michelle

    2016-04-05

    Feedback-driven learning, observed across phylogeny and of clear adaptive value, is frequently operationalized in simple operant conditioning paradigms, but it can be much more complex, driven by abstract representations of success and failure. This study investigates the neural processes involved in processing success and failure during feedback learning, which are not well understood. Data analyzed were acquired during a multisession neurofeedback experiment in which ten participants were presented with, and instructed to modulate, the activity of their orbitofrontal cortex with the aim of decreasing their anxiety. We assessed the regional blood-oxygenation-level-dependent response to the individualized neurofeedback signals of success and failure across twelve functional runs acquired in two different magnetic resonance sessions in each of ten individuals. Neurofeedback signals of failure correlated early during learning with deactivation in the precuneus/posterior cingulate and neurofeedback signals of success correlated later during learning with deactivation in the medial prefrontal/anterior cingulate cortex. The intensity of the latter deactivations predicted the efficacy of the neurofeedback intervention in the reduction of anxiety. These findings indicate a role for regulation of the default mode network during feedback learning, and suggest a higher sensitivity to signals of failure during the early feedback learning and to signals of success subsequently.

  14. Highly Parallel Modern Signal Processing.

    DTIC Science & Technology

    1982-02-28

    looked at the application of these techniques to systems with coherent speckle noise, such as synthetic aperature (SAR) imagery, coherent sonar and...pprtitioned matrix inversion , comput;atio-n o"f crossambigul ty fun~ctions, formation of outer prCdu1cL tAand skewed outer products, and multiplication of...operations are multiplication, inversion , and L-U decomposition. In signal processing such operations can be found in adaptive filtering, data

  15. Signal processing in eukaryotic chemotaxis

    NASA Astrophysics Data System (ADS)

    Segota, Igor; Rachakonda, Archana; Franck, Carl

    2013-03-01

    Unlike inanimate condensed matter, living cells depend upon the detection of chemical signals for their existence. First, we experimentally determined the chemotaxis response of eukaryotic Dictyostelium cells to static folic acid gradients and show that they can respond to gradients as shallow as 0.2% across the cell body. Second, using Shannon's information theory, we showed that the information cells receive about the gradient exceeds the theoretically predicted information at the receptor-ligand binding step, resulting in the violation of the data processing inequality. Finally, we analyzed how eukaryotic cells can affect the gradient signals by secreting enzymes that degrade the signal. We analyzed this effect with a focus on a well described Dictyostelium cAMP chemotaxis system where cAMP signals are affected by an extracellular cAMP phosphodiesterase (PDE) and its inhibitor (PDI). Using a reaction-diffusion model of this set of interactions in the extracellular space, we show that cells can effectively sense much steeper chemical gradients than naively expected (up to a factor of 12). We also found that the rough estimates of experimental PDE and PDI secretion rates are close to the optimal values for gradient sensing as predicted by our model.

  16. Nuclear sensor signal processing circuit

    DOEpatents

    Kallenbach, Gene A.; Noda, Frank T.; Mitchell, Dean J.; Etzkin, Joshua L.

    2007-02-20

    An apparatus and method are disclosed for a compact and temperature-insensitive nuclear sensor that can be calibrated with a non-hazardous radioactive sample. The nuclear sensor includes a gamma ray sensor that generates tail pulses from radioactive samples. An analog conditioning circuit conditions the tail-pulse signals from the gamma ray sensor, and a tail-pulse simulator circuit generates a plurality of simulated tail-pulse signals. A computer system processes the tail pulses from the gamma ray sensor and the simulated tail pulses from the tail-pulse simulator circuit. The nuclear sensor is calibrated under the control of the computer. The offset is adjusted using the simulated tail pulses. Since the offset is set to zero or near zero, the sensor gain can be adjusted with a non-hazardous radioactive source such as, for example, naturally occurring radiation and potassium chloride.

  17. Signal Processing for Optical Networks

    DTIC Science & Technology

    2007-11-02

    ONLY (Leave Blank) 2. REPORT DATE 5 /1/98 3. REPORT TYPE AND DATES COVERED Final 9/30/95 - 1/1/98 4. TITLE AND SUBTITLE Signal Processing...for Optical Networks: 6. AUTHORS Dennis M. Healy Jr. 5 . FUNDING NUMBERS G (Grant) F1960 93 0567- 7. PERFORMING ORGANIZATION NAME(S) AND...NUMBER 9. SPONSORING / MONITORING AGENCY NAME(S) AND ADDRESS(ES) AFOSR/PKA 110 Duncan Avenue, Room Bl 15 Boiling, AFB DC 20332- 8050 Monitor

  18. Signal processing for distributed sensor concept: DISCO

    NASA Astrophysics Data System (ADS)

    Rafailov, Michael K.

    2007-04-01

    Distributed Sensor concept - DISCO proposed for multiplication of individual sensor capabilities through cooperative target engagement. DISCO relies on ability of signal processing software to format, to process and to transmit and receive sensor data and to exploit those data in signal synthesis process. Each sensor data is synchronized formatted, Signal-to-Noise Ration (SNR) enhanced and distributed inside of the sensor network. Signal processing technique for DISCO is Recursive Adaptive Frame Integration of Limited data - RAFIL technique that was initially proposed [1] as a way to improve the SNR, reduce data rate and mitigate FPA correlated noise of an individual sensor digital video-signal processing. In Distributed Sensor Concept RAFIL technique is used in segmented way, when constituencies of the technique are spatially and/or temporally separated between transmitters and receivers. Those constituencies include though not limited to two thresholds - one is tuned for optimum probability of detection, the other - to manage required false alarm rate, and limited frame integration placed somewhere between the thresholds as well as formatters, conventional integrators and more. RAFIL allows a non-linear integration that, along with SNR gain, provides system designers more capability where cost, weight, or power considerations limit system data rate, processing, or memory capability [2]. DISCO architecture allows flexible optimization of SNR gain, data rates and noise suppression on sensor's side and limited integration, re-formatting and final threshold on node's side. DISCO with Recursive Adaptive Frame Integration of Limited data may have flexible architecture that allows segmenting the hardware and software to be best suitable for specific DISCO applications and sensing needs - whatever it is air-or-space platforms, ground terminals or integration of sensors network.

  19. Extracting Coherent Information from Noise Based Correlation Processing

    DTIC Science & Technology

    2015-09-30

    signal processing that overcome the effects of the fluctuating ocean by essentilly developing techniques that speed up the processing to time scales...appropriate signal processing methods. WORK COMPLETED There have been two thrusts –the first has been related to extending the range/ valdity of the...Correlation Processing W. A. Kuperman and W. S. Hodgkiss Marine Physical Laboratory of the Scripps Institution of Ocenaography Univeritiy of

  20. Synthetic aperture radar signal processing: Trends and technologies

    NASA Technical Reports Server (NTRS)

    Curlander, John C.

    1993-01-01

    An overview of synthetic aperture radar (SAR) technology is presented in vugraph form. The following topics are covered: an SAR ground data system; SAR signal processing algorithms; SAR correlator architectures; and current and future trends.

  1. No-signaling, perfect bipartite dichotomic correlations and local randomness

    SciTech Connect

    Seevinck, M. P.

    2011-03-28

    The no-signaling constraint on bi-partite correlations is reviewed. It is shown that in order to obtain non-trivial Bell-type inequalities that discern no-signaling correlations from more general ones, one must go beyond considering expectation values of products of observables only. A new set of nontrivial no-signaling inequalities is derived which have a remarkably close resemblance to the CHSH inequality, yet are fundamentally different. A set of inequalities by Roy and Singh and Avis et al., which is claimed to be useful for discerning no-signaling correlations, is shown to be trivially satisfied by any correlation whatsoever. Finally, using the set of newly derived no-signaling inequalities a result with potential cryptographic consequences is proven: if different parties use identical devices, then, once they have perfect correlations at spacelike separation between dichotomic observables, they know that because of no-signaling the local marginals cannot but be completely random.

  2. Chaos-Based Signal Processing

    NASA Astrophysics Data System (ADS)

    Ogorzałek, Maciej J.

    2002-07-01

    Nonlinear systems exhibiting chaotic behavior can be considered as a source of a great variety of signals. Given a time series measured from a known or an unknown dynamical system we address a series of problems, such as section-wise approximation of the measured signal by pieces of trajectories from a chosen nonlinear dynamical system (model) signal restoration when the measured signal has been corrupted e.g. by quantization; signal coding and compression. The key to attack these problems is estimation of the initial conditions for a dynamical system which is used as the generator of approximating waveforms.

  3. Seismic signal processing on heterogeneous supercomputers

    NASA Astrophysics Data System (ADS)

    Gokhberg, Alexey; Ermert, Laura; Fichtner, Andreas

    2015-04-01

    The processing of seismic signals - including the correlation of massive ambient noise data sets - represents an important part of a wide range of seismological applications. It is characterized by large data volumes as well as high computational input/output intensity. Development of efficient approaches towards seismic signal processing on emerging high performance computing systems is therefore essential. Heterogeneous supercomputing systems introduced in the recent years provide numerous computing nodes interconnected via high throughput networks, every node containing a mix of processing elements of different architectures, like several sequential processor cores and one or a few graphical processing units (GPU) serving as accelerators. A typical representative of such computing systems is "Piz Daint", a supercomputer of the Cray XC 30 family operated by the Swiss National Supercomputing Center (CSCS), which we used in this research. Heterogeneous supercomputers provide an opportunity for manifold application performance increase and are more energy-efficient, however they have much higher hardware complexity and are therefore much more difficult to program. The programming effort may be substantially reduced by the introduction of modular libraries of software components that can be reused for a wide class of seismology applications. The ultimate goal of this research is design of a prototype for such library suitable for implementing various seismic signal processing applications on heterogeneous systems. As a representative use case we have chosen an ambient noise correlation application. Ambient noise interferometry has developed into one of the most powerful tools to image and monitor the Earth's interior. Future applications will require the extraction of increasingly small details from noise recordings. To meet this demand, more advanced correlation techniques combined with very large data volumes are needed. This poses new computational problems that

  4. Correlated EEG Signals Simulation Based on Artificial Neural Networks.

    PubMed

    Tomasevic, Nikola M; Neskovic, Aleksandar M; Neskovic, Natasa J

    2016-09-30

    In recent years, simulation of the human electroencephalogram (EEG) data found its important role in medical domain and neuropsychology. In this paper, a novel approach to simulation of two cross-correlated EEG signals is proposed. The proposed method is based on the principles of artificial neural networks (ANN). Contrary to the existing EEG data simulators, the ANN-based approach was leveraged solely on the experimentally acquired EEG data. More precisely, measured EEG data were utilized to optimize the simulator which consisted of two ANN models (each model responsible for generation of one EEG sequence). In order to acquire the EEG recordings, the measurement campaign was carried out on a healthy awake adult having no cognitive, physical or mental load. For the evaluation of the proposed approach, comprehensive quantitative and qualitative statistical analysis was performed considering probability distribution, correlation properties and spectral characteristics of generated EEG processes. The obtained results clearly indicated the satisfactory agreement with the measurement data.

  5. Superconductive signal-processing circuits

    NASA Astrophysics Data System (ADS)

    Vanduzer, Theodore

    1994-08-01

    This work addresses new signal processing circuits using the special features of superconductivity. A novel flash-type analog-to-digital converter based on a comparator invented in the preceding contract period was demonstrated. The comparator was shown to be useful as a logic gate and an encoder was designed with it. A high-resolution delta-sigma analog-to-digital converter was devised with superconductive components in spite of the lack of an analog integrator in this technology. Positive theoretical results are being followed up experimentally. A simple flux-shuttle single-flux-quantum shift register was devised and several different readout schemes were studied. A six-bit-long version was successfully tested at 1 GHz. A decoder that takes in a five-bit word to select one of 32 output lines was completed. The design involved very tight limitations on current and power. The decoder was combined with a serial-to-parallel converter and operated at 2 GHz. A study of the appropriate architectures for various types of superconductive or Josephson digital technology was developed: an inductance-extraction program.

  6. [Neural correlates of emotional processes].

    PubMed

    Weniger, Godehard

    2014-02-12

    The investigation of emotional processes has been neglected for a long time. But with the appearance of new imaging methods, a growing interest in the neural representation of emotional processes emerged. According to recent findings, emotional information were proceed by overlapping neural networks, especially the interaction between the limbic system and heteromodal association cortices.

  7. Spectral Correlation of Multicarrier Modulated Signals and Its Application for Signal Detection

    NASA Astrophysics Data System (ADS)

    Zhang, Haijian; Le Ruyet (Eurasipmember), Didier; Terré, Michel

    2009-12-01

    Spectral correlation theory for cyclostationary time-series signals has been studied for decades. Explicit formulas of spectral correlation function for various types of analog-modulated and digital-modulated signals are already derived. In this paper, we investigate and exploit the cyclostationarity characteristics for two kinds of multicarrier modulated (MCM) signals: conventional OFDM and filter bank based multicarrier (FBMC) signals. The spectral correlation characterization of MCM signal can be described by a special linear periodic time-variant (LPTV) system. Using this LPTV description, we have derived the explicit theoretical formulas of nonconjugate and conjugate cyclic autocorrelation function (CAF) and spectral correlation function (SCF) for OFDM and FBMC signals. According to theoretical spectral analysis, Cyclostationary Signatures (CS) are artificially embedded into MCM signal and a low-complexity signature detector is, therefore, presented for detecting MCM signal. Theoretical analysis and simulation results demonstrate the efficiency and robustness of this CS detector compared to traditionary energy detector.

  8. Digital Signal Processing Based Biotelemetry Receivers

    NASA Technical Reports Server (NTRS)

    Singh, Avtar; Hines, John; Somps, Chris

    1997-01-01

    This is an attempt to develop a biotelemetry receiver using digital signal processing technology and techniques. The receiver developed in this work is based on recovering signals that have been encoded using either Pulse Position Modulation (PPM) or Pulse Code Modulation (PCM) technique. A prototype has been developed using state-of-the-art digital signal processing technology. A Printed Circuit Board (PCB) is being developed based on the technique and technology described here. This board is intended to be used in the UCSF Fetal Monitoring system developed at NASA. The board is capable of handling a variety of PPM and PCM signals encoding signals such as ECG, temperature, and pressure. A signal processing program has also been developed to analyze the received ECG signal to determine heart rate. This system provides a base for using digital signal processing in biotelemetry receivers and other similar applications.

  9. Analog Signal Correlating Using an Analog-Based Signal Conditioning Front End

    NASA Technical Reports Server (NTRS)

    Prokop, Norman; Krasowski, Michael

    2013-01-01

    This innovation is capable of correlating two analog signals by using an analog-based signal conditioning front end to hard-limit the analog signals through adaptive thresholding into a binary bit stream, then performing the correlation using a Hamming "similarity" calculator function embedded in a one-bit digital correlator (OBDC). By converting the analog signal into a bit stream, the calculation of the correlation function is simplified, and less hardware resources are needed. This binary representation allows the hardware to move from a DSP where instructions are performed serially, into digital logic where calculations can be performed in parallel, greatly speeding up calculations.

  10. Enhancement Of Optical Registration Signals Through Digital Signal Processing Techniques

    NASA Astrophysics Data System (ADS)

    Cote, Daniel R.; Lazo-Wasem, Jeanne

    1988-01-01

    Alignment and setup of lighography processes has largely been conducted on special test wafers. Actual product level optimization has been limited to manual techniques such as optical verniers. This is especially time consuming and prone to inconsistencies when the registration characteristics of lithographic systems are being measured. One key factor obstructing the use of automated metrology equipment on product level wafers is the inability to discern reliably, metrology features from the background noise and variations in optical registration signals. This is often the case for metal levels such as aluminum and tungsten. This paper discusses methods for enhancement of typical registration signals obtained from difficult semiconductor process levels. Brightfield and darkfield registration signals are obtained using a microscope and a 1024 element linear photodiode array. These signals are then digitized and stored on the hard disk of a computer. The techniques utilized include amplitude selective and adaptive and non-adaptive frequency domain filtering techniques. The effect of each of these techniques upon calculated registration values is analyzed by determining the positional variation of the center location of a two line registration feature. Plots of raw and processed signals obtained are presented as are plots of the power spectral density of ideal metrology feature signal and noise patterns. It is concluded that the proper application of digital signal processing (DSP) techniques to problematic optical registration signals greatly enhances the applicability of automated optical registration measurement techniques to difficult semiconductor process levels.

  11. Signal processing considerations for low signal to noise ratio laser Doppler and phase Doppler signals

    NASA Technical Reports Server (NTRS)

    Ibrahim, K. M.; Wertheimer, G. D.; Bachalo, William D.

    1991-01-01

    The relative performance of current methods used for estimating the phase and the frequency in LDV and phase Doppler applications in low signal to noise ratio conditions is analyzed. These methods include the Fourier analysis and the correlation techniques. Three methods that use the correlation function for frequency and phase estimations are evaluated in terms of accuracy and speed of processing. These methods include: (1) the frequency estimation using zero crossings counting of the auto-correlation function, (2) the Blackman-Tukey method, and (3) the AutoRegressive method (AR). The relative performance of these methods is evaluated and compared with the Fourier analysis method which provides the optimum performance in terms of the Maximum Likelihood (ML) criteria.

  12. Adaptive Signal Processing Testbed signal excision software: User's manual

    NASA Astrophysics Data System (ADS)

    Parliament, Hugh A.

    1992-05-01

    The Adaptive Signal Processing Testbed (ASPT) signal excision software is a set of programs that provide real-time processing functions for the excision of interfering tones from a live spread-spectrum signal as well as off-line functions for the analysis of the effectiveness of the excision technique. The processing functions provided by the ASPT signal excision software are real-time adaptive filtering of live data, storage to disk, and file sorting and conversion. The main off-line analysis function is bit error determination. The purpose of the software is to measure the effectiveness of an adaptive filtering algorithm to suppress interfering or jamming signals in a spread spectrum signal environment. A user manual for the software is provided, containing information on the different software components available to perform signal excision experiments: the real-time excision software, excision host program, file processing utilities, and despreading and bit error rate determination software. In addition, information is presented describing the excision algorithm implemented, the real-time processing framework, the steps required to add algorithms to the system, the processing functions used in despreading, and description of command sequences for post-run analysis of the data.

  13. Time Integrating Optical Signal Processing

    DTIC Science & Technology

    1981-07-01

    diode source modulation, and (b) acousto - lit X)= l,(t)l(t - x / v). ( 2 ) optic deflector modulation for SSS example. F,,r double sideband modulation 1... 2 -1 2.1.2 Acousto - Optic Time-Integrating Correlator . ...... .. 2 -3 2.1.3 Noncoherent Space Integrating Correlator ......... . . 2 -6 2.1.4...device limitation. Acousto - optic devices ] are available with time-bandwidth product much greater than the number of resolvable image samples. 1- 2 I i

  14. Process Dissociation and Mixture Signal Detection Theory

    ERIC Educational Resources Information Center

    DeCarlo, Lawrence T.

    2008-01-01

    The process dissociation procedure was developed in an attempt to separate different processes involved in memory tasks. The procedure naturally lends itself to a formulation within a class of mixture signal detection models. The dual process model is shown to be a special case. The mixture signal detection model is applied to data from a widely…

  15. Signals Intelligence - Processing - Analysis - Classification

    DTIC Science & Technology

    2009-10-01

    Example: Language identification from audio signals. In a certain mission, a set of languages seems important beforehand. These languages will – with a...tasks to be performed. • OCR: determine the text parts in an image – language dependent approach, quality depends on the language. • Steganography

  16. Improved television signal processing system

    NASA Technical Reports Server (NTRS)

    Wong, R. Y.

    1967-01-01

    Digital system processes spacecraft television pictures by converting images sensed on a photostorage vidicon to pulses which can be transmitted by telemetry. This system can be applied in the processing of medical X ray photographs and in electron microscopy.

  17. Signal Processing Fault Detection System

    DTIC Science & Technology

    2007-07-13

    of strain sensor signals is wavelet analysis which is a linear mathematical analysis technique that can analyze discontinuities and edge effects...Real wavelets are suitable for identifying discontinuities and data compression. Analytic wavelets are suitable for capturing frequency content within a...function (i.e. the time series data captured from the sensors) and l*a,.u is identified as the complex conjugate of the mother wavelet . The variable t

  18. Signal processing in ultrasound. [for diagnostic medicine

    NASA Technical Reports Server (NTRS)

    Le Croissette, D. H.; Gammell, P. M.

    1978-01-01

    Signal is the term used to denote the characteristic in the time or frequency domain of the probing energy of the system. Processing of this signal in diagnostic ultrasound occurs as the signal travels through the ultrasonic and electrical sections of the apparatus. The paper discusses current signal processing methods, postreception processing, display devices, real-time imaging, and quantitative measurements in noninvasive cardiology. The possibility of using deconvolution in a single transducer system is examined, and some future developments using digital techniques are outlined.

  19. Bistatic SAR: Signal Processing and Image Formation.

    SciTech Connect

    Wahl, Daniel E.; Yocky, David A.

    2014-10-01

    This report describes the significant processing steps that were used to take the raw recorded digitized signals from the bistatic synthetic aperture RADAR (SAR) hardware built for the NCNS Bistatic SAR project to a final bistatic SAR image. In general, the process steps herein are applicable to bistatic SAR signals that include the direct-path signal and the reflected signal. The steps include preprocessing steps, data extraction to for a phase history, and finally, image format. Various plots and values will be shown at most steps to illustrate the processing for a bistatic COSMO SkyMed collection gathered on June 10, 2013 on Kirtland Air Force Base, New Mexico.

  20. Correlation Spectroscopy of Minor Species: Signal Purification and Distribution Analysis

    SciTech Connect

    Laurence, T A; Kwon, Y; Yin, E; Hollars, C; Camarero, J A; Barsky, D

    2006-06-21

    We are performing experiments that use fluorescence resonance energy transfer (FRET) and fluorescence correlation spectroscopy (FCS) to monitor the movement of an individual donor-labeled sliding clamp protein molecule along acceptor-labeled DNA. In addition to the FRET signal sought from the sliding clamp-DNA complexes, the detection channel for FRET contains undesirable signal from free sliding clamp and free DNA. When multiple fluorescent species contribute to a correlation signal, it is difficult or impossible to distinguish between contributions from individual species. As a remedy, we introduce ''purified FCS'' (PFCS), which uses single molecule burst analysis to select a species of interest and extract the correlation signal for further analysis. We show that by expanding the correlation region around a burst, the correlated signal is retained and the functional forms of FCS fitting equations remain valid. We demonstrate the use of PFCS in experiments with DNA sliding clamps. We also introduce ''single molecule FCS'', which obtains diffusion time estimates for each burst using expanded correlation regions. By monitoring the detachment of weakly-bound 30-mer DNA oligomers from a single-stranded DNA plasmid, we show that single molecule FCS can distinguish between bursts from species that differ by a factor of 5 in diffusion constant.

  1. Synthesis, Analysis, and Processing of Fractal Signals

    DTIC Science & Technology

    1991-10-01

    fractal dimension of the underlying signal , when defined. Robust estimation of the fractal dimension of 1/f processes is important in a number of...modeling errors. The resulting parameter estimation algorithms, which compute both fractal dimension parameters and the accompanying signal and noise...Synthesis, Analysis, and Processing of Fractal Signals RLE Technical Report No. 566 Gregory W. Wornell October 1991 Research Laboratory of

  2. Advanced Digital Signal Processing for Hybrid Lidar

    DTIC Science & Technology

    2013-09-30

    Advanced Digital Signal Processing for Hybrid Lidar William D. Jemison Clarkson University [Technical Section Technical Objectives The technical...objective of this project is the development and evaluation of various digital signal processing (DSP) algorithms that will enhance hybrid lidar ...algorithm as shown in Figure 1. Hardware Platform for Algorithm Implementation + Underwater Channel Characteristics ^ Lidar DSP Algorithm Figure

  3. Noise-processing by signaling networks.

    PubMed

    Kontogeorgaki, Styliani; Sánchez-García, Rubén J; Ewing, Rob M; Zygalakis, Konstantinos C; MacArthur, Ben D

    2017-04-03

    Signaling networks mediate environmental information to the cell nucleus. To perform this task effectively they must be able to integrate multiple stimuli and distinguish persistent signals from transient environmental fluctuations. However, the ways in which signaling networks process environmental noise are not well understood. Here we outline a mathematical framework that relates a network's structure to its capacity to process noise, and use this framework to dissect the noise-processing ability of signaling networks. We find that complex networks that are dense in directed paths are poor noise processors, while those that are sparse and strongly directional process noise well. These results suggest that while cross-talk between signaling pathways may increase the ability of signaling networks to integrate multiple stimuli, too much cross-talk may compromise the ability of the network to distinguish signal from noise. To illustrate these general results we consider the structure of the signalling network that maintains pluripotency in mouse embryonic stem cells, and find an incoherent feedforward loop structure involving Stat3, Tfcp2l1, Esrrb, Klf2 and Klf4 is particularly important for noise-processing. Taken together these results suggest that noise-processing is an important function of signaling networks and they may be structured in part to optimize this task.

  4. Internal signal correlates neural populations and biases perceptual decision reports

    PubMed Central

    Carnevale, Federico; de Lafuente, Victor; Romo, Ranulfo; Parga, Néstor

    2012-01-01

    In perceptual decision-making tasks the activity of neurons in frontal and posterior parietal cortices covaries more with perceptual reports than with the physical properties of stimuli. This relationship is revealed when subjects have to make behavioral choices about weak or uncertain stimuli. If knowledge about stimulus onset time is available, decision making can be based on accumulation of sensory evidence. However, the time of stimulus onset or even its very presence is often ambiguous. By analyzing firing rates and correlated variability of frontal lobe neurons while monkeys perform a vibrotactile detection task, we show that behavioral outcomes are crucially affected by the state of cortical networks before stimulus onset times. The results suggest that sensory detection is partly due to a purely internal signal whereas the stimulus, if finally applied, adds a contribution to this initial processing later on. The probability to detect or miss the stimulus can thus be explained as the combined effect of this variable internal signal and the sensory evidence. PMID:23112203

  5. High-speed and reconfigurable all-optical signal processing for phase and amplitude modulated signals

    NASA Astrophysics Data System (ADS)

    Khaleghi, Salman

    nonlinear media, such as highly nonlinear fiber, periodically poled lithium niobate, and semiconductor optical amplifiers, for nonlinear mixing of optical signals. We propose and experimentally demonstrate a novel, fully tunable optical tapped-delay-line that is a key building block for signal processing functions. Applications such as finite impulse response filtering, equalization, correlation (pattern recognition), discrete Fourier transform, digital-to-analog conversion, and flexible optical signal conversion and generation are shown. The phase- and amplitude-preserving nature of the demonstrated techniques, together with their wide-tuning range, allows for processing of optical signals that carry different modulation formats with different data rates. The reconfigurability may apply to future optical networks that carry heterogeneous traffic with different modulation formats and baud rates.

  6. RSFQ Baseband Digital Signal Processing

    NASA Astrophysics Data System (ADS)

    Herr, Anna Yurievna

    Ultra fast switching speed of superconducting digital circuits enable realization of Digital Signal Processors with performance unattainable by any other technology. Based on rapid-single-flux technology (RSFQ) logic, these integrated circuits are capable of delivering high computation capacity up to 30 GOPS on a single processor and very short latency of 0.1ns. There are two main applications of such hardware for practical telecommunication systems: filters for superconducting ADCs operating with digital RF data and recursive filters at baseband. The later of these allows functions such as multiuser detection for 3G WCDMA, equalization and channel precoding for 4G OFDM MIMO, and general blind detection. The performance gain is an increase in the cell capacity, quality of service, and transmitted data rate. The current status of the development of the RSFQ baseband DSP is discussed. Major components with operating speed of 30GHz have been developed. Designs, test results, and future development of the complete systems including cryopackaging and CMOS interface are reviewed.

  7. Weighted parallel contributions of binocular correlation and match signals to conscious perception of depth.

    PubMed

    Fujita, Ichiro; Doi, Takahiro

    2016-06-19

    Binocular disparity is detected in the primary visual cortex by a process similar to calculation of local cross-correlation between left and right retinal images. As a consequence, correlation-based neural signals convey information about false disparities as well as the true disparity. The false responses in the initial disparity detectors are eliminated at later stages in order to encode only disparities of the features correctly matched between the two eyes. For a simple stimulus configuration, a feed-forward nonlinear process can transform the correlation signal into the match signal. For human observers, depth judgement is determined by a weighted sum of the correlation and match signals rather than depending solely on the latter. The relative weight changes with spatial and temporal parameters of the stimuli, allowing adaptive recruitment of the two computations under different visual circumstances. A full transformation from correlation-based to match-based representation occurs at the neuronal population level in cortical area V4 and manifests in single-neuron responses of inferior temporal and posterior parietal cortices. Neurons in area V5/MT represent disparity in a manner intermediate between the correlation and match signals. We propose that the correlation and match signals in these areas contribute to depth perception in a weighted, parallel manner.This article is part of the themed issue 'Vision in our three-dimensional world'.

  8. Optical Profilometers Using Adaptive Signal Processing

    NASA Technical Reports Server (NTRS)

    Hall, Gregory A.; Youngquist, Robert; Mikhael, Wasfy

    2006-01-01

    A method of adaptive signal processing has been proposed as the basis of a new generation of interferometric optical profilometers for measuring surfaces. The proposed profilometers would be portable, hand-held units. Sizes could be thus reduced because the adaptive-signal-processing method would make it possible to substitute lower-power coherent light sources (e.g., laser diodes) for white light sources and would eliminate the need for most of the optical components of current white-light profilometers. The adaptive-signal-processing method would make it possible to attain scanning ranges of the order of decimeters in the proposed profilometers.

  9. 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

  10. Nonlinear and Nonstationary Signal Processing

    NASA Astrophysics Data System (ADS)

    Wunsch, Carl

    Stationary linear systems driven by Gaussian processes are the basic representations of time series used in the Earth sciences. A large body of literature has developed around these misleadingly simple models, which straddle statistics, optimization, control, probability theory, and related fields. That fundamental errors of inference are still made in the refereed literature is perhaps a testimony to the subtleties and confusion that arise when statistics meets the real geophysical world. A major journal devoted to modern climate studies recently felt compelled to publish a tutorial explaining the importance of avoiding aliasing errors when sampling meteorological variables; this subject was clearly understood 100 years ago.

  11. 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.

  12. Digital signal processing in microwave radiometers

    NASA Technical Reports Server (NTRS)

    Lawrence, R. W.; Stanley, W. D.; Harrington, R. F.

    1980-01-01

    A microprocessor based digital signal processing unit has been proposed to replace analog sections of a microwave radiometer. A brief introduction to the radiometer system involved and a description of problems encountered in the use of digital techniques in radiometer design are discussed. An analysis of the digital signal processor as part of the radiometer is then presented.

  13. Topics in digital signal processing

    NASA Astrophysics Data System (ADS)

    Narayan, S. S. R.

    Three discrete Fourier transform (DFT) algorithms, namely, the fast Fourier transform algorithm (FFT), the prime factor algorithm (PFA) and the Winograd Fourier transform algorithm (WFTA) are analyzed and compared. A new set of short-length DFT algorithms well-suited for special purpose hardware implementations, employing monolithic multiplier-accumulators and microprocessors, are presented. Architectural considerations in designing DFT processors based on these algorithms are discussed. Efficient hardware structures for implementing the FFT and the PFA are presented. A digital implementation for performing linear-FM (LFM) pulse compression by using bandpass filter banks is presented. The concept of transform domain adaptive filtering is introduced. The DFT and the discrete cosine transform (DFT) domain adaptive filtering algorithm are considered. Applications of these in the areas of speech processing and adaptive line enhancers are discussed. A simple waveform coding algorithm capable of providing good quality speech at about 1.5 bits per sample is presented.

  14. Neutron coincidence counting with digital signal processing

    NASA Astrophysics Data System (ADS)

    Bagi, Janos; Dechamp, Luc; Dransart, Pascal; Dzbikowicz, Zdzislaw; Dufour, Jean-Luc; Holzleitner, Ludwig; Huszti, Joseph; Looman, Marc; Marin Ferrer, Montserrat; Lambert, Thierry; Peerani, Paolo; Rackham, Jamie; Swinhoe, Martyn; Tobin, Steve; Weber, Anne-Laure; Wilson, Mark

    2009-09-01

    Neutron coincidence counting is a widely adopted nondestructive assay (NDA) technique used in nuclear safeguards to measure the mass of nuclear material in samples. Nowadays, most neutron-counting systems are based on the original-shift-register technology, like the (ordinary or multiplicity) Shift-Register Analyser. The analogue signal from the He-3 tubes is processed by an amplifier/single channel analyser (SCA) producing a train of TTL pulses that are fed into an electronic unit that performs the time- correlation analysis. Following the suggestion of the main inspection authorities (IAEA, Euratom and the French Ministry of Industry), several research laboratories have started to study and develop prototypes of neutron-counting systems with PC-based processing. Collaboration in this field among JRC, IRSN and LANL has been established within the framework of the ESARDA-NDA working group. Joint testing campaigns have been performed in the JRC PERLA laboratory, using different equipment provided by the three partners. One area of development is the use of high-speed PCs and pulse acquisition electronics that provide a time stamp (LIST-Mode Acquisition) for every digital pulse. The time stamp data can be processed directly during acquisition or saved on a hard disk. The latter method has the advantage that measurement data can be analysed with different values for parameters like predelay and gate width, without repeating the acquisition. Other useful diagnostic information, such as die-away time and dead time, can also be extracted from this stored data. A second area is the development of "virtual instruments." These devices, in which the pulse-processing system can be embedded in the neutron counter itself and sends counting data to a PC, can give increased data-acquisition speeds. Either or both of these developments could give rise to the next generation of instrumentation for improved practical neutron-correlation measurements. The paper will describe the

  15. Optical signal processing of phased array radar

    NASA Astrophysics Data System (ADS)

    Weverka, Robert T.

    This thesis develops optical processors that scale to very high processing speed. Optical signal processing is often promoted on the basis of smaller size, lower weight and lower power consumption as well as higher signal processing speed. While each of these requirements has applications, it is the ones that require processing speed beyond that available in electronics that are most compelling. Thirty years ago, optical processing was the only method fast enough to process Synthetic Aperture Radar (SAR), one of the more demanding signal processing tasks at this time. Since that time electronic processing speed has improved sufficiently to tackle that problem. We have sought out the problems that require significantly higher processing speed and developed optical processors that tackle these more difficult problems. The components that contribute to high signal processing speed are high input signal bandwidth, a large number of parallel input channels each with this high bandwidth, and a large number of parallel operations required on each input channel. Adaptive signal processing for phased array radar has all of these factors. The processors developed for this task scale well in three dimensions, which allows them to maximize parallelism for high speed. This thesis explores an example of a negative feedback adaptive phased array processor and an example of a positive feedback phased array processor. The negative feedback processor uses and array of inputs in up to two dimensions together with the time history of the signal in the third dimension to adapt the array pattern to null out incoming jammer signals. The positive feedback processor uses the incoming signals and assumptions about the radar scene to correct for position errors in a phased array. Discovery and analysis of these new processors are facilitated by an original volume holographic analysis technique developed in the thesis. The thesis includes a new acoustooptic Bragg cell geometry developed with

  16. Neural Networks Applied to Signal Processing

    DTIC Science & Technology

    1989-09-01

    DTIC FILE COpy NAVAL POSTGRADUATE SCHOOL . Monterey, California Lf 0 (0 V’ STATES 4 THESIS NEURAL NETWORKS APPLIED TO SIGNAL PROCESSING by Mark D...FUNDING NUMBERS PROGRAM PROJECT TASK WORK UNIT ELEMENT NO NO NO ACCESSION NO. 11. TITLE (Include Security Classification) NEURAL NETWORKS APPLIED TO...for public release; distribution is unlimited Neural Networks Applied to Signal Processing by Mark D. Baehre Captain, United States Army B.S., United

  17. Removing correlations in signals transmitted over a quantum memory channel

    NASA Astrophysics Data System (ADS)

    Lupo, Cosmo; Memarzadeh, Laleh; Mancini, Stefano

    2012-01-01

    We consider a model of a bosonic memory channel, which induces correlations among the transmitted signals. The application of suitable unitary transformations at the encoding and decoding stages allows the complete removal of correlations, thereby mapping the memory channel into a memoryless one. However, such transformations, being global over an arbitrarily large number of bosonic modes, are not realistically implementable. We then introduce a family of efficiently realizable transformations, which can be used to partially remove correlations among errors, and we quantify the reduction of the gap with memoryless channels.

  18. Process correlation analysis model for process improvement identification.

    PubMed

    Choi, Su-jin; Kim, Dae-Kyoo; Park, Sooyong

    2014-01-01

    Software process improvement aims at improving the development process of software systems. It is initiated by process assessment identifying strengths and weaknesses and based on the findings, improvement plans are developed. In general, a process reference model (e.g., CMMI) is used throughout the process of software process improvement as the base. CMMI defines a set of process areas involved in software development and what to be carried out in process areas in terms of goals and practices. Process areas and their elements (goals and practices) are often correlated due to the iterative nature of software development process. However, in the current practice, correlations of process elements are often overlooked in the development of an improvement plan, which diminishes the efficiency of the plan. This is mainly attributed to significant efforts and the lack of required expertise. In this paper, we present a process correlation analysis model that helps identify correlations of process elements from the results of process assessment. This model is defined based on CMMI and empirical data of improvement practices. We evaluate the model using industrial data.

  19. Correlated activity supports efficient cortical processing

    PubMed Central

    Hung, Chou P.; Cui, Ding; Chen, Yueh-peng; Lin, Chia-pei; Levine, Matthew R.

    2015-01-01

    Visual recognition is a computational challenge that is thought to occur via efficient coding. An important concept is sparseness, a measure of coding efficiency. The prevailing view is that sparseness supports efficiency by minimizing redundancy and correlations in spiking populations. Yet, we recently reported that “choristers”, neurons that behave more similarly (have correlated stimulus preferences and spontaneous coincident spiking), carry more generalizable object information than uncorrelated neurons (“soloists”) in macaque inferior temporal (IT) cortex. The rarity of choristers (as low as 6% of IT neurons) indicates that they were likely missed in previous studies. Here, we report that correlation strength is distinct from sparseness (choristers are not simply broadly tuned neurons), that choristers are located in non-granular output layers, and that correlated activity predicts human visual search efficiency. These counterintuitive results suggest that a redundant correlational structure supports efficient processing and behavior. PMID:25610392

  20. Prediction Theory of Periodically Correlated Stochastic Processes

    DTIC Science & Technology

    2015-05-12

    SECURITY CLASSIFICATION OF: The research dealt with the prediction problem for periodically correlated sequences, that is the stochastic sequences...was to develop an alternative technique for analysis such sequences . In the first published paper we 1. REPORT DATE (DD-MM-YYYY) 4. TITLE AND...Aug-2014 Approved for Public Release; Distribution Unlimited Final Report: Prediction Theory of Periodically Correlated Stochastic Processes. The

  1. Digital signal processor and programming system for parallel signal processing

    SciTech Connect

    Van den Bout, D.E.

    1987-01-01

    This thesis describes an integrated assault upon the problem of designing high-throughput, low-cost digital signal-processing systems. The dual prongs of this assault consist of: (1) the design of a digital signal processor (DSP) which efficiently executes signal-processing algorithms in either a uniprocessor or multiprocessor configuration, (2) the PaLS programming system which accepts an arbitrary algorithm, partitions it across a group of DSPs, synthesizes an optimal communication link topology for the DSPs, and schedules the partitioned algorithm upon the DSPs. The results of applying a new quasi-dynamic analysis technique to a set of high-level signal-processing algorithms were used to determine the uniprocessor features of the DSP design. For multiprocessing applications, the DSP contains an interprocessor communications port (IPC) which supports simple, flexible, dataflow communications while allowing the total communication bandwidth to be incrementally allocated to achieve the best link utilization. The net result is a DSP with a simple architecture that is easy to program for both uniprocessor and multi-processor modes of operation. The PaLS programming system simplifies the task of parallelizing an algorithm for execution upon a multiprocessor built with the DSP.

  2. Photoacoustic correlation signal-to-noise ratio enhancement by coherent averaging and optical waveform optimization.

    PubMed

    Telenkov, Sergey A; Alwi, Rudolf; Mandelis, Andreas

    2013-10-01

    Photoacoustic (PA) imaging of biological tissues using laser diodes instead of conventional Q-switched pulsed systems provides an attractive alternative for biomedical applications. However, the relatively low energy of laser diodes operating in the pulsed regime, results in generation of very weak acoustic waves, and low signal-to-noise ratio (SNR) of the detected signals. This problem can be addressed if optical excitation is modulated using custom waveforms and correlation processing is employed to increase SNR through signal compression. This work investigates the effect of the parameters of the modulation waveform on the resulting correlation signal and offers a practical means for optimizing PA signal detection. The advantage of coherent signal averaging is demonstrated using theoretical analysis and a numerical model of PA generation. It was shown that an additional 5-10 dB of SNR can be gained through waveform engineering by adjusting the parameters and profile of optical modulation waveforms.

  3. Using acoustic emission signals for monitoring of production processes.

    PubMed

    Tönshoff, H K; Jung, M; Männel, S; Rietz, W

    2000-07-01

    The systems for in-process quality assurance offer the possibility of estimating the workpiece quality during machining. Especially for finishing processes like grinding or turning of hardened steels, it is important to control the process continuously in order to avoid rejects and refinishing. This paper describes the use of on-line monitoring systems with process-integrated measurement of acoustic emission to evaluate hard turning and grinding processes. The correlation between acoustic emission signals and subsurface integrity is determined to analyse the progression of the processes and the workpiece quality.

  4. Intelligent Signal Processing for Detection System Optimization

    SciTech Connect

    Fu, C Y; Petrich, L I; Daley, P F; Burnham, A K

    2004-06-18

    A wavelet-neural network signal processing method has demonstrated approximately tenfold improvement in the detection limit of various nitrogen and phosphorus compounds over traditional signal-processing methods in analyzing the output of a thermionic detector attached to the output of a gas chromatograph. A blind test was conducted to validate the lower detection limit. All fourteen of the compound spikes were detected when above the estimated threshold, including all three within a factor of two above. In addition, two of six were detected at levels 1/2 the concentration of the nominal threshold. We would have had another two correct hits if we had allowed human intervention to examine the processed data. One apparent false positive in five nulls was traced to a solvent impurity, whose presence was identified by running a solvent aliquot evaporated to 1% residual volume, while the other four nulls were properly classified. We view this signal processing method as broadly applicable in analytical chemistry, and we advocate that advanced signal processing methods be applied as directly as possible to the raw detector output so that less discriminating preprocessing and post-processing does not throw away valuable signal.

  5. Intelligent Signal Processing for Detection System Optimization

    SciTech Connect

    Fu, C Y; Petrich, L I; Daley, P F; Burnham, A K

    2004-12-05

    A wavelet-neural network signal processing method has demonstrated approximately tenfold improvement over traditional signal-processing methods for the detection limit of various nitrogen and phosphorus compounds from the output of a thermionic detector attached to a gas chromatograph. A blind test was conducted to validate the lower detection limit. All fourteen of the compound spikes were detected when above the estimated threshold, including all three within a factor of two above the threshold. In addition, two of six spikes were detected at levels of 1/2 the concentration of the nominal threshold. Another two of the six would have been detected correctly if we had allowed human intervention to examine the processed data. One apparent false positive in five nulls was traced to a solvent impurity, whose presence was subsequently identified by analyzing a solvent aliquot evaporated to 1% residual volume, while the other four nulls were properly classified. We view this signal processing method as broadly applicable in analytical chemistry, and we advocate that advanced signal processing methods should be applied as directly as possible to the raw detector output so that less discriminating preprocessing and post-processing does not throw away valuable signal.

  6. Sonar signal processing using probabilistic signal and ocean environmental models.

    PubMed

    Culver, R Lee; Camin, H John

    2008-12-01

    Acoustic signals propagating through the ocean are refracted, scattered, and attenuated by the ocean volume and boundaries. Many aspects of how the ocean affects acoustic propagation are understood, such that the characteristics of a received signal can often be predicted with some degree of certainty. However, acoustic ocean parameters vary with time and location in a manner that is not, and cannot be, precisely known; some uncertainty will always remain. For this reason, the characteristics of the received signal can never be precisely predicted and must be described in probabilistic terms. A signal processing structure recently developed relies on knowledge of the ocean environment to predict the statistical characteristics of the received signal, and incorporates this description into the processor in order to detect and classify targets. Acoustic measurements at 250 Hz from the 1996 Strait of Gibraltar Acoustic Monitoring Experiment are used to illustrate how the processor utilizes environmental data to classify source depth and to underscore the importance of environmental model fidelity and completeness.

  7. Calibration of Correlation Radiometers Using Pseudo-Random Noise Signals

    PubMed Central

    Pérez, Isaac Ramos; Bosch-Lluis, Xavi; Camps, Adriano; Alvarez, Nereida Rodriguez; Hernandez, Juan Fernando Marchán; Domènech, Enric Valencia; Vernich, Carlos; de la Rosa, Sonia; Pantoja, Sebastián

    2009-01-01

    The calibration of correlation radiometers, and particularly aperture synthesis interferometric radiometers, is a critical issue to ensure their performance. Current calibration techniques are based on the measurement of the cross-correlation of receivers’ outputs when injecting noise from a common noise source requiring a very stable distribution network. For large interferometric radiometers this centralized noise injection approach is very complex from the point of view of mass, volume and phase/amplitude equalization. Distributed noise injection techniques have been proposed as a feasible alternative, but are unable to correct for the so-called “baseline errors” associated with the particular pair of receivers forming the baseline. In this work it is proposed the use of centralized Pseudo-Random Noise (PRN) signals to calibrate correlation radiometers. PRNs are sequences of symbols with a long repetition period that have a flat spectrum over a bandwidth which is determined by the symbol rate. Since their spectrum resembles that of thermal noise, they can be used to calibrate correlation radiometers. At the same time, since these sequences are deterministic, new calibration schemes can be envisaged, such as the correlation of each receiver’s output with a baseband local replica of the PRN sequence, as well as new distribution schemes of calibration signals. This work analyzes the general requirements and performance of using PRN sequences for the calibration of microwave correlation radiometers, and particularizes the study to a potential implementation in a large aperture synthesis radiometer using an optical distribution network. PMID:22454576

  8. Digital Processing of Weak Signals Buried in Noise

    NASA Astrophysics Data System (ADS)

    Emerson, Darrel

    This article describes the use of digital signal processing to pull the AMSAT AO-13 ZRO test signal out of the noise. In the ZRO tests, a signal is transmitted from the Oscar 13 satellite at progressively lower power levels, in 3 dB steps. The challenge is to decode successfully the weakest possible signal. The signal from the receiver audio was digitized using a Sound Blaster card, then filtered with a modified FFT routine. The modification was to allow the pre-detection filter to follow the slowly drifting signal. After using the matched, sliding filter before detection, the post-detection signal was passed through another matched filter. Finally, a cross-correlation technique comparing the detected, filtered signal with every possible combination of ZRO signal was applied, taking also into account a gradual drift of CW sending speed. The final, statistically most probable, solution turned out to be correct. This gave the only successful detection of level A transmissions from Oscar 13 so far (Aug 1996.) The extensive digital processing partly made up for the relatively poor receiving antenna; a 10-element 146 MHz Yagi, part of the Cushcraft AOP-1 combination.

  9. Surveillance of industrial processes with correlated parameters

    DOEpatents

    White, Andrew M.; Gross, Kenny C.; Kubic, William L.; Wigeland, Roald A.

    1996-01-01

    A system and method for surveillance of an industrial process. The system and method includes a plurality of sensors monitoring industrial process parameters, devices to convert the sensed data to computer compatible information and a computer which executes computer software directed to analyzing the sensor data to discern statistically reliable alarm conditions. The computer software is executed to remove serial correlation information and then calculate Mahalanobis distribution data to carry out a probability ratio test to determine alarm conditions.

  10. Surveillance of industrial processes with correlated parameters

    DOEpatents

    White, A.M.; Gross, K.C.; Kubic, W.L.; Wigeland, R.A.

    1996-12-17

    A system and method for surveillance of an industrial process are disclosed. The system and method includes a plurality of sensors monitoring industrial process parameters, devices to convert the sensed data to computer compatible information and a computer which executes computer software directed to analyzing the sensor data to discern statistically reliable alarm conditions. The computer software is executed to remove serial correlation information and then calculate Mahalanobis distribution data to carry out a probability ratio test to determine alarm conditions. 10 figs.

  11. Overview of Digital Signal Processing Theory

    DTIC Science & Technology

    1975-05-20

    of digital integrated- circuit hardware elements along with their extremely high reliability, maintainability, and repeatability of performance have...limited by large-signal-performance and power limitations of circuit components. In the implementation of digital signal process- ing systems there...E. Polak and E. Wong, Notes For A First Course On Linear Systems, Van Nostrand Reinhold Company, New York, 1970. 2. C.A. Desoer , Notes For A

  12. Novel sonar signal processing tool using Shannon entropy

    SciTech Connect

    Quazi, A.H.

    1996-06-01

    Traditionally, conventional signal processing extracts information from sonar signals using amplitude, signal energy or frequency domain quantities obtained using spectral analysis techniques. The object is to investigate an alternate approach which is entirely different than that of traditional signal processing. This alternate approach is to utilize the Shannon entropy as a tool for the processing of sonar signals with emphasis on detection, classification, and localization leading to superior sonar system performance. Traditionally, sonar signals are processed coherently, semi-coherently, and incoherently, depending upon the a priori knowledge of the signals and noise. Here, the detection, classification, and localization technique will be based on the concept of the entropy of the random process. Under a constant energy constraint, the entropy of a received process bearing finite number of sample points is maximum when hypothesis H{sub 0} (that the received process consists of noise alone) is true and decreases when correlated signal is present (H{sub 1}). Therefore, the strategy used for detection is: (I) Calculate the entropy of the received data; then, (II) compare the entropy with the maximum value; and, finally, (III) make decision: H{sub 1} is assumed if the difference is large compared to pre-assigned threshold and H{sub 0} is otherwise assumed. The test statistics will be different between entropies under H{sub 0} and H{sub 1}. Here, we shall show the simulated results for detecting stationary and non-stationary signals in noise, and results on detection of defects in a Plexiglas bar using an ultrasonic experiment conducted by Hughes. {copyright} {ital 1996 American Institute of Physics.}

  13. Two-dimensional signal reconstruction: The correlation sampling method

    SciTech Connect

    Roman, H. E.

    2007-12-15

    An accurate approach for reconstructing a time-dependent two-dimensional signal from non-synchronized time series recorded at points located on a grid is discussed. The method, denoted as correlation sampling, improves the standard conditional sampling approach commonly employed in the study of turbulence in magnetoplasma devices. Its implementation is illustrated in the case of an artificial time-dependent signal constructed using a fractal algorithm that simulates a fluctuating surface. A statistical method is also discussed for distinguishing coherent (i.e., collective) from purely random (noisy) behavior for such two-dimensional fluctuating phenomena.

  14. A unified approach to sparse signal processing

    NASA Astrophysics Data System (ADS)

    Marvasti, Farokh; Amini, Arash; Haddadi, Farzan; Soltanolkotabi, Mahdi; Khalaj, Babak Hossein; Aldroubi, Akram; Sanei, Saeid; Chambers, Janathon

    2012-12-01

    A unified view of the area of sparse signal processing is presented in tutorial form by bringing together various fields in which the property of sparsity has been successfully exploited. For each of these fields, various algorithms and techniques, which have been developed to leverage sparsity, are described succinctly. The common potential benefits of significant reduction in sampling rate and processing manipulations through sparse signal processing are revealed. The key application domains of sparse signal processing are sampling, coding, spectral estimation, array processing, component analysis, and multipath channel estimation. In terms of the sampling process and reconstruction algorithms, linkages are made with random sampling, compressed sensing, and rate of innovation. The redundancy introduced by channel coding in finite and real Galois fields is then related to over-sampling with similar reconstruction algorithms. The error locator polynomial (ELP) and iterative methods are shown to work quite effectively for both sampling and coding applications. The methods of Prony, Pisarenko, and MUltiple SIgnal Classification (MUSIC) are next shown to be targeted at analyzing signals with sparse frequency domain representations. Specifically, the relations of the approach of Prony to an annihilating filter in rate of innovation and ELP in coding are emphasized; the Pisarenko and MUSIC methods are further improvements of the Prony method under noisy environments. The iterative methods developed for sampling and coding applications are shown to be powerful tools in spectral estimation. Such narrowband spectral estimation is then related to multi-source location and direction of arrival estimation in array processing. Sparsity in unobservable source signals is also shown to facilitate source separation in sparse component analysis; the algorithms developed in this area such as linear programming and matching pursuit are also widely used in compressed sensing. Finally

  15. Nonlinear Real-Time Optical Signal Processing.

    DTIC Science & Technology

    1984-10-01

    DTIC ELECTE I B IIMAGE PROCESSING INSTITUTE 84 11 26 107 UNCLASSIFIED SECURITY CLASSIFICATION OF THIS PAGE (When Dota Entered), REPORT DOCUMENTATION...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...RDepartment of Electrical Engineering Image Processing institute University of Southern California University Park-MC 0272 Los Angeles, California

  16. Bacteriorhodopsin Film For Processing SAR Signals

    NASA Technical Reports Server (NTRS)

    Yu, Jeffrey W.; Chao, Tien-Hsin; Margalit, Ruth; Cheng, Li-Jen

    1992-01-01

    "Instant" photographic film based on semisynthetic retinal pigment bacteriorhodopsin proposed for optical processing of synthetic-aperture-radar (SAR) signals. Input image recorded on film by laser operating at writing wavelength of bacteriorhodopsin, and output image recorded on computer by standard frame-grabber. Because it requires no chemical development, enables processing in nearly real time. Fast response and high resolution well suited for application. Film reusable, with concomitant reduction in cost of SAR processing.

  17. Methodological Framework for Estimating the Correlation Dimension in HRV Signals

    PubMed Central

    Bolea, Juan; Laguna, Pablo; Remartínez, José María; Rovira, Eva; Navarro, Augusto; Bailón, Raquel

    2014-01-01

    This paper presents a methodological framework for robust estimation of the correlation dimension in HRV signals. It includes (i) a fast algorithm for on-line computation of correlation sums; (ii) log-log curves fitting to a sigmoidal function for robust maximum slope estimation discarding the estimation according to fitting requirements; (iii) three different approaches for linear region slope estimation based on latter point; and (iv) exponential fitting for robust estimation of saturation level of slope series with increasing embedded dimension to finally obtain the correlation dimension estimate. Each approach for slope estimation leads to a correlation dimension estimate, called D^2, D^2⊥, and D^2max. D^2 and D^2max estimate the theoretical value of correlation dimension for the Lorenz attractor with relative error of 4%, and D^2⊥ with 1%. The three approaches are applied to HRV signals of pregnant women before spinal anesthesia for cesarean delivery in order to identify patients at risk for hypotension. D^2 keeps the 81% of accuracy previously described in the literature while D^2⊥ and D^2max approaches reach 91% of accuracy in the same database. PMID:24592284

  18. Analysis of physiological signals using state space correlation entropy.

    PubMed

    Tripathy, Rajesh Kumar; Deb, Suman; Dandapat, Samarendra

    2017-02-01

    In this letter, the authors propose a new entropy measure for analysis of time series. This measure is termed as the state space correlation entropy (SSCE). The state space reconstruction is used to evaluate the embedding vectors of a time series. The SSCE is computed from the probability of the correlations of the embedding vectors. The performance of SSCE measure is evaluated using both synthetic and real valued signals. The experimental results reveal that, the proposed SSCE measure along with SVM classifier have sensitivity value of 91.60%, which is higher than the performance of both sample entropy and permutation entropy features for detection of shockable ventricular arrhythmia.

  19. Designer cell signal processing circuits for biotechnology.

    PubMed

    Bradley, Robert W; Wang, Baojun

    2015-12-25

    Microorganisms are able to respond effectively to diverse signals from their environment and internal metabolism owing to their inherent sophisticated information processing capacity. A central aim of synthetic biology is to control and reprogramme the signal processing pathways within living cells so as to realise repurposed, beneficial applications ranging from disease diagnosis and environmental sensing to chemical bioproduction. To date most examples of synthetic biological signal processing have been built based on digital information flow, though analogue computing is being developed to cope with more complex operations and larger sets of variables. Great progress has been made in expanding the categories of characterised biological components that can be used for cellular signal manipulation, thereby allowing synthetic biologists to more rationally programme increasingly complex behaviours into living cells. Here we present a current overview of the components and strategies that exist for designer cell signal processing and decision making, discuss how these have been implemented in prototype systems for therapeutic, environmental, and industrial biotechnological applications, and examine emerging challenges in this promising field.

  20. Designer cell signal processing circuits for biotechnology

    PubMed Central

    Bradley, Robert W.; Wang, Baojun

    2015-01-01

    Microorganisms are able to respond effectively to diverse signals from their environment and internal metabolism owing to their inherent sophisticated information processing capacity. A central aim of synthetic biology is to control and reprogramme the signal processing pathways within living cells so as to realise repurposed, beneficial applications ranging from disease diagnosis and environmental sensing to chemical bioproduction. To date most examples of synthetic biological signal processing have been built based on digital information flow, though analogue computing is being developed to cope with more complex operations and larger sets of variables. Great progress has been made in expanding the categories of characterised biological components that can be used for cellular signal manipulation, thereby allowing synthetic biologists to more rationally programme increasingly complex behaviours into living cells. Here we present a current overview of the components and strategies that exist for designer cell signal processing and decision making, discuss how these have been implemented in prototype systems for therapeutic, environmental, and industrial biotechnological applications, and examine emerging challenges in this promising field. PMID:25579192

  1. Phase sensitive Raman process with correlated seeds

    SciTech Connect

    Chen, Bing; Qiu, Cheng; Chen, L. Q. Zhang, Kai; Guo, Jinxian; Yuan, Chun-Hua; Zhang, Weiping; Ou, Z. Y.

    2015-03-16

    A phase sensitive Raman scattering was experimentally demonstrated by injecting a Stokes light seed into an atomic ensemble, whose internal state is set in such a way that it is coherent with the input Stokes seed. Such phase sensitive characteristic is a result of interference effect due to the phase correlation between the injected Stokes light field and the internal state of the atomic ensemble in the Raman process. Furthermore, the constructive interference leads to a Raman efficiency larger than other kinds of Raman processes such as stimulated Raman process with Stokes seed injection alone or uncorrelated light-atom seeding. It may find applications in precision spectroscopy, quantum optics, and precise measurement.

  2. 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.

  3. Array algebra estimation in signal processing

    NASA Astrophysics Data System (ADS)

    Rauhala, U. A.

    A general theory of linear estimators called array algebra estimation is interpreted in some terms of multidimensional digital signal processing, mathematical statistics, and numerical analysis. The theory has emerged during the past decade from the new field of a unified vector, matrix and tensor algebra called array algebra. The broad concepts of array algebra and its estimation theory cover several modern computerized sciences and technologies converting their established notations and terminology into one common language. Some concepts of digital signal processing are adopted into this language after a review of the principles of array algebra estimation and its predecessors in mathematical surveying sciences.

  4. Processing oscillatory signals by incoherent feedforward loops

    NASA Astrophysics Data System (ADS)

    Zhang, Carolyn; Wu, Feilun; Tsoi, Ryan; Shats, Igor; You, Lingchong

    From the timing of amoeba development to the maintenance of stem cell pluripotency,many biological signaling pathways exhibit the ability to differentiate between pulsatile and sustained signals in the regulation of downstream gene expression.While networks underlying this signal decoding are diverse,many are built around a common motif, the incoherent feedforward loop (IFFL),where an input simultaneously activates an output and an inhibitor of the output.With appropriate parameters,this motif can generate temporal adaptation,where the system is desensitized to a sustained input.This property serves as the foundation for distinguishing signals with varying temporal profiles.Here,we use quantitative modeling to examine another property of IFFLs,the ability to process oscillatory signals.Our results indicate that the system's ability to translate pulsatile dynamics is limited by two constraints.The kinetics of IFFL components dictate the input range for which the network can decode pulsatile dynamics.In addition,a match between the network parameters and signal characteristics is required for optimal ``counting''.We elucidate one potential mechanism by which information processing occurs in natural networks with implications in the design of synthetic gene circuits for this purpose. This work was partially supported by the National Science Foundation Graduate Research Fellowship (CZ).

  5. Multitime correlation functions in nonclassical stochastic processes

    NASA Astrophysics Data System (ADS)

    Krumm, F.; Sperling, J.; Vogel, W.

    2016-06-01

    A general method is introduced for verifying multitime quantum correlations through the characteristic function of the time-dependent P functional that generalizes the Glauber-Sudarshan P function. Quantum correlation criteria are derived which identify quantum effects for an arbitrary number of points in time. The Magnus expansion is used to visualize the impact of the required time ordering, which becomes crucial in situations when the interaction problem is explicitly time dependent. We show that the latter affects the multi-time-characteristic function and, therefore, the temporal evolution of the nonclassicality. As an example, we apply our technique to an optical parametric process with a frequency mismatch. The resulting two-time-characteristic function yields full insight into the two-time quantum correlation properties of such a system.

  6. Processing of the laser Doppler velocimeter signals

    NASA Technical Reports Server (NTRS)

    Meyers, J. F.; Feller, W. V.

    1973-01-01

    The laser Doppler velocimeter (LDV) is a probeless technique that provides a remote measurement of mean and fluctuating velocities. The measurement is actually obtained from small particles embedded in the flow which scatter light from an illuminating laser beam interference pattern. A portion of this scattered light is collected by a photomultiplier which yields an electronic signal whose frequency is directly proportional to the velocity of the small particles. The purpose of this paper is to describe and critically compare three techniques most used to process this electronic signal. These techniques are: (1) spectrum analyzer - a frequency scanning filter (frequency domain instrument), (2) wide-band frequency tracker - a frequency lock loop (frequency domain instrument), and (3) high-speed frequency counter - an interval timer (time domain instrument). The study determines the ability of each technique to process the LDV signal and yield velocity data to be used in determining the flow characteristics.

  7. Spatiotemporal signal processing for blind separation of multichannel signals

    NASA Astrophysics Data System (ADS)

    Tugnait, Jitendra K.

    1996-06-01

    This paper is concerned with the problem of blind separation of independent signals (sources) from their linear convolutive mixtures. The problem consists of recovering the sources up to shaping filters from the observations of multiple-input multiple-output (MIMO) system output. The various signals are assumed to be linear but not necessarily i.i.d. (independent and identically distributed). The problem is cast into the framework of spatio-temporal equalization and estimation of the matrix impulse response function of MIMO channels (systems). An iterative, Godard cost based approach is considered for spatio-temporal equalization and MIMO impulse response estimation. Stationary points of the cost function are investigated and it is shown that all stable local minima correspond to desirable minima when doubly infinite equalizers are used. Analysis is also provided for the case when finite-length equalizers exist. The various input sequences are extracted and cancelled one-by-one. The matrix impulse response is then obtained by cross-correlating the extracted inputs with the observed outputs. Identifiability conditions are analyzed. Computer simulation examples are presented to illustrate the proposed approach.

  8. Displays, memories, and signal processing: A compilation

    NASA Technical Reports Server (NTRS)

    1975-01-01

    Articles on electronics systems and techniques were presented. The first section is on displays and other electro-optical systems; the second section is devoted to signal processing. The third section presented several new memory devices for digital equipment, including articles on holographic memories. The latest patent information available is also given.

  9. Signal processing aspects of windshear detection

    NASA Technical Reports Server (NTRS)

    Aalfs, David D.; Baxa, Ernest G., Jr.; Bracalente, Emedio M.

    1993-01-01

    Low-altitude windshear (LAWS) has been identified as a major hazard to aircraft, particularly during takeoff and landing. The Federal Aviation Administration (FAA) has been involved with developing technology to detect LAWS. A key element in this technology is high resolution pulse Doppler weather radar equipped with signal and data processing to provide timely information about possible hazardous conditions.

  10. A Virtual Laboratory for Digital Signal Processing

    ERIC Educational Resources Information Center

    Dow, Chyi-Ren; Li, Yi-Hsung; Bai, Jin-Yu

    2006-01-01

    This work designs and implements a virtual digital signal processing laboratory, VDSPL. VDSPL consists of four parts: mobile agent execution environments, mobile agents, DSP development software, and DSP experimental platforms. The network capability of VDSPL is created by using mobile agent and wrapper techniques without modifying the source code…

  11. Distributed radiofrequency signal processing using multicore fibers

    NASA Astrophysics Data System (ADS)

    Garcia, S.; Gasulla, I.

    2016-11-01

    Next generation fiber-wireless communication paradigms will require new technologies to address the current limitations to massive capacity, connectivity and flexibility. Multicore optical fibers, which were conceived for high-capacity digital communications, can bring numerous advantages to fiber-wireless radio access architectures. Besides radio over fiber parallel distribution and multiple antenna connectivity, multicore fibers can implement, at the same time, a variety of broadband processing functionalities for microwave and millimeter-wave signals. This approach leads to the novel concept of "fiber-distributed signal processing". In particular, we capitalize on the spatial parallelism inherent to multicore fibers to implement a broadband tunable true time delay line, which is the basis of multiple processing applications such as signal filtering, arbitrary waveform generation and squint-free radio beamsteering. We present the design of trench-assisted heterogeneous multicore fibers composed of cores featuring individual spectral group delays and chromatic dispersion profiles. Besides fulfilling the requirements for true time delay line operation, the MCFs are optimized in terms of higher-order dispersion, crosstalk and bend sensitivity. Microwave photonics signal processing will benefit from the performance stability, 2D operation versatility and compactness brought by the reported fiberintegrated solution.

  12. Photon correlations through Raman virtual processes

    NASA Astrophysics Data System (ADS)

    de Melo E Souza, Reinaldo; Saraiva, Andre; Koiller, Belita

    In Raman inelastic scattering phonons are either absorbed or created, in what is respectively called an anti-Stokes (aS) or a Stokes (S) process. While these two processes are generally uncorrelated, it is possible that the same phonon generated by S is subsequently absorbed by aS. This two photon process is referred to as SaS. In a standard Raman process, conservation of energy forbids virtual phonons to play a role. However, in a SaS process these virtual phonons may be relevant as long as their lifetimes exceed the interval between the two scatterings. We derive the effective photon-photon interaction mediated by the phonon field. The effective hamiltonian is analogue to the one present in BCS superconductivity. The difference lies in the nature of the particles involved - since photons are bosons, there is no Fermi sea instability and no pair condensation. Still it is possible to obtain an attractive photon-photon interaction. Finally, we propose an experiment to detect the correlated photons emerging from a semiconductor. We pinpoint the material properties that might enhance this effect and discuss the possible technological applications of this idea as a correlated photon source. This work is part of the Brazilian National Institute for Science and Technology on Quantum Information. We also acknowledge partial support from the Brazilian agencies FAPERJ, CNPq and CAPES.

  13. An ultrasonic device for signal processing

    NASA Astrophysics Data System (ADS)

    Kulakov, S. V.; Leks, A. G.; Semenov, S. P.; Ulyanov, G. K.

    1985-11-01

    The invention concerns the field of radioengineering and can be used in analog processors of the signals of phased antenna arrays. There are familiar devices for processing the signals of phased antenna arrays. However these are large in size, structurally complicated, and contain expensive parts. In the proposed device, for the purpose of simplification and cheapening the design and reducing the dimensions, the counting system is in the form of a receiving acoustical array, the elements of which are hooked up to a television-type indicator.

  14. Invariance algorithms for processing NDE signals

    NASA Astrophysics Data System (ADS)

    Mandayam, Shreekanth; Udpa, Lalita; Udpa, Satish S.; Lord, William

    1996-11-01

    Signals that are obtained in a variety of nondestructive evaluation (NDE) processes capture information not only about the characteristics of the flaw, but also reflect variations in the specimen's material properties. Such signal changes may be viewed as anomalies that could obscure defect related information. An example of this situation occurs during in-line inspection of gas transmission pipelines. The magnetic flux leakage (MFL) method is used to conduct noninvasive measurements of the integrity of the pipe-wall. The MFL signals contain information both about the permeability of the pipe-wall and the dimensions of the flaw. Similar operational effects can be found in other NDE processes. This paper presents algorithms to render NDE signals invariant to selected test parameters, while retaining defect related information. Wavelet transform based neural network techniques are employed to develop the invariance algorithms. The invariance transformation is shown to be a necessary pre-processing step for subsequent defect characterization and visualization schemes. Results demonstrating the successful application of the method are presented.

  15. Digital signal processing for ionospheric propagation diagnostics

    NASA Astrophysics Data System (ADS)

    Rino, Charles L.; Groves, Keith M.; Carrano, Charles S.; Gunter, Jacob H.; Parris, Richard T.

    2015-08-01

    For decades, analog beacon satellite receivers have generated multifrequency narrowband complex data streams that could be processed directly to extract total electron content (TEC) and scintillation diagnostics. With the advent of software-defined radio, modern digital receivers generate baseband complex data streams that require intermediate processing to extract the narrowband modulation imparted to the signal by ionospheric structure. This paper develops and demonstrates a processing algorithm for digital beacon satellite data that will extract TEC and scintillation components. For algorithm evaluation, a simulator was developed to generate noise-limited multifrequency complex digital signal realizations with representative orbital dynamics and propagation disturbances. A frequency-tracking procedure is used to capture the slowly changing frequency component. Dynamic demodulation against the low-frequency estimate captures the scintillation. The low-frequency reference can be used directly for dual-frequency TEC estimation.

  16. Ultrasonic correlator versus signal averager as a signal to noise enhancement instrument

    NASA Technical Reports Server (NTRS)

    Kishoni, Doron; Pietsch, Benjamin E.

    1990-01-01

    Ultrasonic inspection of thick and attenuating materials is hampered by the reduce amplitudes of the propagated waves to a degree that the noise is too high to enable meaningful interpretation of the data. In order to overcome the low signal to noise ratio (S/N), a correlation technique has been developed. In this method, a continuous pseudo-random pattern generated digitally is transmitted and detected by piezoelectric transducers. A correlation is performed in the instrument between the received signal and a variable delayed image of the transmitted one. The result is shown to be proportional to the impulse response of the investigated material, analogous to a signal received from a pulsed system, with an improved S/N ratio. The degree of S/N enhancement depends on the sweep rate. The correlator is described, and it is compared to the method of enhancing S/N ratio by averaging the signals. The similarities and differences between the two are highlighted and the potential advantage of the correlator system is explained.

  17. Ultrasonic correlator versus signal averager as a signal to noise enhancement instrument

    NASA Technical Reports Server (NTRS)

    Kishoni, Doron; Pietsch, Benjamin E.

    1989-01-01

    Ultrasonic inspection of thick and attenuating materials is hampered by the reduced amplitudes of the propagated waves to a degree that the noise is too high to enable meaningful interpretation of the data. In order to overcome the low Signal to Noise (S/N) ratio, a correlation technique has been developed. In this method, a continuous pseudo-random pattern generated digitally is transmitted and detected by piezoelectric transducers. A correlation is performed in the instrument between the received signal and a variable delayed image of the transmitted one. The result is shown to be proportional to the impulse response of the investigated material, analogous to a signal received from a pulsed system, with an improved S/N ratio. The degree of S/N enhancement depends on the sweep rate. This paper describes the correlator, and compares it to the method of enhancing S/N ratio by averaging the signals. The similarities and differences between the two are highlighted and the potential advantage of the correlator system is explained.

  18. The atmosphere- and hydrosphere-correlated signals in GPS observations

    NASA Astrophysics Data System (ADS)

    Bogusz, Janusz; Boy, Jean-Paul; Klos, Anna; Figurski, Mariusz

    2015-04-01

    analysis of satellite data was performed twofold: firstly, the time series from network solution (NS) processed in Bernese 5.0 software by the Military University of Technology EPN Local Analysis Centre, secondly, the ones from PPP (Precise Point Positioning) from JPL (Jet Propulsion Laboratory) processing in Gipsy-Oasis were analyzed. Both were modelled with wavelet decomposition with Meyer orthogonal mother wavelet. Here, nine levels of decomposition were applied and eighth detail of it was interpreted as changes close to one year. In this way, both NS and PPP time series where presented as curves with annual period with amplitudes and phases changeable in time. The same analysis was performed for atmospheric (ATM) and hydrospheric (HYDR) models. All annual curves (modelled from NS, PPP, ATM and HYDR) were then compared to each other to investigate whether GPS observations contain the atmosphere and hydrosphere correlated signals and in what way the amplitudes of them may disrupt the GPS time series.

  19. Exascale Signal Processing for Millimeter-Wavelength Interferometers

    NASA Astrophysics Data System (ADS)

    Hawkins, David

    2014-04-01

    The Exascale Radio Astronomy conference is a platform for scientists and engineers to discuss the challenges of "big data" with their peers in high-performance computing and industry. The "big data" challenge facing interferometers (arrays of radio telescopes) is the volume of antenna-based and cross-correlation data these instruments produce. Interferometers operating at millimeter wavelengths typically have between 10 and 100 antennas, with receiver bandwidths in excess of 60GHz per antenna now considered feasible (via four 15GHz signals from dual-polarization, sideband separating mixers). This talk presents details on the state-of-the art in wideband analog-to-digital converters, antenna-based signal processing, data transport, and correlation processing, along with the challenges faced when implemented these systems.

  20. Synthesizing oncogenic signal-processing systems that function as both "signal counters" and "signal blockers" in cancer cells.

    PubMed

    Liu, Yuchen; Huang, Weiren; Zhou, Dexi; Han, Yonghua; Duan, Yonggang; Zhang, Xiaoyue; Zhang, Hu; Jiang, Zhimao; Gui, Yaoting; Cai, Zhiming

    2013-07-01

    RNA-protein interaction plays a significant role in regulating eukaryotic translation. This phenomenon raises questions about the ability of artificial biological systems to take the advantage of protein-RNA interaction. Here, we designed an oncogenic signal-processing system expressing both a Renilla luciferase reporter gene controlled by RNA-protein interaction in its 5'-untranslated region (5'-UTR) and a Firefly luciferase normalization gene. To test the ability of the designed system, we then constructed vectors targeting the nuclear factor-κB (NF-κB) or the β-catenin signal. We found that the inhibition (%) of luciferase expression was correlated to the targeted protein content, allowing quantitative measurement of oncogenic signal intensity in cancer cells. The systems inhibited the expression of oncogenic signal downstream genes and induced bladder cancer cell proliferation inhibition and apoptosis without affecting normal urothelial cells. Compared to traditional methods (ELISA and quantitative immunoblotting), the bio-systems provided highly accurate, consistent, and reproducible quantification of protein signals and were able to discriminate between cancerous and non-cancerous cells. In conclusion, the synthetic systems function as both "signal counters" and "signal blockers" in cancer cells. This approach provides a synthetic biology platform for oncogenic signal measurement and cancer treatment.

  1. Processing Electromyographic Signals to Recognize Words

    NASA Technical Reports Server (NTRS)

    Jorgensen, C. C.; Lee, D. D.

    2009-01-01

    A recently invented speech-recognition method applies to words that are articulated by means of the tongue and throat muscles but are otherwise not voiced or, at most, are spoken sotto voce. This method could satisfy a need for speech recognition under circumstances in which normal audible speech is difficult, poses a hazard, is disturbing to listeners, or compromises privacy. The method could also be used to augment traditional speech recognition by providing an additional source of information about articulator activity. The method can be characterized as intermediate between (1) conventional speech recognition through processing of voice sounds and (2) a method, not yet developed, of processing electroencephalographic signals to extract unspoken words directly from thoughts. This method involves computational processing of digitized electromyographic (EMG) signals from muscle innervation acquired by surface electrodes under a subject's chin near the tongue and on the side of the subject s throat near the larynx. After preprocessing, digitization, and feature extraction, EMG signals are processed by a neural-network pattern classifier, implemented in software, that performs the bulk of the recognition task as described.

  2. Hot topics: Signal processing in acoustics

    NASA Astrophysics Data System (ADS)

    Candy, James

    2002-05-01

    Signal processing represents a technology that provides the mechanism to extract the desired information from noisy acoustical measurement data. The desired result can range from extracting a single number like sound intensity level in the case of marine mammals to the seemingly impossible task of imaging the complex bottom in a hostile ocean environment. Some of the latest approaches to solving acoustical processing problems including sophisticated Bayesian processors in architectural acoustics, iterative flaw removal processing for non-destructive evaluation, time-reversal imaging for buried objects and time-reversal receivers in communications as well as some of the exciting breakthroughs using so-called blind processing techniques for deconvolution are discussed. Processors discussed range from the simple to the sophisticated as dictated by the particular application. It is shown how processing techniques are crucial to extracting the required information for success in the underlying application.

  3. Nonlinear Cochlear Signal Processing and Phoneme Perception

    NASA Astrophysics Data System (ADS)

    Allen, Jont B.; Régnier, Marion; Phatak, Sandeep; Li, Feipeng

    2009-02-01

    The most important communication signal is human speech. It is helpful to think of speech communication in terms of Claude Shannon's information theory channel model. When thus viewed, it immediately becomes clear that the most complex part of speech communication channel is in auditory system (the receiver). In my opinion, even after years of work, relatively little is know about how the human auditory system decodes speech. Given cochlear damaged, speech scores are greatly reduced, even with tiny amounts of noise. The exact reasons for this SNR-loss presently remain unclear, but I speculate that the source of this must be cochlear outer hair cell temporal processing, not central processing. Specifically, "temporal edge enhancement" of the speech signal and forward masking could easily be modified in such ears, leading to SNR-Loss. What ever the reason, SNR-Loss is the key problem that needs to be fully researched.

  4. Correlation Between Eddy Current Signal Noise and Peened Surface Roughness

    SciTech Connect

    Wendt, S. E.; Hentscher, S. R.; Raithel, D. C.; Nakagawa, N.

    2007-03-21

    For advanced uses of eddy current (EC) NDE models in, e.g., model-assisted POD, there is a need to understand the origin of EC noise sources so that noise estimations can be made for a given set of inspection conditions, in addition to defect signal predictions. This paper focuses on the material-oriented noise sources that exhibit some universality when isolated from electrical and mechanical noises. Specifically, we report on experimental measurements that show explicit correlations between surface roughness and EC noise as seen in post-peen EC measurements of shot-peened roughness specimens. The samples are 3''-by-3'' Inconel 718 and Ti-6A1-4V blocks, pre-polished and shot-peened at Almen intensities ranging from a low of 4N to as high as 16A, created by smaller ({approx}350 {mu}m) and larger ({approx}1 mm) diameter zirconium oxide shots. Strong correlations are observed between the Almen intensities and the measured surface roughness. The EC noise correlates equally strongly with the Almen intensities for the superalloy specimens. The correlation for the Ti-alloy samples is only apparent at higher intensities, while being weak for lower intensities, indicating the grain noise dominance for smoother surfaces.

  5. Signal Detection for Pareto Renewal Processes.

    DTIC Science & Technology

    1982-10-01

    SThe Pareto distribution itself was, of course, introduced by Vilfredo Pareto (1648 - 1923). (See Reference [221). This distribution has been used and...Bull. Calcutta Statist. Assoc., 7, 115-123. 22. Pareto , Vilfredo (1897). Cours d’Economie Politique. Lausanne and Paris: Rouge and Cie. 23. Park, C...STANDARDS-193-A 0 .1 / - r- ,---------------,- 8-82 SERIES IN STATISTICS AND BIOSTATISTICS SIGNAL DETECTION FOR PARETO RENEWAL PROCESSES C.B. BELL, R

  6. Neural Networks for Signal Processing and Control

    NASA Astrophysics Data System (ADS)

    Hesselroth, Ted Daniel

    cortex by the application of lateral interactions during the learning phase. The organization of the mature network is compared to that found in the macaque monkey by several analytical tests. The capacity of the network to process images is investigated. By a method of reconstructing the input images in terms of V1 activities, the simulations show that images can be faithfully represented in V1 by the proposed network. The signal-to-noise ratio of the image is improved by the representation, and compression ratios of well over two-hundred are possible. Lateral interactions between V1 neurons sharpen their orientational tuning. We further study the dynamics of the processing, showing that the rate of decrease of the error of the reconstruction is maximized for the receptive fields used. Lastly, we employ a Fokker-Planck equation for a more detailed prediction of the error value vs. time. The Fokker-Planck equation for an underdamped system with a driving force is derived, yielding an energy-dependent diffusion coefficient which is the integral of the spectral densities of the force and the velocity of the system. The theory is applied to correlated noise activation and resonant activation. Simulation results for the error of the network vs time are compared to the solution of the Fokker-Planck equation.

  7. Signal processing for ION mobility spectrometers

    NASA Technical Reports Server (NTRS)

    Taylor, S.; Hinton, M.; Turner, R.

    1995-01-01

    Signal processing techniques for systems based upon Ion Mobility Spectrometry will be discussed in the light of 10 years of experience in the design of real-time IMS. Among the topics to be covered are compensation techniques for variations in the number density of the gas - the use of an internal standard (a reference peak) or pressure and temperature sensors. Sources of noise and methods for noise reduction will be discussed together with resolution limitations and the ability of deconvolution techniques to improve resolving power. The use of neural networks (either by themselves or as a component part of a processing system) will be reviewed.

  8. C language algorithms for digital signal processing

    SciTech Connect

    Embree, P.M.; Kimble, B.

    1991-01-01

    The use of the C programming language to construct digital signal-processing (DSP) algorithms for operation on high-performance personal computers is described in a textbook for engineering students. Chapters are devoted to the fundamental principles of DSP, basic C programming techniques, user-interface and disk-storage routines, filtering routines, discrete Fourier transforms, matrix and vector routines, and image-processing routines. Also included is a floppy disk containing a library of standard C mathematics, character-string, memory-allocation, and I/O functions; a library of DSP functions; and several sample DSP programs. 83 refs.

  9. A correlation polarimeter for noise-like signals. [optimum estimation of linearly polarized electromagnetic wave

    NASA Technical Reports Server (NTRS)

    Ohlson, J. E.

    1976-01-01

    Optimum estimation (tracking) of the polarization plane of a linearly polarized electromagnetic wave is determined when the signal is a narrow-band Gaussian random process with a polarization plane angle which is also a Gaussian random process. This model is compared to previous work and is applicable to space communication. The estimator performs a correlation operation similar to an amplitude-comparison monopulse angle tracker, giving the name correlation polarimeter. Under large signal-to-noise ratio (SNR), the estimator is causal. Performance of the causal correlation polarimeter is evaluated for arbitrary SNR. Optimum precorrelation filtering is determined. With low SNR, the performance of this system is far better than that of previously developed systems. Practical implementation is discussed. A scheme is given to reduce the effect of linearly polarized noise.

  10. Quantifying two-dimensional nonstationary signal with power-law correlations by detrended fluctuation analysis

    NASA Astrophysics Data System (ADS)

    Fan, Qingju; Wu, Yonghong

    2015-08-01

    In this paper, we develop a new method for the multifractal characterization of two-dimensional nonstationary signal, which is based on the detrended fluctuation analysis (DFA). By applying to two artificially generated signals of two-component ARFIMA process and binomial multifractal model, we show that the new method can reliably determine the multifractal scaling behavior of two-dimensional signal. We also illustrate the applications of this method in finance and physiology. The analyzing results exhibit that the two-dimensional signals under investigation are power-law correlations, and the electricity market consists of electricity price and trading volume is multifractal, while the two-dimensional EEG signal in sleep recorded for a single patient is weak multifractal. The new method based on the detrended fluctuation analysis may add diagnostic power to existing statistical methods.

  11. Radar transponder apparatus and signal processing technique

    SciTech Connect

    Axline, R.M. Jr.; Sloan, G.R.; Spalding, R.E.

    1994-12-31

    An active, phase-coded, time-grating transponder and a synthetic-aperture radar (SAR) and signal processor means, in combination, allow the recognition and location of the transponder (tag) in the SAR image and allow communication of information messages from the transponder to the SAR. The SAR is an illuminating radar having special processing modifications in an image-formation processor to receive an echo from a remote transponder, after the transponder receives and retransmits the SAR illuminations, and to enhance tile transponder`s echo relative to surrounding ground clutter by recognizing special transponder modulations from phase-shifted from the transponder retransmissions. The remote radio-frequency tag also transmits information to the SAR through a single antenna that also serves to receive the SAR illuminations. Unique tag-modulation and SAR signal processing techniques, in combination, allow the detection and precise geographical location of the tag, through the reduction of interfering signals from ground clutter, and allow communication of environmental and status information from said tag to be communicated to said SAR.

  12. Radar transponder apparatus and signal processing technique

    DOEpatents

    Axline, Jr., Robert M.; Sloan, George R.; Spalding, Richard E.

    1996-01-01

    An active, phase-coded, time-grating transponder and a synthetic-aperture radar (SAR) and signal processor means, in combination, allow the recognition and location of the transponder (tag) in the SAR image and allow communication of information messages from the transponder to the SAR. The SAR is an illuminating radar having special processing modifications in an image-formation processor to receive an echo from a remote transponder, after the transponder receives and retransmits the SAR illuminations, and to enhance the transponder's echo relative to surrounding ground clutter by recognizing special transponder modulations from phase-shifted from the transponder retransmissions. The remote radio-frequency tag also transmits information to the SAR through a single antenna that also serves to receive the SAR illuminations. Unique tag-modulation and SAR signal processing techniques, in combination, allow the detection and precise geographical location of the tag through the reduction of interfering signals from ground clutter, and allow communication of environmental and status information from said tag to be communicated to said SAR.

  13. Radar transponder apparatus and signal processing technique

    DOEpatents

    Axline, R.M. Jr.; Sloan, G.R.; Spalding, R.E.

    1996-01-23

    An active, phase-coded, time-grating transponder and a synthetic-aperture radar (SAR) and signal processor means, in combination, allow the recognition and location of the transponder (tag) in the SAR image and allow communication of information messages from the transponder to the SAR. The SAR is an illuminating radar having special processing modifications in an image-formation processor to receive an echo from a remote transponder, after the transponder receives and retransmits the SAR illuminations, and to enhance the transponder`s echo relative to surrounding ground clutter by recognizing special transponder modulations from phase-shifted from the transponder retransmissions. The remote radio-frequency tag also transmits information to the SAR through a single antenna that also serves to receive the SAR illuminations. Unique tag-modulation and SAR signal processing techniques, in combination, allow the detection and precise geographical location of the tag through the reduction of interfering signals from ground clutter, and allow communication of environmental and status information from said tag to be communicated to said SAR. 4 figs.

  14. An intelligent, onboard signal processing payload concept

    SciTech Connect

    Shriver, P. M.; Harikumar, J.; Briles, S. C.; Gokhale, M.

    2003-01-01

    Our approach to onboard processing will enable a quicker return and improved quality of processed data from small, remote-sensing satellites. We describe an intelligent payload concept which processes RF lightning signal data onboard the spacecraft in a power-aware manner. Presently, onboard processing is severely curtailed due to the conventional management of limited resources and power-unaware payload designs. Delays of days to weeks are commonly experienced before raw data is received, processed into a human-usable format, and finally transmitted to the end-user. We enable this resource-critical technology of onboard processing through the concept of Algorithm Power Modulation (APM). APM is a decision process used to execute a specific software algorithm, from a suite of possible algorithms, to make the best use of the available power. The suite of software algorithms chosen for our application is intended to reduce the probability of false alarms through postprocessing. Each algorithm however also has a cost in energy usage. A heuristic decision tree procedure is used which selects an algorithm based on the available power, time allocated, algorithm priority, and algorithm performance. We demonstrate our approach to power-aware onboard processing through a preliminary software simulation.

  15. FPGA-Based Filterbank Implementation for Parallel Digital Signal Processing

    NASA Technical Reports Server (NTRS)

    Berner, Stephan; DeLeon, Phillip

    1999-01-01

    One approach to parallel digital signal processing decomposes a high bandwidth signal into multiple lower bandwidth (rate) signals by an analysis bank. After processing, the subband signals are recombined into a fullband output signal by a synthesis bank. This paper describes an implementation of the analysis and synthesis banks using (Field Programmable Gate Arrays) FPGAs.

  16. Efficient audio signal processing for embedded systems

    NASA Astrophysics Data System (ADS)

    Chiu, Leung Kin

    As mobile platforms continue to pack on more computational power, electronics manufacturers start to differentiate their products by enhancing the audio features. However, consumers also demand smaller devices that could operate for longer time, hence imposing design constraints. In this research, we investigate two design strategies that would allow us to efficiently process audio signals on embedded systems such as mobile phones and portable electronics. In the first strategy, we exploit properties of the human auditory system to process audio signals. We designed a sound enhancement algorithm to make piezoelectric loudspeakers sound ”richer" and "fuller." Piezoelectric speakers have a small form factor but exhibit poor response in the low-frequency region. In the algorithm, we combine psychoacoustic bass extension and dynamic range compression to improve the perceived bass coming out from the tiny speakers. We also developed an audio energy reduction algorithm for loudspeaker power management. The perceptually transparent algorithm extends the battery life of mobile devices and prevents thermal damage in speakers. This method is similar to audio compression algorithms, which encode audio signals in such a ways that the compression artifacts are not easily perceivable. Instead of reducing the storage space, however, we suppress the audio contents that are below the hearing threshold, therefore reducing the signal energy. In the second strategy, we use low-power analog circuits to process the signal before digitizing it. We designed an analog front-end for sound detection and implemented it on a field programmable analog array (FPAA). The system is an example of an analog-to-information converter. The sound classifier front-end can be used in a wide range of applications because programmable floating-gate transistors are employed to store classifier weights. Moreover, we incorporated a feature selection algorithm to simplify the analog front-end. A machine

  17. Processing of radio signals by acoustoelectronic and acoustooptic devices

    NASA Astrophysics Data System (ADS)

    Kulakov, S. V.

    Particular papers are presented on radio-signal spectrum analyzers using SAW devices; the acoustic field of a fan-type converter of surface acoustic waves; the design of devices executing the Mellin transform on the basis of SAW components; the synchronization of complex signals by acoustoelectronic convolvers; panoramic acoustooptic receivers; and wideband acoustooptic devices base on integrated optics. Consideration is also given to an acoustooptic method for the coding and recognition of images; an integral-equation method for investigating light diffraction by ultrasound; acoustooptic signal processing devices based on diffused waveguides in lithium niobate; the effect of additive noise on the operation of a time-integrating acoustooptic correlator; and a high-resolution acoustooptic spectrum-analyzer. For individual items see A84-33477 to A84-33495

  18. Mixed signal learning by spike correlation propagation in feedback inhibitory circuits.

    PubMed

    Hiratani, Naoki; Fukai, Tomoki

    2015-04-01

    The brain can learn and detect mixed input signals masked by various types of noise, and spike-timing-dependent plasticity (STDP) is the candidate synaptic level mechanism. Because sensory inputs typically have spike correlation, and local circuits have dense feedback connections, input spikes cause the propagation of spike correlation in lateral circuits; however, it is largely unknown how this secondary correlation generated by lateral circuits influences learning processes through STDP, or whether it is beneficial to achieve efficient spike-based learning from uncertain stimuli. To explore the answers to these questions, we construct models of feedforward networks with lateral inhibitory circuits and study how propagated correlation influences STDP learning, and what kind of learning algorithm such circuits achieve. We derive analytical conditions at which neurons detect minor signals with STDP, and show that depending on the origin of the noise, different correlation timescales are useful for learning. In particular, we show that non-precise spike correlation is beneficial for learning in the presence of cross-talk noise. We also show that by considering excitatory and inhibitory STDP at lateral connections, the circuit can acquire a lateral structure optimal for signal detection. In addition, we demonstrate that the model performs blind source separation in a manner similar to the sequential sampling approximation of the Bayesian independent component analysis algorithm. Our results provide a basic understanding of STDP learning in feedback circuits by integrating analyses from both dynamical systems and information theory.

  19. Digital signal processor and processing method for GPS receivers

    NASA Technical Reports Server (NTRS)

    Thomas, Jr., Jess B. (Inventor)

    1989-01-01

    A digital signal processor and processing method therefor for use in receivers of the NAVSTAR/GLOBAL POSITIONING SYSTEM (GPS) employs a digital carrier down-converter, digital code correlator and digital tracking processor. The digital carrier down-converter and code correlator consists of an all-digital, minimum bit implementation that utilizes digital chip and phase advancers, providing exceptional control and accuracy in feedback phase and in feedback delay. Roundoff and commensurability errors can be reduced to extremely small values (e.g., less than 100 nanochips and 100 nanocycles roundoff errors and 0.1 millichip and 1 millicycle commensurability errors). The digital tracking processor bases the fast feedback for phase and for group delay in the C/A, P.sub.1, and P.sub.2 channels on the L.sub.1 C/A carrier phase thereby maintaining lock at lower signal-to-noise ratios, reducing errors in feedback delays, reducing the frequency of cycle slips and in some cases obviating the need for quadrature processing in the P channels. Simple and reliable methods are employed for data bit synchronization, data bit removal and cycle counting. Improved precision in averaged output delay values is provided by carrier-aided data-compression techniques. The signal processor employs purely digital operations in the sense that exactly the same carrier phase and group delay measurements are obtained, to the last decimal place, every time the same sampled data (i.e., exactly the same bits) are processed.

  20. Hardware System for Real-Time EMG Signal Acquisition and Separation Processing during Electrical Stimulation.

    PubMed

    Hsueh, Ya-Hsin; Yin, Chieh; Chen, Yan-Hong

    2015-09-01

    The study aimed to develop a real-time electromyography (EMG) signal acquiring and processing device that can acquire signal during electrical stimulation. Since electrical stimulation output can affect EMG signal acquisition, to integrate the two elements into one system, EMG signal transmitting and processing method has to be modified. The whole system was designed in a user-friendly and flexible manner. For EMG signal processing, the system applied Altera Field Programmable Gate Array (FPGA) as the core to instantly process real-time hybrid EMG signal and output the isolated signal in a highly efficient way. The system used the power spectral density to evaluate the accuracy of signal processing, and the cross correlation showed that the delay of real-time processing was only 250 μs.

  1. Cerebral correlates of analogical processing and their modulation by training.

    PubMed

    Wartenburger, Isabell; Heekeren, Hauke R; Preusse, Franziska; Kramer, Jürg; van der Meer, Elke

    2009-10-15

    There is increasing interest in understanding the neural systems that mediate analogical thinking, which is essential for learning and fluid intelligence. The aim of the present study was to shed light on the cerebral correlates of geometric analogical processing and on training-induced changes at the behavioral and brain level. In healthy participants a bilateral fronto-parietal network was engaged in processing geometric analogies and showed greater blood oxygenation dependent (BOLD) signals as resource demands increased. This network, as well as fusiform and subcortical brain regions, additionally showed training-induced decreases in the BOLD signal over time. The general finding that brain regions were modulated by the amount of resources demanded by the task, and/or by the reduction of allocated resources due to short term training, reflects increased efficiency--in terms of more focal and more specialized brain activation--to more economically process the geometric analogies. Our data indicate a rapid adaptation of the cognitive system which is efficiently modulated by short term training based on a positive correlation of resource demands and brain activation.

  2. Advanced Digital Signal Processing for Hybrid Lidar

    DTIC Science & Technology

    2013-03-31

    project "Advanced Digital Signal Processing for Hybrid Lidar " covering the period of 1/1/2013-3/31/2013. 9LO\\SO^O’IH^’?’ William D. Jemison...Chaotic LIDAR for Naval Applications This document contains a Progress Summary for FY13 Q2 and a Short Work Statement for FY13 Progress Summary for...This technique has the potential to increase the unambiguous range of hybrid lidar -radar while maintaining reasonable range resolution. Proof-of

  3. Digital signal processing for radioactive decay studies

    SciTech Connect

    Miller, D.; Madurga, M.; Paulauskas, S. V.; Ackermann, D.; Heinz, S.; Hessberger, F. P.; Hofmann, S.; Grzywacz, R.; Miernik, K.; Rykaczewski, K.; Tan, H.

    2011-11-30

    The use of digital acquisition system has been instrumental in the investigation of proton and alpha emitting nuclei. Recent developments extend the sensitivity and breadth of the application. The digital signal processing capabilities, used predominately by UT/ORNL for decay studies, include digitizers with decreased dead time, increased sampling rates, and new innovative firmware. Digital techniques and these improvements are furthermore applicable to a range of detector systems. Improvements in experimental sensitivity for alpha and beta-delayed neutron emitters measurements as well as the next generation of superheavy experiments are discussed.

  4. Advanced Digital Signal Processing for Hybrid Lidar

    DTIC Science & Technology

    2014-03-31

    on a multimeter to ensure that the PMT remained within its linear operating regime. The AC-coupTed signal was demodulated and digitized in the SDR ...receiver. The I and Q samples obtained by"" the SDR are transferred over an Ethernet cable to a PC, where the data are processed in a custom LabVIEW...Q samples are generated by the SDR receiver and used to compute range on a PC. Ranging results from the FDR experiments and RangeFinder simulations

  5. Research on Superconductive Signal-Processing Devices.

    DTIC Science & Technology

    1984-11-30

    LABORATORY RESEARCH ON SUPERCONDUCTIVE SIGNAL-PROCESSING DEVICES ANNUAIL REPORT To THlE AIR FORCE OFF ICE O1P SCIENT [F[C RESEARCH ELE(;TRONICS ANI... J .,.-,.c.t n......... :.. u ll.. . . -1i1611tiC /.. TABLE OF CONTENTS Abstract iii 1.0 Introduction 1 2.0 Background 3 2.1 Summary of early program...desirable at the present time. 30 30 ............ j . . . ... .o.o. -....... ’’•."".-’,-.-.-............ -. . i 3.2.2 Extension of Time-Bandwidth

  6. [A biomedical signal processing toolkit programmed by Java].

    PubMed

    Xie, Haiyuan

    2012-09-01

    According to the biomedical signal characteristics, a new biomedical signal processing toolkit is developed. The toolkit is programmed by Java. It is used in basic digital signal processing, random signal processing and etc. All the methods in toolkit has been tested, the program is robust. The feature of the toolkit is detailed explained, easy use and good practicability.

  7. Inertial processing of vestibulo-ocular signals

    NASA Technical Reports Server (NTRS)

    Hess, B. J.; Angelaki, D. E.

    1999-01-01

    New evidence for a central resolution of gravito-inertial signals has been recently obtained by analyzing the properties of the vestibulo-ocular reflex (VOR) in response to combined lateral translations and roll tilts of the head. It is found that the VOR generates robust compensatory horizontal eye movements independent of whether or not the interaural translatory acceleration component is canceled out by a gravitational acceleration component due to simultaneous roll-tilt. This response property of the VOR depends on functional semicircular canals, suggesting that the brain uses both otolith and semicircular canal signals to estimate head motion relative to inertial space. Vestibular information about dynamic head attitude relative to gravity is the basis for computing head (and body) angular velocity relative to inertial space. Available evidence suggests that the inertial vestibular system controls both head attitude and velocity with respect to a gravity-centered reference frame. The basic computational principles underlying the inertial processing of otolith and semicircular canal afferent signals are outlined.

  8. Pre-earthquake signals: Underlying physical processes

    NASA Astrophysics Data System (ADS)

    Freund, Friedemann

    2011-06-01

    Prior to large earthquakes the Earth sends out transient signals, sometimes strong, more often subtle and fleeting. These signals may consist of local magnetic field variations, electromagnetic emissions over a wide range of frequencies, a variety of atmospheric and ionospheric phenomena. Great uncertainty exists as to the nature of the processes that could produce such signals, both inside the Earth's crust and at the surface. The absence of a comprehensive physical mechanism has led to a patchwork of explanations, which are not internally consistent. The recognition that most crustal rocks contain dormant electronic charge carriers in the form of peroxy defects, OSi/⧹SiO, holds the key to a deeper understanding of these pre-earthquake signals from a solid state physics perspective. When rocks are stressed, peroxy links break, releasing electronic charge carriers, h ·, known as positive holes. The positive holes are highly mobile and can flow out of the stressed subvolume. The situation is similar to that in a battery. The h · outflow is possible when the battery circuit closes. The h · outflow constitutes an electric current, which generates magnetic field variations and low frequency EM emissions. When the positive holes arrive at the Earth's surface, they lead to ionization of air at the ground-air interface. Under certain conditions corona discharges occur, which cause RF emission. The upward expansion of ionized air may be the reason for perturbations in the ionosphere. Recombination of h · charge carriers at the surface leads to a spectroscopically distinct, non-thermal IR emission.

  9. Signal processing for fiber optic gyroscope (FOG)

    NASA Astrophysics Data System (ADS)

    Tanaka, Ryuichi; Kurokawa, Akihiro; Sato, Yoshiyuki; Magome, Tsutomu; Hayakawa, Yoshiaki; Nakatani, Ichiro; Kawaguchi, Junichiro

    1994-11-01

    A fiber-optic gyroscope (FOG) is expected to be the next generation gyroscope for guidance and control, because of various advantages. We have been developing the FOG-Inertial Navigation and Guidance (ING) for M-V satellite launching rocket of the Institute of Space and Astronautical Science (ISAS) since 1990. The FOG-ING consists of an Inertial Measurement Unit (IMU) and an Central Processing Unit Assembly. At current status, the proto-flight model FOG-IMU is being actively developed. And the flight test of the FOG-ING was performed on February 20, 1993, aboard M-3SII-7 satellite launching rocket at the ISAS test facilities in Uchinoura, Japan. This paper presents the signal processing technologies of our FOG which are used for the above FOG-ING.

  10. 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.

  11. GLAST Burst Monitor Signal Processing System

    NASA Astrophysics Data System (ADS)

    Bhat, P. Narayana; Briggs, Michael; Connaughton, Valerie; Diehl, Roland; Fishman, Gerald; Greiner, Jochen; Kippen, R. Marc; von Kienlin, Andreas; Kouveliotou, Chryssa; Lichti, Giselher; Meegan, Charles; Paciesas, William; Persyn, Steven; Preece, Robert; Steinle, Helmut; Wilson-Hodge, Colleen

    2007-07-01

    The onboard Data Processing Unit (DPU), designed and built by Southwest Research Institute, performs the high-speed data acquisition for GBM. The analog signals from each of the 14 detectors are digitized by high-speed multichannel analog data acquisition architecture. The streaming digital values resulting from a periodic (period of 104.2 ns) sampling of the analog signal by the individual ADCs are fed to a Field-Programmable Gate Array (FPGA). Real-time Digital Signal Processing (DSP) algorithms within the FPGA implement functions like filtering, thresholding, time delay and pulse height measurement. The spectral data with a 12-bit resolution are formatted according to the commandable look-up-table (LUT) and then sent to the High-Speed Science-Date Bus (HSSDB, speed=1.5 MB/s) to be telemetered to ground. The DSP offers a novel feature of a commandable & constant event deadtime. The ADC non-linearities have been calibrated so that the spectral data can be corrected during analysis. The best temporal resolution is 2 μs for the pre-burst & post-trigger time-tagged events (TTE) data. The time resolution of the binned data types is commandable from 64 msec to 1.024 s for the CTIME data (8 channel spectral resolution) and 1.024 to 32.768 s for the CSPEC data (128 channel spectral resolution). The pulse pile-up effects have been studied by Monte Carlo simulations. For a typical GRB, the possible shift in the Epeak value at high-count rates (~100 kHz) is ~1% while the change in the single power-law index could be up to 5%.

  12. GLAST Burst Monitor Signal Processing System

    SciTech Connect

    Bhat, P. Narayana; Briggs, Michael; Connaughton, Valerie; Paciesas, William; Preece, Robert; Diehl, Roland; Greiner, Jochen; Kienlin, Andreas von; Lichti, Giselher; Steinle, Helmut; Fishman, Gerald; Kouveliotou, Chryssa; Meegan, Charles; Wilson-Hodge, Colleen; Kippen, R. Marc; Persyn, Steven

    2007-07-12

    The onboard Data Processing Unit (DPU), designed and built by Southwest Research Institute, performs the high-speed data acquisition for GBM. The analog signals from each of the 14 detectors are digitized by high-speed multichannel analog data acquisition architecture. The streaming digital values resulting from a periodic (period of 104.2 ns) sampling of the analog signal by the individual ADCs are fed to a Field-Programmable Gate Array (FPGA). Real-time Digital Signal Processing (DSP) algorithms within the FPGA implement functions like filtering, thresholding, time delay and pulse height measurement. The spectral data with a 12-bit resolution are formatted according to the commandable look-up-table (LUT) and then sent to the High-Speed Science-Date Bus (HSSDB, speed=1.5 MB/s) to be telemetered to ground. The DSP offers a novel feature of a commandable and constant event deadtime. The ADC non-linearities have been calibrated so that the spectral data can be corrected during analysis. The best temporal resolution is 2 {mu}s for the pre-burst and post-trigger time-tagged events (TTE) data. The time resolution of the binned data types is commandable from 64 msec to 1.024 s for the CTIME data (8 channel spectral resolution) and 1.024 to 32.768 s for the CSPEC data (128 channel spectral resolution). The pulse pile-up effects have been studied by Monte Carlo simulations. For a typical GRB, the possible shift in the Epeak value at high-count rates ({approx}100 kHz) is {approx}1% while the change in the single power-law index could be up to 5%.

  13. Developmental changes of BOLD signal correlations with global human EEG power and synchronization during working memory.

    PubMed

    Michels, Lars; Lüchinger, Rafael; Koenig, Thomas; Martin, Ernst; Brandeis, Daniel

    2012-01-01

    In humans, theta band (5-7 Hz) power typically increases when performing cognitively demanding working memory (WM) tasks, and simultaneous EEG-fMRI recordings have revealed an inverse relationship between theta power and the BOLD (blood oxygen level dependent) signal in the default mode network during WM. However, synchronization also plays a fundamental role in cognitive processing, and the level of theta and higher frequency band synchronization is modulated during WM. Yet, little is known about the link between BOLD, EEG power, and EEG synchronization during WM, and how these measures develop with human brain maturation or relate to behavioral changes. We examined EEG-BOLD signal correlations from 18 young adults and 15 school-aged children for age-dependent effects during a load-modulated Sternberg WM task. Frontal load (in-)dependent EEG theta power was significantly enhanced in children compared to adults, while adults showed stronger fMRI load effects. Children demonstrated a stronger negative correlation between global theta power and the BOLD signal in the default mode network relative to adults. Therefore, we conclude that theta power mediates the suppression of a task-irrelevant network. We further conclude that children suppress this network even more than adults, probably from an increased level of task-preparedness to compensate for not fully mature cognitive functions, reflected in lower response accuracy and increased reaction time. In contrast to power, correlations between instantaneous theta global field synchronization and the BOLD signal were exclusively positive in both age groups but only significant in adults in the frontal-parietal and posterior cingulate cortices. Furthermore, theta synchronization was weaker in children and was--in contrast to EEG power--positively correlated with response accuracy in both age groups. In summary we conclude that theta EEG-BOLD signal correlations differ between spectral power and synchronization and that

  14. Digital Signal Processing in the GRETINA Spectrometer

    NASA Astrophysics Data System (ADS)

    Cromaz, Mario

    2015-10-01

    Developments in the segmentation of large-volume HPGe crystals has enabled the development of high-efficiency gamma-ray spectrometers which have the ability to track the path of gamma-rays scattering through the detector volume. This technology has been successfully implemented in the GRETINA spectrometer whose high efficiency and ability to perform precise event-by-event Doppler correction has made it an important tool in nuclear spectroscopy. Tracking has required the spectrometer to employ a fully digital signal processing chain. Each of the systems 1120 channels are digitized by 100 Mhz, 14-bit flash ADCs. Filters that provide timing and high-resolution energies are implemented on local FPGAs acting on the ADC data streams while interaction point locations and tracks, derived from the trace on each detector segment, are calculated in real time on a computing cluster. In this presentation we will give a description of GRETINA's digital signal processing system, the impact of design decisions on system performance, and a discussion of possible future directions as we look towards soon developing larger spectrometers such as GRETA with full 4 π solid angle coverage. This work was supported by the Office of Science in the Department of Energy under grant DE-AC02-05CH11231.

  15. Hybrid integrated optic modules for real-time signal processing

    NASA Technical Reports Server (NTRS)

    Tsai, C. S.

    1984-01-01

    The most recent progress on four relatively new hybrid integrated optic device modules in LiNbO3 waveguides and one in YIG/GGG waveguide that are currently being studied are discussed. The five hybrid modules include a time-integrating acoustooptic correlator, a channel waveguide acoustooptic frequency shifter/modulator, an electrooptic channel waveguide total internal reflection moculator/switch, an electrooptic analog-to-digital converter using a Fabry-Perot modulator array, and a noncollinear magnetooptic modulator using magnetostatic surface waves. All of these devices possess the desirable characteristics of very large bandwidth (GHz or higher), very small substrate size along the optical path (typically 1.5 cm or less), single-mode optical propagation, and low drive power requirement. The devices utilize either acoustooptic, electrooptic or magnetooptic effects in planar or channel waveguides and, therefore, act as efficient interface devices between a light wave and temporal signals. Major areas of application lie in wideband multichannel optical real-time signal processing and communications. Some of the specific applications include spectral analysis and correlation of radio frequency (RF) signals, fiber-optic sensing, optical computing and multiport switching/routing, and analog-to-digital conversion of wide RF signals.

  16. Parallel Processing with Digital Signal Processing Hardware and Software

    NASA Technical Reports Server (NTRS)

    Swenson, Cory V.

    1995-01-01

    The assembling and testing of a parallel processing system is described which will allow a user to move a Digital Signal Processing (DSP) application from the design stage to the execution/analysis stage through the use of several software tools and hardware devices. The system will be used to demonstrate the feasibility of the Algorithm To Architecture Mapping Model (ATAMM) dataflow paradigm for static multiprocessor solutions of DSP applications. The individual components comprising the system are described followed by the installation procedure, research topics, and initial program development.

  17. Active voltammetric microsensors with neural signal processing.

    SciTech Connect

    Vogt, M. C.

    1998-12-11

    Many industrial and environmental processes, including bioremediation, would benefit from the feedback and control information provided by a local multi-analyte chemical sensor. For most processes, such a sensor would need to be rugged enough to be placed in situ for long-term remote monitoring, and inexpensive enough to be fielded in useful numbers. The multi-analyte capability is difficult to obtain from common passive sensors, but can be provided by an active device that produces a spectrum-type response. Such new active gas microsensor technology has been developed at Argonne National Laboratory. The technology couples an electrocatalytic ceramic-metallic (cermet) microsensor with a voltammetric measurement technique and advanced neural signal processing. It has been demonstrated to be flexible, rugged, and very economical to produce and deploy. Both narrow interest detectors and wide spectrum instruments have been developed around this technology. Much of this technology's strength lies in the active measurement technique employed. The technique involves applying voltammetry to a miniature electrocatalytic cell to produce unique chemical ''signatures'' from the analytes. These signatures are processed with neural pattern recognition algorithms to identify and quantify the components in the analyte. The neural signal processing allows for innovative sampling and analysis strategies to be employed with the microsensor. In most situations, the whole response signature from the voltammogram can be used to identify, classify, and quantify an analyte, without dissecting it into component parts. This allows an instrument to be calibrated once for a specific gas or mixture of gases by simple exposure to a multi-component standard rather than by a series of individual gases. The sampled unknown analytes can vary in composition or in concentration, the calibration, sensing, and processing methods of these active voltammetric microsensors can detect, recognize, and

  18. The Structural Correlates of Statistical Information Processing during Speech Perception

    PubMed Central

    Deschamps, Isabelle; Hasson, Uri; Tremblay, Pascale

    2016-01-01

    The processing of continuous and complex auditory signals such as speech relies on the ability to use statistical cues (e.g. transitional probabilities). In this study, participants heard short auditory sequences composed either of Italian syllables or bird songs and completed a regularity-rating task. Behaviorally, participants were better at differentiating between levels of regularity in the syllable sequences than in the bird song sequences. Inter-individual differences in sensitivity to regularity for speech stimuli were correlated with variations in surface-based cortical thickness (CT). These correlations were found in several cortical areas including regions previously associated with statistical structure processing (e.g. bilateral superior temporal sulcus, left precentral sulcus and inferior frontal gyrus), as well other regions (e.g. left insula, bilateral superior frontal gyrus/sulcus and supramarginal gyrus). In all regions, this correlation was positive suggesting that thicker cortex is related to higher sensitivity to variations in the statistical structure of auditory sequences. Overall, these results suggest that inter-individual differences in CT within a distributed network of cortical regions involved in statistical structure processing, attention and memory is predictive of the ability to detect structural structure in auditory speech sequences. PMID:26919234

  19. Cellular defense processes regulated by pathogen-elicited receptor signaling

    NASA Astrophysics Data System (ADS)

    Wu, Rongcong; Goldsipe, Arthur; Schauer, David B.; Lauffenburger, Douglas A.

    2011-06-01

    Vertebrates are constantly threatened by the invasion of microorganisms and have evolved systems of immunity to eliminate infectious pathogens in the body. Initial sensing of microbial agents is mediated by the recognition of pathogens by means of molecular structures expressed uniquely by microbes of a given type. So-called 'Toll-like receptors' are expressed on host epithelial barrier cells play an essential role in the host defense against microbial pathogens by inducing cell responses (e.g., proliferation, death, cytokine secretion) via activation of intracellular signaling networks. As these networks, comprising multiple interconnecting dynamic pathways, represent highly complex multi-variate "information processing" systems, the signaling activities particularly critical for governing the host cell responses are poorly understood and not easily ascertained by a priori theoretical notions. We have developed over the past half-decade a "data-driven" computational modeling approach, on a 'cue-signal-response' combined experiment/computation paradigm, to elucidate key multi-variate signaling relationships governing the cell responses. In an example presented here, we study how a canonical set of six kinase pathways combine to effect microbial agent-induced apoptotic death of a macrophage cell line. One modeling technique, partial least-squares regression, yielded the following key insights: {a} signal combinations most strongly correlated to apoptotic death are orthogonal to those most strongly correlated with release of inflammatory cytokines; {b} the ratio of two key pathway activities is the most powerful predictor of microbe-induced macrophage apoptotic death; {c} the most influential time-window of this signaling activity ratio is surprisingly fast: less than one hour after microbe stimulation.

  20. Ultrasonic signal processing and tissue characterization

    NASA Astrophysics Data System (ADS)

    Mu, Zhiping

    Ultrasound imaging has become one of the most widely used diagnostic tools in medicine. While it has advantages, compared with other modalities, in terms of safety, low-cost, accessibility, portability and capability of real-time imaging, it has limitations. One of the major disadvantages of ultrasound imaging is the relatively low image quality, especially the low signal-to-noise ratio (SNR) and the low spatial resolution. Part of this dissertation is dedicated to the development of digital ultrasound signal and image processing methods to improve ultrasound image quality. Conventional B-mode ultrasound systems display the demodulated signals, i.e., the envelopes, in the images. In this dissertation, I introduce the envelope matched quadrature filtering (EMQF) technique, which is a novel demodulation technique generating optimal performance in envelope detection. In ultrasonography, the echo signals are the results of the convolution of the pulses and the medium responses, and the finite pulse length is a major source of the degradation of the image resolution. Based on the more appropriate complex-valued medium response assumption rather than the real-valued assumption used by many researchers, a nonparametric iterative deconvolution method, the Least Squares method with Point Count regularization (LSPC), is proposed. This method was tested using simulated and experimental data, and has produced excellent results showing significant improvements in resolution. During the past two decades, ultrasound tissue characterization (UTC) has emerged as an active research field and shown potentials of applications in a variety of clinical areas. Particularly interesting to me is a group of methods characterizing the scatterer spatial distribution. For resolvable regular structures, a deconvolution based method is proposed to estimate parameters characterizing such structures, including mean scatterer spacing, and has demonstrated superior performance when compared to

  1. Nonlinear biochemical signal processing via noise propagation

    NASA Astrophysics Data System (ADS)

    Kim, Kyung Hyuk; Qian, Hong; Sauro, Herbert M.

    2013-10-01

    Single-cell studies often show significant phenotypic variability due to the stochastic nature of intra-cellular biochemical reactions. When the numbers of molecules, e.g., transcription factors and regulatory enzymes, are in low abundance, fluctuations in biochemical activities become significant and such "noise" can propagate through regulatory cascades in terms of biochemical reaction networks. Here we develop an intuitive, yet fully quantitative method for analyzing how noise affects cellular phenotypes based on identifying a system's nonlinearities and noise propagations. We observe that such noise can simultaneously enhance sensitivities in one behavioral region while reducing sensitivities in another. Employing this novel phenomenon we designed three biochemical signal processing modules: (a) A gene regulatory network that acts as a concentration detector with both enhanced amplitude and sensitivity. (b) A non-cooperative positive feedback system, with a graded dose-response in the deterministic case, that serves as a bistable switch due to noise-induced ultra-sensitivity. (c) A noise-induced linear amplifier for gene regulation that requires no feedback. The methods developed in the present work allow one to understand and engineer nonlinear biochemical signal processors based on fluctuation-induced phenotypes.

  2. A Novel Approach for Adaptive Signal Processing

    NASA Technical Reports Server (NTRS)

    Chen, Ya-Chin; Juang, Jer-Nan

    1998-01-01

    Adaptive linear predictors have been used extensively in practice in a wide variety of forms. In the main, their theoretical development is based upon the assumption of stationarity of the signals involved, particularly with respect to the second order statistics. On this basis, the well-known normal equations can be formulated. If high- order statistical stationarity is assumed, then the equivalent normal equations involve high-order signal moments. In either case, the cross moments (second or higher) are needed. This renders the adaptive prediction procedure non-blind. A novel procedure for blind adaptive prediction has been proposed and considerable implementation has been made in our contributions in the past year. The approach is based upon a suitable interpretation of blind equalization methods that satisfy the constant modulus property and offers significant deviations from the standard prediction methods. These blind adaptive algorithms are derived by formulating Lagrange equivalents from mechanisms of constrained optimization. In this report, other new update algorithms are derived from the fundamental concepts of advanced system identification to carry out the proposed blind adaptive prediction. The results of the work can be extended to a number of control-related problems, such as disturbance identification. The basic principles are outlined in this report and differences from other existing methods are discussed. The applications implemented are speech processing, such as coding and synthesis. Simulations are included to verify the novel modelling method.

  3. A MUSIC-based method for SSVEP signal processing.

    PubMed

    Chen, Kun; Liu, Quan; Ai, Qingsong; Zhou, Zude; Xie, Sheng Quan; Meng, Wei

    2016-03-01

    The research on brain computer interfaces (BCIs) has become a hotspot in recent years because it offers benefit to disabled people to communicate with the outside world. Steady state visual evoked potential (SSVEP)-based BCIs are more widely used because of higher signal to noise ratio and greater information transfer rate compared with other BCI techniques. In this paper, a multiple signal classification based method was proposed for multi-dimensional SSVEP feature extraction. 2-second data epochs from four electrodes achieved excellent accuracy rates including idle state detection. In some asynchronous mode experiments, the recognition accuracy reached up to 100%. The experimental results showed that the proposed method attained good frequency resolution. In most situations, the recognition accuracy was higher than canonical correlation analysis, which is a typical method for multi-channel SSVEP signal processing. Also, a virtual keyboard was successfully controlled by different subjects in an unshielded environment, which proved the feasibility of the proposed method for multi-dimensional SSVEP signal processing in practical applications.

  4. Ultrasound perfusion signal processing for tumor detection

    NASA Astrophysics Data System (ADS)

    Kim, MinWoo; Abbey, Craig K.; Insana, Michael F.

    2016-04-01

    Enhanced blood perfusion in a tissue mass is an indication of neo-vascularity and a sign of a potential malignancy. Ultrasonic pulsed-Doppler imaging is a preferred modality for noninvasive monitoring of blood flow. However, the weak blood echoes and disorganized slow flow make it difficult to detect perfusion using standard methods without the expense and risk of contrast enhancement. Our research measures the efficiency of conventional power-Doppler (PD) methods at discriminating flow states by comparing measurement performance to that of an ideal discriminator. ROC analysis applied to the experimental results shows that power Doppler methods are just 30-50 % efficient at perfusion flows less than 1ml/min, suggesting an opportunity to improve perfusion assessment through signal processing. A new perfusion estimator is proposed by extending the statistical discriminator approach. We show that 2-D perfusion color imaging may be enhanced using this approach.

  5. Real-Time Signal Processing Systems

    DTIC Science & Technology

    1992-10-29

    available resources. I I 11 I -.-i C) LL-J M, r* >0 00 xT <L r C.) a±uz 1< 2ltEAhc~et n1 LO x LAJ YL LJ cy CL CU Qý a- qw Um 04 4C L:j x I= 4C a. a. m...Lj < HO 4C x CX OC 010893w 1 =5 33VARNI iSOH 3WAI Figure 2. Vector Processing Nardware 13 The VPH is ideally suited for high-speed signal...8" x 10". Trace widths less than 8 mils and via sizes smaller than 15 mils would also significantly increase cost. When the boards are to be layed

  6. Tunable signal processing through modular control of transcription factor translocation.

    PubMed

    Hao, Nan; Budnik, Bogdan A; Gunawardena, Jeremy; O'Shea, Erin K

    2013-01-25

    Signaling pathways can induce different dynamics of transcription factor (TF) activation. We explored how TFs process signaling inputs to generate diverse dynamic responses. The budding yeast general stress-responsive TF Msn2 acted as a tunable signal processor that could track, filter, or integrate signals in an input-dependent manner. This tunable signal processing appears to originate from dual regulation of both nuclear import and export by phosphorylation, as mutants with one form of regulation sustained only one signal-processing function. Versatile signal processing by Msn2 is crucial for generating distinct dynamic responses to different natural stresses. Our findings reveal how complex signal-processing functions are integrated into a single molecule and provide a guide for the design of TFs with "programmable" signal-processing functions.

  7. Development of a Real-Time General-Purpose Digital Signal Processing Laboratory System.

    DTIC Science & Technology

    1983-12-01

    Structure Chart ..... ............... . 66 21 Block Diagram of Correlation Method ......... . 72 vi A .0 P List of Tables .. .:.,- Table Page I User Interface...transmitted and received by complex electrical apparatus, the performance of which could be subjected to mathematical analysis. Signal processing now ...The definition of the term "signal" now includes almost any physical variable of interest, and the techniques of signal analysis and processing are

  8. Signal-to-noise ratio limitations for intensity correlation imaging.

    PubMed

    Fried, David L; Riker, Jim; Agrawal, Brij

    2014-07-01

    Intensity correlation imaging (ICI) is a concept which has been considered for the task of providing images of satellites in geosynchronous orbit using ground-based equipment. This concept is based on the intensity interferometer principle first developed by Hanbury Brown and Twiss. It is the objective of this paper to establish that a sun-lit geosynchronous satellite is too faint a target object to allow intensity interferometry to be used in developing image information about it-at least not in a reasonable time and with a reasonable amount of equipment. An analytic treatment of the basic phenomena is presented. This is an analysis of one aspect of the statistics of the very high frequency random variations of a very narrow portion of the optical spectra of the incoherent (black-body like-actually reflected sunlight) radiation from the satellite, an analysis showing that the covariance of this radiation as measured by a pair of ground-based telescopes is directly proportional to the square of the magnitude of one component of the Fourier transform of the image of the satellite-the component being the one for a spatial frequency whose value is determined by the separation of the two telescopes. This analysis establishes the magnitude of the covariance. A second portion of the analysis considers shot-noise effects. It is shown that even with much less than one photodetection event (pde) per signal integration time an unbiased estimate of the covariance of the optical field's random variations can be developed. Also, a result is developed for the standard deviation to be associated with the estimated value of the covariance. From these results an expression is developed for what may be called the signal-to-noise ratio to be associated with an estimate of the covariance. This signal-to-noise ratio, it turns out, does not depend on the measurement's integration time, Δt (in seconds), or on the optical spectral bandwidth, Δν (in Hertz), utilized-so long as

  9. A Linear Subspace Approach to Burst Communication Signal Processing

    DTIC Science & Technology

    2006-05-31

    190 62 α = 1 Ts component of the Spectral Correlation Function . . . 191 63 MMSE Filter for an OQPSK Signal . . . . . . . . . . . . . . 199 64 BFSK...MMSE Minimum Mean Square Error . . . . . . . . . . . . . . . 4 MSK Minimum Shift Keying . . . . . . . . . . . . . . . . . . . 7 OQPSK Offset Quadrature...the real portion of its complex argument. 5Appendix C extends this model to Offset QPSK ( OQPSK ) signals and Minimum Shift Keyed (MSK) signals. 7 t

  10. Signal processing schemes for optical voltage transducer

    NASA Astrophysics Data System (ADS)

    Chen, Jinling; Xie, Delin; Chen, Hongbin; Xie, Latang; Song, Jianhe; Luo, Xiaoni

    2006-02-01

    This paper describes an optical voltage transducer(OVT) for a 35kV system based on Pockels effect in a BGO(Bi 4Ge 3O 12) crystal. OVT used to measure the voltage of power are superior to conventional electromagnet-induced voltage transducer in many aspects, thus it has great potential to applications. It has some advantages. These advantages are: 1)Optics provides total galvanic separation between the measuring point at high voltage (HV) potential and the measuring equipment at ground potential. 2)Transmission of measuring signals in optical fibers is immune to induced electromagnetic noise even in EMI-environment of switchyards and other high voltage installations. 3)Optics and especially optical fibers make the insulation costs independent of voltage levels thus giving an economical advantage at voltage levels above 100kV. 4)The use of optics is expected to reduce the weight of the transducers. 5)Optical transducers are expected to have a large bandwidth than conventional transducers. 6)The output-signals from an optical transducer are easily interfaced with computers and electronically operated equipment such as digital relays. New techniques developed in electronics and optical field including fiber optic technology bring new contributions to the measurement of voltage and electric field. A Pockels voltage sensor has been widely introduced to electrical power transmission and distribution systems and some advantage of the optical voltage measuring techniques are reported. In this paper, a brief summary of electro-optic effects and the principle of OVT is proposed. The signal processing schemes of different optical path and features are analyzed. The basic principle of OVT is to modulate the irradiance of the light-directed to OVT by an optical fiber-according to the potential difference between the HV-line and the ground potential. The modulation of the light is accomplished by placing a material-that has an optical property (the birefringence), which is

  11. Signal Processing and Interpretation Using Multilevel Signal Abstractions.

    DTIC Science & Technology

    1986-06-01

    correlation measure, because they concentrate on the elements’ important features. Numeric correlation, on the other side, cannot easily differentiate ...Figure 2.17, C s 2 s -i’n 02 T3 - T= = (AIA 3 )(- + - ) (2.13) V C In the above equations , T2 - TL and T3 -T are measured from the power traces " of the...To solve " these trigonometric equations for 0 and v, we note that the difference 1- 02 is also known and equal to some angle c. To proceed, we

  12. Interactions between visceral afferent signaling and stimulus processing

    PubMed Central

    Critchley, Hugo D.; Garfinkel, Sarah N.

    2015-01-01

    Visceral afferent signals to the brain influence thoughts, feelings and behavior. Here we highlight the findings of a set of empirical investigations in humans concerning body-mind interaction that focus on how feedback from states of autonomic arousal shapes cognition and emotion. There is a longstanding debate regarding the contribution of the body to mental processes. Recent theoretical models broadly acknowledge the role of (autonomically-mediated) physiological arousal to emotional, social and motivational behaviors, yet the underlying mechanisms are only partially characterized. Neuroimaging is overcoming this shortfall; first, by demonstrating correlations between autonomic change and discrete patterns of evoked, and task-independent, neural activity; second, by mapping the central consequences of clinical perturbations in autonomic response and; third, by probing how dynamic fluctuations in peripheral autonomic state are integrated with perceptual, cognitive and emotional processes. Building on the notion that an important source of the brain's representation of physiological arousal is derived from afferent information from arterial baroreceptors, we have exploited the phasic nature of these signals to show their differential contribution to the processing of emotionally-salient stimuli. This recent work highlights the facilitation at neural and behavioral levels of fear and threat processing that contrasts with the more established observations of the inhibition of central pain processing during baroreceptors activation. The implications of this body-brain-mind axis are discussed. PMID:26379481

  13. Coherent signal processing in optical coherence tomography

    NASA Astrophysics Data System (ADS)

    Kulkarni, Manish Dinkarrao

    1999-09-01

    Optical coherence tomography (OCT) is a novel method for non-invasive sub-surface imaging of biological tissue micro-structures. OCT achieves high spatial resolution ( ~ 15 m m in three dimensions) using a fiber-optically integrated system which is suitable for application in minimally invasive diagnostics, including endoscopy. OCT uses an optical heterodyne detection technique based on white light interferometry. Therefore extremely faint reflections ( ~ 10 fW) are routinely detected with high spatial localization. The goal of this thesis is twofold. The first is to present a theoretical model for describing image formation in OCT, and attempt to enhance the current level of understanding of this new modality. The second objective is to present signal processing methods for improving OCT image quality. We present deconvolution algorithms to obtain improved longitudinal resolution in OCT. This technique may be implemented without increasing system complexity as compared to current clinical OCT systems. Since the spectrum of the light backscattered from bio-scatterers is closely associated with ultrastructural variations in tissue, we propose a new technique for measuring spectra as a function of depth. This advance may assist OCT in differentiating various tissue types and detecting abnormalities within a tissue. In addition to depth resolved spectroscopy, Doppler processing of OCT signals can also improve OCT image contrast. We present a new technique, termed color Doppler OCT (CDOCT). It is an innovative extension of OCT for performing spatially localized optical Doppler velocimetry. Micron-resolution imaging of blood flow in sub-surface vessels in living tissue using CDOCT is demonstrated. The fundamental issues regarding the trade- off between the velocity estimation precision and image acquisition rate are presented. We also present novel algorithms for high accuracy velocity estimation. In many blood vessels velocities tend to be on the order of a few cm

  14. Pedagogical reforms of digital signal processing education

    NASA Astrophysics Data System (ADS)

    Christensen, Michael

    The future of the engineering discipline is arguably predicated heavily upon appealing to the future generation, in all its sensibilities. The greatest burden in doing so, one might rightly believe, lies on the shoulders of the educators. In examining the causal means by which the profession arrived at such a state, one finds that the technical revolution, precipitated by global war, had, as its catalyst, institutions as expansive as the government itself to satisfy the demand for engineers, who, as a result of such an existential crisis, were taught predominantly theoretical underpinnings to address a finite purpose. By contrast, the modern engineer, having expanded upon this vision and adapted to an evolving society, is increasingly placed in the proverbial role of the worker who must don many hats: not solely a scientist, yet often an artist; not a businessperson alone, but neither financially naive; not always a representative, though frequently a collaborator. Inasmuch as change then serves as the only constancy in a global climate, therefore, the educational system - if it is to mimic the demands of the industry - is left with an inherent need for perpetual revitalization to remain relevant. This work aims to serve that end. Motivated by existing research in engineering education, an epistemological challenge is molded into the framework of the electrical engineer with emphasis on digital signal processing. In particular, it is investigated whether students are better served by a learning paradigm that tolerates and, when feasible, encourages error via a medium free of traditional adjudication. Through the creation of learning modules using the Adobe Captivate environment, a wide range of fundamental knowledge in signal processing is challenged within the confines of existing undergraduate courses. It is found that such an approach not only conforms to the research agenda outlined for the engineering educator, but also reflects an often neglected reality

  15. Spatial acoustic signal processing for immersive communication

    NASA Astrophysics Data System (ADS)

    Atkins, Joshua

    Computing is rapidly becoming ubiquitous as users expect devices that can augment and interact naturally with the world around them. In these systems it is necessary to have an acoustic front-end that is able to capture and reproduce natural human communication. Whether the end point is a speech recognizer or another human listener, the reduction of noise, reverberation, and acoustic echoes are all necessary and complex challenges. The focus of this dissertation is to provide a general method for approaching these problems using spherical microphone and loudspeaker arrays.. In this work, a theory of capturing and reproducing three-dimensional acoustic fields is introduced from a signal processing perspective. In particular, the decomposition of the spatial part of the acoustic field into an orthogonal basis of spherical harmonics provides not only a general framework for analysis, but also many processing advantages. The spatial sampling error limits the upper frequency range with which a sound field can be accurately captured or reproduced. In broadband arrays, the cost and complexity of using multiple transducers is an issue. This work provides a flexible optimization method for determining the location of array elements to minimize the spatial aliasing error. The low frequency array processing ability is also limited by the SNR, mismatch, and placement error of transducers. To address this, a robust processing method is introduced and used to design a reproduction system for rendering over arbitrary loudspeaker arrays or binaurally over headphones. In addition to the beamforming problem, the multichannel acoustic echo cancellation (MCAEC) issue is also addressed. A MCAEC must adaptively estimate and track the constantly changing loudspeaker-room-microphone response to remove the sound field presented over the loudspeakers from that captured by the microphones. In the multichannel case, the system is overdetermined and many adaptive schemes fail to converge to

  16. Optimal Hamiltonian Simulation by Quantum Signal Processing

    NASA Astrophysics Data System (ADS)

    Low, Guang Hao; Chuang, Isaac L.

    2017-01-01

    The physics of quantum mechanics is the inspiration for, and underlies, quantum computation. As such, one expects physical intuition to be highly influential in the understanding and design of many quantum algorithms, particularly simulation of physical systems. Surprisingly, this has been challenging, with current Hamiltonian simulation algorithms remaining abstract and often the result of sophisticated but unintuitive constructions. We contend that physical intuition can lead to optimal simulation methods by showing that a focus on simple single-qubit rotations elegantly furnishes an optimal algorithm for Hamiltonian simulation, a universal problem that encapsulates all the power of quantum computation. Specifically, we show that the query complexity of implementing time evolution by a d -sparse Hamiltonian H ^ for time-interval t with error ɛ is O [t d ∥H ^ ∥max+log (1 /ɛ ) /log log (1 /ɛ ) ] , which matches lower bounds in all parameters. This connection is made through general three-step "quantum signal processing" methodology, comprised of (i) transducing eigenvalues of H ^ into a single ancilla qubit, (ii) transforming these eigenvalues through an optimal-length sequence of single-qubit rotations, and (iii) projecting this ancilla with near unity success probability.

  17. Microwave photonic delay line signal processing.

    PubMed

    Diehl, John F; Singley, Joseph M; Sunderman, Christopher E; Urick, Vincent J

    2015-11-01

    This paper provides a path for the design of state-of-the-art fiber-optic delay lines for signal processing. The theoretical forms for various radio-frequency system performance metrics are derived for four modulation types: X- and Z-cut Mach-Zehnder modulators, a phase modulator with asymmetric Mach-Zehnder interferometer, and a polarization modulator with control waveplate and polarizing beam splitter. Each modulation type is considered to cover the current and future needs for ideal system designs. System gain, compression point, and third-order output intercept point are derived from the transfer matrices for each modulation type. A discussion of optical amplifier placement and fiber-effect mitigation is offered. The paper concludes by detailing two high-performance delay lines, built for unique applications, that exhibit performance levels an order of magnitude better than commercial delay lines. This paper should serve as a guide to maximizing the performance of future systems and offer a look into current and future research being done to further improve photonics technologies.

  18. Optimal signal processing for continuous qubit readout

    NASA Astrophysics Data System (ADS)

    Ng, Shilin; Tsang, Mankei

    2014-08-01

    The measurement of a quantum two-level system, or a qubit in modern terminology, often involves an electromagnetic field that interacts with the qubit, before the field is measured continuously and the qubit state is inferred from the noisy field measurement. During the measurement, the qubit may undergo spontaneous transitions, further obscuring the initial qubit state from the observer. Taking advantage of some well-known techniques in stochastic detection theory, here we propose a signal processing protocol that can infer the initial qubit state optimally from the measurement in the presence of noise and qubit dynamics. Assuming continuous quantum-nondemolition measurements with Gaussian or Poissonian noise and a classical Markov model for the qubit, we derive analytic solutions to the protocol in some special cases of interest using Itō calculus. Our method is applicable to multihypothesis testing for robust qubit readout and relevant to experiments on qubits in superconducting microwave circuits, trapped ions, nitrogen-vacancy centers in diamond, semiconductor quantum dots, or phosphorus donors in silicon.

  19. Integrated optical signal processing with magnetostatic waves

    NASA Technical Reports Server (NTRS)

    Fisher, A. D.; Lee, J. N.

    1984-01-01

    Magneto-optical devices based on Bragg diffraction of light by magnetostatic waves (MSW's) offer the potential of large time-bandwidth optical signal processing at microwave frequencies of 1 to 20 GHz and higher. A thin-film integrated-optical configuration, with the interacting MSW and guided-optical wave both propagating in a common ferrite layer, is necessary to avoid shape-factor demagnetization effects. The underlying theory of the MSW-optical interaction is outlined, including the development of expressions for optical diffraction efficiency as a function of MSW power and other relevant parameters. Bradd diffraction of guided-optical waves by transversely-propagating magnetostatic waves and collinear TE/TM mode conversion included by MSW's have been demonstrated in yttrium iron garnet (YIG) thin films. Diffraction levels as large as 4% (7 mm interaction length) and a modulation dynamic range of approx 30 dB have been observed. Advantages of these MSW-based devices over the analogous acousto-optical devices include: much greater operating frequencies, tunability of the MSW dispersion relation by varying either the RF frequency or the applied bias magnetic field, simple broad-band MSW transducer structures (e.g., a single stripline), and the potential for very high diffraction efficiencies.

  20. Processing Motion Signals in Complex Environments

    NASA Technical Reports Server (NTRS)

    Verghese, Preeti

    2000-01-01

    Motion information is critical for human locomotion and scene segmentation. Currently we have excellent neurophysiological models that are able to predict human detection and discrimination of local signals. Local motion signals are insufficient by themselves to guide human locomotion and to provide information about depth, object boundaries and surface structure. My research is aimed at understanding the mechanisms underlying the combination of motion signals across space and time. A target moving on an extended trajectory amidst noise dots in Brownian motion is much more detectable than the sum of signals generated by independent motion energy units responding to the trajectory segments. This result suggests that facilitation occurs between motion units tuned to similar directions, lying along the trajectory path. We investigated whether the interaction between local motion units along the motion direction is mediated by contrast. One possibility is that contrast-driven signals from motion units early in the trajectory sequence are added to signals in subsequent units. If this were the case, then units later in the sequence would have a larger signal than those earlier in the sequence. To test this possibility, we compared contrast discrimination thresholds for the first and third patches of a triplet of sequentially presented Gabor patches, aligned along the motion direction. According to this simple additive model, contrast increment thresholds for the third patch should be higher than thresholds for the first patch.The lack of a measurable effect on contrast thresholds for these various manipulations suggests that the pooling of signals along a trajectory is not mediated by contrast-driven signals. Instead, these results are consistent with models that propose that the facilitation of trajectory signals is achieved by a second-level network that chooses the strongest local motion signals and combines them if they occur in a spatio-temporal sequence consistent

  1. Intelligent, onboard signal processing payload concept, addendum :

    SciTech Connect

    Shriver, P. M.; Harikumar, J.; Briles, S. C.; Gokhale, M.

    2003-01-01

    This document addresses two issues in the original paper entitled 'An Intelligent, Onboard Signal Processing Payload Concept' submitted to the SPIE AeroSense 2003 C0nference.l Since the original paper submission, and prior to the scheduled presentation, a correction has been made to one of the figures in the original paper and an update has been performed to the software simulation of the payload concept. The figure, referred to as Figure 8. Simulation Results in the original paper, contains an error in the voltage versus the capacity drained chart. This chart does not correctly display the voltage changes experienced by the battery module due to the varying discharge rates. This error is an artifact of the procedure used to graph the data. Additionally, the original version of the Simulation related the algorithm execution rate to the lightning event rate regardless of the number of events in the ring buffer. This feature was mentioned in section 5. Simulation Results of the original paper. A correction was also made to the size of the ring buffer. Incorrect information was provided to the authors that placed the number of possible events at 18,310. Corrected information has since been obtained that specifies the ring buffer can typically hold only 1,000 events. This has a significant impact on the APM process and the number of events lost when the size of the ring buffer is exceeded. Also, upon further analysis, it was realized that the simulation contained an error in the recording of the number of events in the ring buffer. The faster algorithms, LMS and ML, should have been able to process all events during the simulation time interval, but the initial results did not reflect this characteristic. The updated version of the simulation appropriately handles the number of algorithm executions and recording of events in the ring buffer as well as uses the correct size for the ring buffer. These improvements to the simulation and subsequent results are discussed in

  2. Accelerating radio astronomy cross-correlation with graphics processing units

    NASA Astrophysics Data System (ADS)

    Clark, M. A.; LaPlante, P. C.; Greenhill, L. J.

    2013-05-01

    We present a highly parallel implementation of the cross-correlation of time-series data using graphics processing units (GPUs), which is scalable to hundreds of independent inputs and suitable for the processing of signals from 'large-Formula' arrays of many radio antennas. The computational part of the algorithm, the X-engine, is implemented efficiently on NVIDIA's Fermi architecture, sustaining up to 79% of the peak single-precision floating-point throughput. We compare performance obtained for hardware- and software-managed caches, observing significantly better performance for the latter. The high performance reported involves use of a multi-level data tiling strategy in memory and use of a pipelined algorithm with simultaneous computation and transfer of data from host to device memory. The speed of code development, flexibility, and low cost of the GPU implementations compared with application-specific integrated circuit (ASIC) and field programmable gate array (FPGA) implementations have the potential to greatly shorten the cycle of correlator development and deployment, for cases where some power-consumption penalty can be tolerated.

  3. Biologically-based signal processing system applied to noise removal for signal extraction

    DOEpatents

    Fu, Chi Yung; Petrich, Loren I.

    2004-07-13

    The method and system described herein use a biologically-based signal processing system for noise removal for signal extraction. A wavelet transform may be used in conjunction with a neural network to imitate a biological system. The neural network may be trained using ideal data derived from physical principles or noiseless signals to determine to remove noise from the signal.

  4. Investigation of certain characteristics of thinned antenna arrays with digital signal processing

    NASA Astrophysics Data System (ADS)

    Danilevskii, L. V.; Domanov, Iu. A.; Korobko, O. V.; Tauroginskii, B. I.

    1983-11-01

    A thinned array with correlation processing of input signals is examined. It is shown that amplitude quantization does not change the signal at the thinned-array input as compared with the complete antenna array. The discreteness of time delay causes the thinned and complete arrays to become nonequivalent. Computer-simulation results are presented.

  5. Multivariate Gaussian Process Model for Correlated Time Series in R

    SciTech Connect

    Kalendra, Eric

    2015-04-07

    RmultiProcess software is designed to work with multiple correlated sensors. The characteristic that allows data to be filled in or the support to be changed is correlation, the interdependence between observations.

  6. Neural mechanisms of spatiotemporal signal processing

    NASA Astrophysics Data System (ADS)

    Khanbabaie Shoub, Shaban (Reza)

    We have studied the synaptic, dendritic, and network mechanisms of spatiotemporal signal processing underlying the computation of visual motion in the avian tectum. Such mechanisms are critical for information processing in all vertebrates, but have been difficult to elucidate in mammals because of anatomical limitations. We have therefore developed a chick tectal slice preparation, which has features that help us circumvent these limitations. Using single-electrode multi-pulse synaptic stimulation experiments we found that the SGC-I cell responds to synaptic stimulation in a binary manner and its response is phasic in a time dependent probabilistic manner over large time scales. Synaptic inputs at two locations typically interact in a mutually exclusive manner when delivered within the "interaction time" of approximately 30 ms. Then we constructed a model of SGC-I cell and the retinal inputs to examine the role of the observed non-linear cellular properties in shaping the response of SGC-I neurons to assumed retinal representations of dynamic spatiotemporal visual stimuli. We found that by these properties, SGC-I cells can classify different stimuli. Especially without the phasic synaptic signal transfer the model SGC-I cell fails to distinguish between the static stationary stimuli and dynamic spatiotemporal stimuli. Based on one-site synaptic response probability and the assumption of independent neighboring dendritic endings we predicted the response probability of SGC-I cells to multiple synaptic inputs. We tested this independence-based model prediction and found that the independency assumption is not valid. The measured SGC-I response probability to multiple synaptic inputs does not increase with the number of synaptic inputs. The presence of GABAergic horizontal cells in layer 5 suggest an inhibitory effect of these cells on the SGC-I retino-tectal synaptic responses. In our experiment we found that the measured SGC-I response probability to multiple

  7. Microwave signal processing with photorefractive dynamic holography

    NASA Astrophysics Data System (ADS)

    Fotheringham, Edeline B.

    Have you ever found yourself listening to the music playing from the closest stereo rather than to the bromidic (uninspiring) person speaking to you? Your ears receive information from two sources but your brain listens to only one. What if your cell phone could distinguish among signals sharing the same bandwidth too? There would be no "full" channels to stop you from placing or receiving a call. This thesis presents a nonlinear optical circuit capable of distinguishing uncorrelated signals that have overlapping temporal bandwidths. This so called autotuning filter is the size of a U.S. quarter dollar and requires less than 3 mW of optical power to operate. It is basically an oscillator in which the losses are compensated with dynamic holographic gain. The combination of two photorefractive crystals in the resonator governs the filter's winner-take-all dynamics through signal-competition for gain. This physical circuit extracts what is mathematically referred to as the largest principal component of its spatio-temporal input space. The circuit's practicality is demonstrated by its incorporation in an RF-photonic system. An unknown mixture of unknown microwave signals, received by an antenna array, constitutes the input to the system. The output electronically returns one of the original microwave signals. The front-end of the system down converts the 10 GHz microwave signals and amplifies them before the signals phase modulate optical beams. The optical carrier is suppressed from these beams so that it may not be considered as a signal itself to the autotuning filter. The suppression is achieved with two-beam coupling in a single photorefractive crystal. The filter extracts the more intense of the signals present on the carrier-suppressed input beams. The detection of the extracted signal restores the microwave signal to an electronic form. The system, without the receiving antenna array, is packaged in a 13 x 18 x 6″ briefcase. Its power consumption equals that

  8. Adaptive Noise Suppression Using Digital Signal Processing

    NASA Technical Reports Server (NTRS)

    Kozel, David; Nelson, Richard

    1996-01-01

    A signal to noise ratio dependent adaptive spectral subtraction algorithm is developed to eliminate noise from noise corrupted speech signals. The algorithm determines the signal to noise ratio and adjusts the spectral subtraction proportion appropriately. After spectra subtraction low amplitude signals are squelched. A single microphone is used to obtain both eh 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 unvoice frames an estimate of the noise is obtained. A running average of the noise is used to approximate the expected value of the noise. Applications include the emergency egress vehicle and the crawler transporter.

  9. Wavelet Signal Processing for Transient Feature Extraction

    DTIC Science & Technology

    1992-03-15

    Research was conducted to evaluate the feasibility of applying Wavelets and Wavelet Transform methods to transient signal feature extraction problems... Wavelet transform techniques were developed to extract low dimensional feature data that allowed a simple classification scheme to easily separate

  10. Wavelet Transform Signal Processing Applied to Ultrasonics.

    DTIC Science & Technology

    1995-05-01

    THE WAVELET TRANSFORM IS APPLIED TO THE ANALYSIS OF ULTRASONIC WAVES FOR IMPROVED SIGNAL DETECTION AND ANALYSIS OF THE SIGNALS. In instances where...the mother wavelet is well defined, the wavelet transform has relative insensitivity to noise and does not need windowing. Peak detection of...ultrasonic pulses using the wavelet transform is described and results show good detection even when large white noise was added. The use of the wavelet

  11. Optical Wavelet Signals Processing and Multiplexing

    NASA Astrophysics Data System (ADS)

    Cincotti, Gabriella; Moreolo, Michela Svaluto; Neri, Alessandro

    2005-12-01

    We present compact integrable architectures to perform the discrete wavelet transform (DWT) and the wavelet packet (WP) decomposition of an optical digital signal, and we show that the combined use of planar lightwave circuits (PLC) technology and multiresolution analysis (MRA) can add flexibility to current multiple access optical networks. We furnish the design guidelines to synthesize wavelet filters as two-port lattice-form planar devices, and we give some examples of optical signal denoising and compression/decompression techniques in the wavelet domain. Finally, we present a fully optical wavelet packet division multiplexing (WPDM) scheme where data signals are waveform-coded onto wavelet atom functions for transmission, and numerically evaluate its performances.

  12. Electrophysiological Correlates of Stimulus Equivalence Processes

    ERIC Educational Resources Information Center

    Haimson, Barry; Wilkinson, Krista M.; Rosenquist, Celia; Ouimet, Carolyn; McIlvane, William J.

    2009-01-01

    Research reported here concerns neural processes relating to stimulus equivalence class formation. In Experiment 1, two types of word pairs were presented successively to normally capable adults. In one type, the words had related usage in English (e.g., uncle, aunt). In the other, the two words were not typically related in their usage (e.g.,…

  13. Tomographic Processing of Synthetic Aperture Radar Signals for Enhanced Resolution

    DTIC Science & Technology

    1989-11-01

    digital signal processing view of strip-mapping synthetic aperture radar," M.S. thesis , University of Illinois, Urbana, IL,1988." [571 David C. Munson...TOMOGRAPHIC PROCESSING OF 1 SYNTHETIC APERTURE I RADAR SIGNALS FOR ENHANCED RESOLUTION,I * Jerald Lee Bauck DTIC ELECTE JAN2419901D I I UNIVERSITY OF ILLINOIS...NC 27709-2211 ELEMENT NO. NO. NO CCESSION NO. 11i. TITLE (Include Security Classification) TOMOGRAPHIC PROCESSING OF SYNTHETIC APERTURE RADlAR SIGNALS

  14. Optical Architectures for Signal Processing - Part A

    DTIC Science & Technology

    2003-04-01

    Input: F; 7 1 Ouput Microwave signal •icrowave signal Optical sourcd Passive optical I Photodetector . device P𔃻 ’ P2 b) Optical source Input: Microwave...integrated illumination with optical power of 2 mW. It can be concluded from Fig. 7 that the same switching performances can be observed whatever the way...1 2 3 4 5 6 7 8 9 10 Frequency (GHz) Figure 7 : Comparison of switching performances under 2mW of optical power for the full integrated structure

  15. Advanced Digital Signal Processing for Hybrid Lidar

    DTIC Science & Technology

    2014-10-30

    was moved in 10 cm increments from a range of 1.35 m to 3.05 m. The photomultiplier tube ( PMT ) collected light scattered from the submerged target...through the window. A bias-tee at the output of the PMT separated the DC and AC components of the photocurrent. The DC-coupled signal was monitored on a...multimeter to ensure that the PMT remained within its linear operating region. The AC-coupled signal was demodulated and digitized in the software

  16. Advanced Digital Signal Processing for Hybrid Lidar

    DTIC Science & Technology

    2014-09-30

    The target was moved in 10 cm increments from a range of 1.35 m to 3.05 m. The photomultiplier tube ( PMT ) collected light scattered from the...submerged target through the window. A bias-tee at the output of the PMT separated the DC and AC components of the photocurrent. The DC-coupled signal was...monitored on a multimeter to ensure that the PMT remained within its linear operating region. The AC-coupled signal was demodulated and digitized in

  17. Multifractal detrended cross-correlation analysis for two nonstationary signals.

    PubMed

    Zhou, Wei-Xing

    2008-06-01

    We propose a method called multifractal detrended cross-correlation analysis to investigate the multifractal behaviors in the power-law cross-correlations between two time series or higher-dimensional quantities recorded simultaneously, which can be applied to diverse complex systems such as turbulence, finance, ecology, physiology, geophysics, and so on. The method is validated with cross-correlated one- and two-dimensional binomial measures and multifractal random walks. As an example, we illustrate the method by analyzing two financial time series.

  18. Vibrotactile identification of signal-processed sounds from environmental events.

    PubMed

    Ranjbar, Parivash; Stranneby, Dag; Borg, Erik

    2009-01-01

    This study compared three different signal-processing principles (eight basic algorithms)-transposing, modulating, and filtering-to find the principle(s)/algorithm(s) that resulted in the best tactile identification of environmental sounds. The subjects were 19 volunteers (9 female/10 male) who were between 18 and 50 years old and profoundly hearing impaired. We processed sounds produced by 45 representative environmental events with the different algorithms and presented them to subjects as tactile stimuli using a wide-band stationary vibrator. We compared eight algorithms based on the three principles (one unprocessed, as reference). The subjects identified the stimuli by choosing among 10 alternatives drawn from the 45 events. We found that algorithm and subject were significant factors affecting the results (repeated measures analysis of variance, p < 0.001). We also found large differences between individuals regarding which algorithm was best. The test-retest variability was small (mean +/- 95% confidence interval = 8 +/- 3 percentage units), and no correlation was noted between identification score and individual vibratory thresholds. One transposing algorithm and two modulating algorithms led to significantly better results than did the unprocessed signals (p < 0.05). Thus, the two principles of transposing and modulating were appropriate, whereas filtering was unsuccessful. In future work, the two transposing algorithms and the modulating algorithm will be used in tests with a portable vibrator for people with dual sensory impairment (hearing and vision).

  19. Laser heterodyne interferometric signal processing method based on rising edge locking with high frequency clock signal.

    PubMed

    Zhang, Enzheng; Chen, Benyong; Yan, Liping; Yang, Tao; Hao, Qun; Dong, Wenjun; Li, Chaorong

    2013-02-25

    A novel phase measurement method composed of the rising-edge locked signal processing and the digital frequency mixing is proposed for laser heterodyne interferometer. The rising-edge locked signal processing, which employs a high frequency clock signal to lock the rising-edges of the reference and measurement signals, not only can improve the steepness of the rising-edge, but also can eliminate the error counting caused by multi-rising-edge phenomenon in fringe counting. The digital frequency mixing is realized by mixing the digital interference signal with a digital base signal that is different from conventional frequency mixing with analogue signals. These signal processing can improve the measurement accuracy and enhance anti-interference and measurement stability. The principle and implementation of the method are described in detail. An experimental setup was constructed and a series of experiments verified the feasibility of the method in large displacement measurement with high speed and nanometer resolution.

  20. Correlation analysis of transitional processes of chronorhythms

    NASA Astrophysics Data System (ADS)

    Strinadko, Marina M.; Timochko, Katerina B.; Strinadko, Olena M.; Abramov, Igor V.

    1999-11-01

    The biological system reaction on spasmodic change of a phase of sine wave revolting force is investigated. The model researches for the biosystem unit that is described by linear differential equation of the second order are carried out. Possibility of time asymmetry in adaptation and transitional processes of biological units, at spasmodic change of phase identical modulo and opposite on the sign is shown. The residual in time of adaptation depends on state of biosystem's unit at the moment of perturbation.

  1. 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.

  2. Development of an Ontology-Directed Signal Processing Toolbox

    SciTech Connect

    Stephen W. Lang

    2011-05-27

    This project was focused on the development of tools for the automatic configuration of signal processing systems. The goal is to develop tools that will be useful in a variety of Government and commercial areas and useable by people who are not signal processing experts. In order to get the most benefit from signal processing techniques, deep technical expertise is often required in order to select appropriate algorithms, combine them into a processing chain, and tune algorithm parameters for best performance on a specific problem. Therefore a significant benefit would result from the assembly of a toolbox of processing algorithms that has been selected for their effectiveness in a group of related problem areas, along with the means to allow people who are not signal processing experts to reliably select, combine, and tune these algorithms to solve specific problems. Defining a vocabulary for problem domain experts that is sufficiently expressive to drive the configuration of signal processing functions will allow the expertise of signal processing experts to be captured in rules for automated configuration. In order to test the feasibility of this approach, we addressed a lightning classification problem, which was proposed by DOE as a surrogate for problems encountered in nuclear nonproliferation data processing. We coded a toolbox of low-level signal processing algorithms for extracting features of RF waveforms, and demonstrated a prototype tool for screening data. We showed examples of using the tool for expediting the generation of ground-truth metadata, for training a signal recognizer, and for searching for signals with particular characteristics. The public benefits of this approach, if successful, will accrue to Government and commercial activities that face the same general problem - the development of sensor systems for complex environments. It will enable problem domain experts (e.g. analysts) to construct signal and image processing chains without

  3. Information processing in multi-step signaling pathways

    NASA Astrophysics Data System (ADS)

    Ganesan, Ambhi; Hamidzadeh, Archer; Zhang, Jin; Levchenko, Andre

    Information processing in complex signaling networks is limited by a high degree of variability in the abundance and activity of biochemical reactions (biological noise) operating in living cells. In this context, it is particularly surprising that many signaling pathways found in eukaryotic cells are composed of long chains of biochemical reactions, which are expected to be subject to accumulating noise and delayed signal processing. Here, we challenge the notion that signaling pathways are insulated chains, and rather view them as parts of extensively branched networks, which can benefit from a low degree of interference between signaling components. We further establish conditions under which this pathway organization would limit noise accumulation, and provide evidence for this type of signal processing in an experimental model of a calcium-activated MAPK cascade. These results address the long-standing problem of diverse organization and structure of signaling networks in live cells.

  4. Advanced Digital Signal Processing for Hybrid Lidar

    DTIC Science & Technology

    2012-12-31

    in the sense that this is the first point at which point the signal magnitude is maximum. On the other extreme, as c becomes large (high turbidity ...centimeter intervals in a 3.6 meter long water tank at varying turbidities [4]. In this preliminary experiment, the single delay line canceler was...in Through-the-Wall Radar Imaging," IEEE Transactions on Geoscience and Remote Sensing , vol. 47, no. 9, pp. 3192-3208, Sept. 2009. [3] Zege, E.P

  5. Advanced Digital Signal Processing for Hybrid Lidar

    DTIC Science & Technology

    2013-12-31

    signal separation. Previous work was reported at the Oceans 󈧑 conference. Frequency Domain Reflectometry In an attempt overcome the unambiguous...respectively. The phase function of Maalox antacid was used as an input to the simulation program. In addition, the effect of integration time on...configuration as the simulations. The object position was fixed at the maximum distance while the turbidity was varied by dissolving Equate antacid into the

  6. Statistical measures of Planck scale signal correlations in interferometers

    SciTech Connect

    Hogan, Craig J.; Kwon, Ohkyung

    2015-06-22

    A model-independent statistical framework is presented to interpret data from systems where the mean time derivative of positional cross correlation between world lines, a measure of spreading in a quantum geometrical wave function, is measured with a precision smaller than the Planck time. The framework provides a general way to constrain possible departures from perfect independence of classical world lines, associated with Planck scale bounds on positional information. A parametrized candidate set of possible correlation functions is shown to be consistent with the known causal structure of the classical geometry measured by an apparatus, and the holographic scaling of information suggested by gravity. Frequency-domain power spectra are derived that can be compared with interferometer data. As a result, simple projections of sensitivity for specific experimental set-ups suggests that measurements will directly yield constraints on a universal time derivative of the correlation function, and thereby confirm or rule out a class of Planck scale departures from classical geometry.

  7. Artificial intelligence applied to process signal analysis

    NASA Technical Reports Server (NTRS)

    Corsberg, Dan

    1988-01-01

    Many space station processes are highly complex systems subject to sudden, major transients. In any complex process control system, a critical aspect of the human/machine interface is the analysis and display of process information. Human operators can be overwhelmed by large clusters of alarms that inhibit their ability to diagnose and respond to a disturbance. Using artificial intelligence techniques and a knowledge base approach to this problem, the power of the computer can be used to filter and analyze plant sensor data. This will provide operators with a better description of the process state. Once a process state is recognized, automatic action could be initiated and proper system response monitored.

  8. Classification of Acousto-Optic Correlation Signatures of Spread Spectrum Signals Using Artificial Neural Networks

    DTIC Science & Technology

    1989-12-01

    Ohio ’aPw iorlipuab muo i 0I2, AFIT/GE/ENG/89D-10 CLASSIFICATION OF ACOUSTO - OPTIC CORRELATION SIGNATURES OF SPREAD SPECTRUM SIGNALS USING ARTIFICIAL...ENG/89D- 10 CLASSIFICATION OF ACOUSTO - OPTIC CORRELATION SIGNATURES OF SPREAD SPECTRUM SIGNALS USING ARTIFICIAL NEURAL NETWORKS THESIS John W. DeBerry...Captain, USAF AFIT/GE/ENG/89D- 10 Approved for public release; distribution unlimited. AFIT/GE/ENG/89D-10 CLASSIFICATION OF ACOUSTO - OPTIC CORRELATION

  9. Local Quantum Measurement and No-Signaling Imply Quantum Correlations

    NASA Astrophysics Data System (ADS)

    Barnum, H.; Beigi, S.; Boixo, S.; Elliott, M. B.; Wehner, S.

    2010-04-01

    We show that, assuming that quantum mechanics holds locally, the finite speed of information is the principle that limits all possible correlations between distant parties to be quantum mechanical as well. Local quantum mechanics means that a Hilbert space is assigned to each party, and then all local positive-operator-valued measurements are (in principle) available; however, the joint system is not necessarily described by a Hilbert space. In particular, we do not assume the tensor product formalism between the joint systems. Our result shows that if any experiment would give nonlocal correlations beyond quantum mechanics, quantum theory would be invalidated even locally.

  10. Local quantum measurement and no-signaling imply quantum correlations.

    PubMed

    Barnum, H; Beigi, S; Boixo, S; Elliott, M B; Wehner, S

    2010-04-09

    We show that, assuming that quantum mechanics holds locally, the finite speed of information is the principle that limits all possible correlations between distant parties to be quantum mechanical as well. Local quantum mechanics means that a Hilbert space is assigned to each party, and then all local positive-operator-valued measurements are (in principle) available; however, the joint system is not necessarily described by a Hilbert space. In particular, we do not assume the tensor product formalism between the joint systems. Our result shows that if any experiment would give nonlocal correlations beyond quantum mechanics, quantum theory would be invalidated even locally.

  11. Evaluation of laser Doppler flowmetry system with fast signal processing using an autoregressive process model

    NASA Astrophysics Data System (ADS)

    Elter, Peter; Stork, Wilhelm; Mueller-Glaser, Klaus-Dieter; Lutter, Norbert O.

    1999-05-01

    This report describes the evaluation of a noninvasive laser Doppler system comprising a sensor, a digital signal processor (DSP) unit and a visualizing PC for continuous blood flow measurements. The first weighted moment of the power spectrum density of the laser Doppler sensor signal is a linear measure for blood flow. In order to estimate the power spectrum densities in real time, a first order autoregressive process model was developed. Due to this very fast signal processing, the system allows measurements both in microcirculation and of higher blood flows in larger vessels with a signal bandwidth of up to 200 kHz, e.g. in superficial arteries. Since the analytical dependency of blood flow and first spectral moment is only valid for tissue perfusion, Monte Carlo simulations were performed to evaluate this dependency also for higher blood flow velocities in larger vessels. A multilayered, semi- infinite tissue model essentially comprising epidermis, dermis and a blood vessel with a parabolic profile of constant blood flow was used varying different parameter like vessel diameter and skin thickness. Furthermore, model measurements were performed using a Delrine slab with a drilling through which constant flow of whole blood was provided. Both the Monte Carlo simulations and model measurements prove very high linear correlations between the calculated spectral moments and flow velocities.

  12. Electrophysiological Correlates of Stimulus Equivalence Processes

    PubMed Central

    Haimson, Barry; Wilkinson, Krista M; Rosenquist, Celia; Ouimet, Carolyn; McIlvane, William J

    2009-01-01

    Research reported here concerns neural processes relating to stimulus equivalence class formation. In Experiment 1, two types of word pairs were presented successively to normally capable adults. In one type, the words had related usage in English (e.g., uncle, aunt). In the other, the two words were not typically related in their usage (e.g., wrist, corn). For pairs of both types, event-related cortical potentials were recorded during and immediately after the presentation of the second word. The obtained waveforms differentiated these two types of pairs. For the unrelated pairs, the waveforms were significantly more negative about 400 ms after the second word was presented, thus replicating the “N400” phenomenon of the cognitive neuroscience literature. In addition, there was a strong positive-tending wave form difference post-stimulus presentation (peaked at about 500 ms) that also differentiated the unrelated from related stimulus pairs. In Experiment 2, the procedures were extended to study arbitrary stimulus–stimulus relations established via matching-to-sample training. Participants were experimentally naïve adults. Sample stimuli (Set A) were trigrams, and comparison stimuli (Sets B, C, D, E, and F) were nonrepresentative forms. Behavioral tests evaluated potentially emergent equivalence relations (i.e., BD, DF, CE, etc.). All participants exhibited classes consistent with the arbitrary matching training. They were also exposed also to an event-related potential procedure like that used in Experiment 1. Some received the ERP procedure before equivalence tests and some after. Only those participants who received ERP procedures after equivalence tests exhibited robust N400 differentiation initially. The positivity observed in Experiment 1 was absent for all participants. These results support speculations that equivalence tests may provide contextual support for the formation of equivalence classes including those that emerge gradually during testing

  13. 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.

  14. 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

  15. Solar axion search technique with correlated signals from multiple detectors

    DOE PAGES

    Xu, Wenqin; Elliott, Steven R.

    2017-01-25

    The coherent Bragg scattering of photons converted from solar axions inside crystals would boost the signal for axion-photon coupling enhancing experimental sensitivity for these hypothetical particles. Knowledge of the scattering angle of solar axions with respect to the crystal lattice is required to make theoretical predications of signal strength. Hence, both the lattice axis angle within a crystal and the absolute angle between the crystal and the Sun must be known. In this paper, we examine how the experimental sensitivity changes with respect to various experimental parameters. We also demonstrate that, in a multiple-crystal setup, knowledge of the relative axismore » orientation between multiple crystals can improve the experimental sensitivity, or equivalently, relax the precision on the absolute solar angle measurement. However, if absolute angles of all crystal axes are measured, we find that a precision of 2°–4° will suffice for an energy resolution of σE = 0.04E and a flat background. Lastly, we also show that, given a minimum number of detectors, a signal model averaged over angles can substitute for precise crystal angular measurements, with some loss of sensitivity.« less

  16. Solar axion search technique with correlated signals from multiple detectors

    NASA Astrophysics Data System (ADS)

    Xu, Wenqin; Elliott, Steven R.

    2017-03-01

    The coherent Bragg scattering of photons converted from solar axions inside crystals would boost the signal for axion-photon coupling enhancing experimental sensitivity for these hypothetical particles. Knowledge of the scattering angle of solar axions with respect to the crystal lattice is required to make theoretical predications of signal strength. Hence, both the lattice axis angle within a crystal and the absolute angle between the crystal and the Sun must be known. In this paper, we examine how the experimental sensitivity changes with respect to various experimental parameters. We also demonstrate that, in a multiple-crystal setup, knowledge of the relative axis orientation between multiple crystals can improve the experimental sensitivity, or equivalently, relax the precision on the absolute solar angle measurement. However, if absolute angles of all crystal axes are measured, we find that a precision of 2∘ -4∘ will suffice for an energy resolution of σE = 0.04 E and a flat background. Finally, we also show that, given a minimum number of detectors, a signal model averaged over angles can substitute for precise crystal angular measurements, with some loss of sensitivity.

  17. Correlation Loss of a Gaussian Signal Passed Through an Odd Quantizer.

    DTIC Science & Technology

    The correlation coefficient of input signal component and quantizer output is shown to...be a weighted version of the corresponding input correlation coefficient . Furthermore, intervals of input rms voltage exist over which a given linear quantizer should be operated to minimize correlation loss. (Author)

  18. Signal processing at the Poker Flat MST radar

    NASA Technical Reports Server (NTRS)

    Carter, D. A.

    1983-01-01

    Signal processing for Mesosphere-Stratosphere-Troposphere (MST) radar is carried out by a combination of hardware in high-speed, special-purpose devices and software in a general-purpose, minicomputer/array processor. A block diagram of the signal processing system is presented, and the steps in the processing pathway are described. The current processing capabilities are given, and a system offering greater coherent integration speed is advanced which hinges upon a high speed preprocessor.

  19. Innovative signal processing for Johnson Noise thermometry

    SciTech Connect

    Ezell, N. Dianne Bull; Britton, Jr, Charles L.; Roberts, Michael

    2016-07-01

    This report summarizes the newly developed algorithm that subtracted the Electromagnetic Interference (EMI). The EMI performance is very important to this measurement because any interference in the form on pickup from external signal sources from such as fluorescent lighting ballasts, motors, etc. can skew the measurement. Two methods of removing EMI were developed and tested at various locations. This report also summarizes the testing performed at different facilities outside Oak Ridge National Laboratory using both EMI removal techniques. The first EMI removal technique reviewed in previous milestone reports and therefore this report will detail the second method.

  20. Statistical measures of Planck scale signal correlations in interferometers

    NASA Astrophysics Data System (ADS)

    Hogan, Craig J.; Kwon, Ohkyung

    2017-04-01

    A model-independent statistical framework is presented to interpret data from systems where the mean time derivative of positional cross correlation between world lines, a measure of spreading in a quantum geometrical wave function, is measured with a precision smaller than the Planck time. The framework provides a general way to constrain possible departures from perfect independence of classical world lines, associated with Planck scale bounds on positional information. A parameterized candidate set of possible correlation functions is shown to be consistent with the known causal structure of the classical geometry measured by an apparatus, and the holographic scaling of information suggested by gravity. Frequency-domain power spectra are derived that can be compared with interferometer data. Simple projections of sensitivity for realistic experimental set-ups suggests that measurements will confirm or rule out a class of Planck scale departures from classical geometry.

  1. [Dynamic Pulse Signal Processing and Analyzing in Mobile System].

    PubMed

    Chou, Yongxin; Zhang, Aihua; Ou, Jiqing; Qi, Yusheng

    2015-09-01

    In order to derive dynamic pulse rate variability (DPRV) signal from dynamic pulse signal in real time, a method for extracting DPRV signal was proposed and a portable mobile monitoring system was designed. The system consists of a front end for collecting and wireless sending pulse signal and a mobile terminal. The proposed method is employed to extract DPRV from dynamic pulse signal in mobile terminal, and the DPRV signal is analyzed both in the time domain and the frequency domain and also with non-linear method in real time. The results show that the proposed method can accurately derive DPRV signal in real time, the system can be used for processing and analyzing DPRV signal in real time.

  2. Signal processing using artificial neural network for BOTDA sensor system.

    PubMed

    Azad, Abul Kalam; Wang, Liang; Guo, Nan; Tam, Hwa-Yaw; Lu, Chao

    2016-03-21

    We experimentally demonstrate the use of artificial neural network (ANN) to process sensing signals obtained from Brillouin optical time domain analyzer (BOTDA). The distributed temperature information is extracted directly from the local Brillouin gain spectra (BGSs) along the fiber under test without the process of determination of Brillouin frequency shift (BFS) and hence conversion from BFS to temperature. Unlike our previous work for short sensing distance where ANN is trained by measured BGSs, here we employ ideal BGSs with different linewidths to train the ANN in order to take the linewidth variation due to different conditions from the training and testing phases into account, making it feasible for long distance sensing. Moreover, the performance of ANN is compared with other two techniques, Lorentzian curve fitting and cross-correlation method, and our results show that ANN has higher accuracy and larger tolerance to measurement error, especially at large frequency scanning step. We also show that the temperature extraction from BOTDA measurements employing ANN is significantly faster than the other two approaches. Hence ANN can be an excellent alternative tool to process BGSs measured by BOTDA and obtain temperature distribution along the fiber, especially when large frequency scanning step is adopted to significantly reduce the measurement time but without sacrifice of sensing accuracy.

  3. Statistical mechanics and visual signal processing

    NASA Astrophysics Data System (ADS)

    Potters, Marc; Bialek, William

    1994-11-01

    We show how to use the language of statistical field theory to address and solve problems in which one must estimate some aspect of the environnent from the data in an array of sensors. In the field theory formulation the optimal estimator can be written as an expectation value in an ensemble where the input data act as external field. Problems at low signal-to-noise ratio can be solved in perturbation theory, while high signal-to-noise ratios are treated with a saddle-point approximation. These ideas are illustrated in detail by an example of visual motion estimation which is chosen to model a problem solved by the fly's brain. The optimal estimator bas a rich structure, adapting to various parameters of the environnent such as the mean-square contrast and the corrélation time of contrast fluctuations. This structure is in qualitative accord with existing measurements on motion sensitive neurons in the fly's brain, and the adaptive properties of the optimal estimator may help resolve conficts among different interpretations of these data. Finally we propose some crucial direct tests of the adaptive behavior. Nous montrons comment employer le langage de la théorie statistique des champs pour poser et résoudre des problèmes où l'on doit estimer une caractéristique de l'environnement à l'aide de données provenant d'un ensemble de détecteurs. Dans ce formalisme, l'estimateur optimal peut être écrit comme la valeur moyenne d'un opérateur, l'ensemble des données d'entrée agissant comme un champ externe. Les problèmes à faible rapport signal-bruit sont résolus par la théorie des perturbations. La méthode du col est employée pour ceux à haut rapport signal-bruit. Ces idées sont illustrées en détails sur un modèle d'estimation visuelle du mouvement basé sur un problème résolu par la mouche. L'estimateur optimal a une structure très riche, s'adaptant à divers paramètres de l'environnement tels la variance du contraste et le temps de corr

  4. Time reversal signal processing for communication.

    SciTech Connect

    Young, Derek P.; Jacklin, Neil; Punnoose, Ratish J.; Counsil, David T.

    2011-09-01

    Time-reversal is a wave focusing technique that makes use of the reciprocity of wireless propagation channels. It works particularly well in a cluttered environment with associated multipath reflection. This technique uses the multipath in the environment to increase focusing ability. Time-reversal can also be used to null signals, either to reduce unintentional interference or to prevent eavesdropping. It does not require controlled geometric placement of the transmit antennas. Unlike existing techniques it can work without line-of-sight. We have explored the performance of time-reversal focusing in a variety of simulated environments. We have also developed new algorithms to simultaneously focus at a location while nulling at an eavesdropper location. We have experimentally verified these techniques in a realistic cluttered environment.

  5. Processing electrophysiological signals for the monitoring of alertness

    NASA Technical Reports Server (NTRS)

    Lai, D. C.

    1974-01-01

    Mathematical techniques are described for processing EEG signals associated with varying states of alertness. Fast algorithms for implementing real-time computations of alertness estimates were developed. A realization of the phase-distortionless digital filter is presented which approaches real-time filtering and a transform for EEG signals. This transform provides information for the alertness estimates and can be performed in real time. A statistical test for stationarity in EEG signals is being developed that will provide a method for determining the duration of the EEG signals necessary for estimating the short-time power or energy spectra for nonstationary analysis of EEG signals.

  6. New signal processing technique for density profile reconstruction using reflectometry

    SciTech Connect

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

    2011-08-15

    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{sup 16} m{sup -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.

  7. 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

  8. [Detrended cross-correlation analysis: a new method for gait signal analysis].

    PubMed

    Wang, Pingping; Wang, Jun

    2012-12-01

    The cross-correlation of gait signal can mirror the health situations of different people. It is important to analyze the long-range cross correlations of the two signals of nonstationarity for medical research. In this paper, we propose a detrended cross-correlation analysis (DCCA) method for analyzing the different gait signal in physiological and pathological conditions. Our work dealt with three kinds of gait signals, including those of normal young people (23 to 29 years of age), those of healthy old people (71 to 77 years of age) and those of the old people (60 to 77 years of age) with Parkinson's disease from the MIT-BIH database. We carried out the DCCA for the three gait signals of nonstationarity. The results showed that the self-similarity of gait signal got more unstable with the age increasing and health status worsening. From the cross-correlation analysis, we found that the cross-correlation degree of gait signal of young people increased gradually, the healthy old people changed slowly and the Parkinson's disease patients showed unstable changes. We can make medical diagnosis and treatment according to the differences among different gait signals.

  9. Signal quality and Bayesian signal processing in neurofeedback based on real-time fMRI.

    PubMed

    Koush, Yury; Zvyagintsev, Mikhail; Dyck, Miriam; Mathiak, Krystyna A; Mathiak, Klaus

    2012-01-02

    Real-time fMRI allows analysis and visualization of the brain activity online, i.e. within one repetition time. It can be used in neurofeedback applications where subjects attempt to control an activation level in a specified region of interest (ROI) of their brain. The signal derived from the ROI is contaminated with noise and artifacts, namely with physiological noise from breathing and heart beat, scanner drift, motion-related artifacts and measurement noise. We developed a Bayesian approach to reduce noise and to remove artifacts in real-time using a modified Kalman filter. The system performs several signal processing operations: subtraction of constant and low-frequency signal components, spike removal and signal smoothing. Quantitative feedback signal quality analysis was used to estimate the quality of the neurofeedback time series and performance of the applied signal processing on different ROIs. The signal-to-noise ratio (SNR) across the entire time series and the group event-related SNR (eSNR) were significantly higher for the processed time series in comparison to the raw data. Applied signal processing improved the t-statistic increasing the significance of blood oxygen level-dependent (BOLD) signal changes. Accordingly, the contrast-to-noise ratio (CNR) of the feedback time series was improved as well. In addition, the data revealed increase of localized self-control across feedback sessions. The new signal processing approach provided reliable neurofeedback, performed precise artifacts removal, reduced noise, and required minimal manual adjustments of parameters. Advanced and fast online signal processing algorithms considerably increased the quality as well as the information content of the control signal which in turn resulted in higher contingency in the neurofeedback loop.

  10. A comb filter based signal processing method to effectively reduce motion artifacts from photoplethysmographic signals.

    PubMed

    Peng, Fulai; Liu, Hongyun; Wang, Weidong

    2015-10-01

    A photoplethysmographic (PPG) signal can provide very useful information about a subject's cardiovascular status. Motion artifacts (MAs), which usually deteriorate the waveform of a PPG signal, severely obstruct its applications in the clinical diagnosis and healthcare area. To reduce the MAs from a PPG signal, in the present study we present a comb filter based signal processing method. Firstly, wavelet de-noising was implemented to preliminarily suppress a part of the MAs. Then, the PPG signal in the time domain was transformed into the frequency domain by a fast Fourier transform (FFT). Thirdly, the PPG signal period was estimated from the frequency domain by tracking the fundamental frequency peak of the PPG signal. Lastly, the MAs were removed by the comb filter which was designed based on the obtained PPG signal period. Experiments with synthetic and real-world datasets were implemented to validate the performance of the method. Results show that the proposed method can effectively restore the PPG signals from the MA corrupted signals. Also, the accuracy of blood oxygen saturation (SpO2), calculated from red and infrared PPG signals, was significantly improved after the MA reduction by the proposed method. Our study demonstrates that the comb filter can effectively reduce the MAs from a PPG signal provided that the PPG signal period is obtained.

  11. Nonlinear Real-Time Optical Signal Processing

    DTIC Science & Technology

    1990-09-01

    parallelism and 3D global free interconnection capabilities. Finally, the instruction set and the programming of the DOCPs are illustrated. C 195 Academic ...Intelligence, Seattle, October, 1987, pp. 19-26. 2. J. Serra, Image Analysis and Mathematical Morphology, Academic Press. New York, 1982. 3. R. M...Technolo . for Parallel Image Processing (S. Levialdi, Ed.), pp. 79-100, Academic Press, New York, 1985. 13. J. Klein and J. Serra, The texture analyzer

  12. Parametric Techniques for Multichannel Signal Processing.

    DTIC Science & Technology

    1985-10-01

    Parameter Estimation," 7th IFAC Symposium on Identification and Sysstem Parameter Estimation, July 1985, York, United Kingdom. 21. B. Porat and B...1801 Page ill Road. Palo Alto, CA 94304. UrSA Boaz PORAT Department ot Electrical Engineering . Technwon, Israel Institute of Technology, Haifa...is a zero-mean white noise many engineering applications. A common model process with variance cr: , and v, is the observed for a wide-sense

  13. The Signal Processing and Communications (SPC) toolbox, release 2

    NASA Astrophysics Data System (ADS)

    Brown, Dennis W.; Fargues, Monique P.

    1995-09-01

    The SPC (Signal Processing & Communications) toolbox is a software package designed to provide the user with a series of data manipulation tools which use MATLAB v.4 graphical user interface controls SPC can be used in the classroom to illustrate and to reinforce basic concepts in digital signal processing and communications. It frees the user from having to write and debug his/her own code and gives him/her more time to understand the advantages and drawbacks of each technique included in the package. It can also be used as a basic analysis and modeling tool for research in Signal Processing.

  14. Fault Tolerant Statistical Signal Processing Algorithms for Parallel Architectures.

    DTIC Science & Technology

    2014-09-26

    AD-fi57 393 FAULT TOLERANT STATISTICAL SIGNAL PROCESSING ALGORITHMS i/i FOR PARALLEL ARCH U) JOHNS HOPKINS UNIV BALTIMORE MD DEPT OF ELECTRICAL...COVERED * ’ Fault Tolerant Statistical Signal Processing Technical A l g o r i t h m s f o r P a r a l l e l A r c h i t e c t u r e s a ._ P E R F O R M I...Identify by block number) , Fault Tolerance, Signal Processing, Parallel Architecture 0 20. ABSTRACT (Continue on reveree side It neceseary and identify by

  15. Preliminary development of digital signal processing in microwave radiometers

    NASA Technical Reports Server (NTRS)

    Stanley, W. D.

    1980-01-01

    Topics covered involve a number of closely related tasks including: the development of several control loop and dynamic noise model computer programs for simulating microwave radiometer measurements; computer modeling of an existing stepped frequency radiometer in an effort to determine its optimum operational characteristics; investigation of the classical second order analog control loop to determine its ability to reduce the estimation error in a microwave radiometer; investigation of several digital signal processing unit designs; initiation of efforts to develop required hardware and software for implementation of the digital signal processing unit; and investigation of the general characteristics and peculiarities of digital processing noiselike microwave radiometer signals.

  16. A Review on Sensor, Signal, and Information Processing Algorithms (PREPRINT)

    DTIC Science & Technology

    2010-01-01

    ratio , and tonality [66]. The number of speakers in the speech signals was determined by analyzing the mod- ulation characteristics of the signals in...gorithms combined local decisions that were corrupted during the transmission process due to channel fading. Also, a new likelihood ratio based test was...maximizes the signal-to-noise ratio (SNR) at the fusion C-11 TRANSMISSION PHASE TRAINING PHASE ( fixed ) trn tot P P - trn P tot P

  17. Physics-based signal processing algorithms for micromachined cantilever arrays

    DOEpatents

    Candy, James V; Clague, David S; Lee, Christopher L; Rudd, Robert E; Burnham, Alan K; Tringe, Joseph W

    2013-11-19

    A method of using physics-based signal processing algorithms for micromachined cantilever arrays. The methods utilize deflection of a micromachined cantilever that represents the chemical, biological, or physical element being detected. One embodiment of the method comprises the steps of modeling the deflection of the micromachined cantilever producing a deflection model, sensing the deflection of the micromachined cantilever and producing a signal representing the deflection, and comparing the signal representing the deflection with the deflection model.

  18. Enhanced correlation of received power-signal fluctuations in bidirectional optical links

    NASA Astrophysics Data System (ADS)

    Minet, Jean; Vorontsov, Mikhail A.; Polnau, Ernst; Dolfi, Daniel

    2013-02-01

    A study of the correlation between the power signals received at both ends of bidirectional free-space optical links is presented. By use of the quasi-optical approximation, we show that an ideal (theoretically 100%) power-signal correlation can be achieved in optical links with specially designed monostatic transceivers based on single-mode fiber collimators. The theoretical prediction of enhanced correlation is supported both by experiments conducted over a 7 km atmospheric path and wave optics numerical analysis of the corresponding bidirectional optical link. In the numerical simulations, we also compare correlation properties of received power signals for different atmospheric conditions and for optical links with monostatic and bistatic geometries based on single-mode fiber collimator and on power-in-the-bucket transceiver types. Applications of the observed phenomena for signal fading mitigation and turbulence-enhanced communication link security in free-space laser communication links are discussed.

  19. Auxiliary signal processing system for a multiparameter radar

    NASA Technical Reports Server (NTRS)

    Chandrasekar, V.; Gray, G. R.; Caylor, I. J.

    1993-01-01

    The design of an auxiliary signal processor for a multiparameter radar is described with emphasis on low cost, quick development, and minimum disruption of radar operations. The processor is based around a low-cost digital signal processor card and personal computer controller. With the use of such a concept, an auxiliary processor was implemented for the NCAR CP-2 radar during a 1991 summer field campaign and allowed measurement of additional polarimetric parameters, namely, the differential phase and the copolar cross correlation. Sample data are presented from both the auxiliary and existing radar signal processors.

  20. Modeling laser velocimeter signals as triply stochastic Poisson processes

    NASA Technical Reports Server (NTRS)

    Mayo, W. T., Jr.

    1976-01-01

    Previous models of laser Doppler velocimeter (LDV) systems have not adequately described dual-scatter signals in a manner useful for analysis and simulation of low-level photon-limited signals. At low photon rates, an LDV signal at the output of a photomultiplier tube is a compound nonhomogeneous filtered Poisson process, whose intensity function is another (slower) Poisson process with the nonstationary rate and frequency parameters controlled by a random flow (slowest) process. In the present paper, generalized Poisson shot noise models are developed for low-level LDV signals. Theoretical results useful in detection error analysis and simulation are presented, along with measurements of burst amplitude statistics. Computer generated simulations illustrate the difference between Gaussian and Poisson models of low-level signals.

  1. Understanding the effects of pre-processing on extracted signal features from gait accelerometry signals.

    PubMed

    Millecamps, Alexandre; Lowry, Kristin A; Brach, Jennifer S; Perera, Subashan; Redfern, Mark S; Sejdić, Ervin

    2015-07-01

    Gait accelerometry is an important approach for gait assessment. Previous contributions have adopted various pre-processing approaches for gait accelerometry signals, but none have thoroughly investigated the effects of such pre-processing operations on the obtained results. Therefore, this paper investigated the influence of pre-processing operations on signal features extracted from gait accelerometry signals. These signals were collected from 35 participants aged over 65years: 14 of them were healthy controls (HC), 10 had Parkinson׳s disease (PD) and 11 had peripheral neuropathy (PN). The participants walked on a treadmill at preferred speed. Signal features in time, frequency and time-frequency domains were computed for both raw and pre-processed signals. The pre-processing stage consisted of applying tilt correction and denoising operations to acquired signals. We first examined the effects of these operations separately, followed by the investigation of their joint effects. Several important observations were made based on the obtained results. First, the denoising operation alone had almost no effects in comparison to the trends observed in the raw data. Second, the tilt correction affected the reported results to a certain degree, which could lead to a better discrimination between groups. Third, the combination of the two pre-processing operations yielded similar trends as the tilt correction alone. These results indicated that while gait accelerometry is a valuable approach for the gait assessment, one has to carefully adopt any pre-processing steps as they alter the observed findings.

  2. Multiwavelength micropulse lidar in atmospheric aerosol study: signal processing

    NASA Astrophysics Data System (ADS)

    Posyniak, Michal; Malinowski, Szymon P.; Stacewicz, Tadeusz; Markowicz, Krzysztof M.; Zielinski, Tymon; Petelski, Tomasz; Makuch, Przemyslaw

    2011-11-01

    Multiwavelength micropulse lidar (MML) designed for continuous optical sounding of the atmosphere is presented. A specific signal processing technique applying two directional Kalman filtering is introduced in order to enhance signal to noise ratio. Application of this technique is illustrated with profiles collected in course of COAST 2009 and WRNP 2010 research campaigns.

  3. Advanced Integrated Optical Signal Processing Components.

    NASA Astrophysics Data System (ADS)

    Rastani, Kasra

    This research was aimed at the development of advanced integrated optical components suitable for devices capable of processing multi-dimensional inputs. In such processors, densely packed waveguide arrays with low crosstalk are needed to provide dissection of the information that has been partially processed. Waveguide arrays also expand the information in the plane of the processor while maintaining its coherence. Rib waveguide arrays with low loss, high mode confinement and highly uniform surface quality (660 elements, 8 μm wide, 1 μm high, and 1 cm long with 2 mu m separations) were fabricated on LiNbO _3 substrates through the ion beam milling technique. A novel feature of the multi-dimensional IO processor architecture proposed herein is the implementation of large area uniform outcoupling (with low to moderate outcoupling efficiencies) from rib waveguide arrays in order to access the third dimension of the processor structure. As a means of outcoupling, uniform surface gratings (2 μm and 4 μm grating periods, 0.05 μm high and 1 mm long) with low outcoupling efficiencies (of approximately 2-18%/mm) were fabricated on the nonuniform surface of the rib waveguide arrays. As a practical technique of modulating the low outcoupling efficiencies of the surface gratings, it was proposed to alter the period of the grating as a function of position along each waveguide. Large aperture (2.5 mm) integrated lenses with short positive focal lengths (1.2-2.5 cm) were developed through a modification of the titanium-indiffused proton exchanged (TIPE) technique. Such integrated lenses were fabricated by increasing the refractive index of the slab waveguides by the TIPE process while maintaining the refractive index of the lenses at the lower level of Ti:LiNbO _3 waveguide. By means of curvature reversal of the integrated lenses, positive focal length lenses have been fabricated while providing high mode confinement for the slab waveguide. The above elements performed as

  4. HYMOSS signal processing for pushbroom spectral imaging

    NASA Technical Reports Server (NTRS)

    Ludwig, David E.

    1991-01-01

    The objective of the Pushbroom Spectral Imaging Program was to develop on-focal plane electronics which compensate for detector array non-uniformities. The approach taken was to implement a simple two point calibration algorithm on focal plane which allows for offset and linear gain correction. The key on focal plane features which made this technique feasible was the use of a high quality transimpedance amplifier (TIA) and an analog-to-digital converter for each detector channel. Gain compensation is accomplished by varying the feedback capacitance of the integrate and dump TIA. Offset correction is performed by storing offsets in a special on focal plane offset register and digitally subtracting the offsets from the readout data during the multiplexing operation. A custom integrated circuit was designed, fabricated, and tested on this program which proved that nonuniformity compensated, analog-to-digital converting circuits may be used to read out infrared detectors. Irvine Sensors Corporation (ISC) successfully demonstrated the following innovative on-focal-plane functions that allow for correction of detector non-uniformities. Most of the circuit functions demonstrated on this program are finding their way onto future IC's because of their impact on reduced downstream processing, increased focal plane performance, simplified focal plane control, reduced number of dewar connections, as well as the noise immunity of a digital interface dewar. The potential commercial applications for this integrated circuit are primarily in imaging systems. These imaging systems may be used for: security monitoring systems, manufacturing process monitoring, robotics, and for spectral imaging when used in analytical instrumentation.

  5. Signal processing techniques for synchronization of wireless sensor networks

    NASA Astrophysics Data System (ADS)

    Lee, Jaehan; Wu, Yik-Chung; Chaudhari, Qasim; Qaraqe, Khalid; Serpedin, Erchin

    2010-11-01

    Clock synchronization is a critical component in wireless sensor networks, as it provides a common time frame to different nodes. It supports functions such as fusing voice and video data from different sensor nodes, time-based channel sharing, and sleep wake-up scheduling, etc. Early studies on clock synchronization for wireless sensor networks mainly focus on protocol design. However, clock synchronization problem is inherently related to parameter estimation, and recently, studies of clock synchronization from the signal processing viewpoint started to emerge. In this article, a survey of latest advances on clock synchronization is provided by adopting a signal processing viewpoint. We demonstrate that many existing and intuitive clock synchronization protocols can be interpreted by common statistical signal processing methods. Furthermore, the use of advanced signal processing techniques for deriving optimal clock synchronization algorithms under challenging scenarios will be illustrated.

  6. Comparative analysis of genomic signal processing for microarray data clustering.

    PubMed

    Istepanian, Robert S H; Sungoor, Ala; Nebel, Jean-Christophe

    2011-12-01

    Genomic signal processing is a new area of research that combines advanced digital signal processing methodologies for enhanced genetic data analysis. It has many promising applications in bioinformatics and next generation of healthcare systems, in particular, in the field of microarray data clustering. In this paper we present a comparative performance analysis of enhanced digital spectral analysis methods for robust clustering of gene expression across multiple microarray data samples. Three digital signal processing methods: linear predictive coding, wavelet decomposition, and fractal dimension are studied to provide a comparative evaluation of the clustering performance of these methods on several microarray datasets. The results of this study show that the fractal approach provides the best clustering accuracy compared to other digital signal processing and well known statistical methods.

  7. 28. Perimeter acquisition radar building room #302, signal process and ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    28. Perimeter acquisition radar building room #302, signal process and analog receiver room - Stanley R. Mickelsen Safeguard Complex, Perimeter Acquisition Radar Building, Limited Access Area, between Limited Access Patrol Road & Service Road A, Nekoma, Cavalier County, ND

  8. Array signal processing in the NASA Deep Space Network

    NASA Technical Reports Server (NTRS)

    Pham, Timothy T.; Jongeling, Andre P.

    2004-01-01

    In this paper, we will describe the benefits of arraying and past as well as expected future use of this application. The signal processing aspects of array system are described. Field measurements via actual tracking spacecraft are also presented.

  9. An algorithm for signal processing in multibeam antenna arrays

    NASA Astrophysics Data System (ADS)

    Danilevskii, L. N.; Domanov, Iu. A.; Korobko, O. V.

    1980-09-01

    A signal processing method for multibeam antenna arrays is presented which can be used to effectively reduce discrete-phasing sidelobes. Calculations of an 11-element array are presented as an example.

  10. Software for biomedical engineering signal processing laboratory experiments.

    PubMed

    Tompkins, Willis J; Wilson, J

    2009-01-01

    In the early 1990's we developed a special computer program called UW DigiScope to provide a mechanism for anyone interested in biomedical digital signal processing to study the field without requiring any other instrument except a personal computer. There are many digital filtering and pattern recognition algorithms used in processing biomedical signals. In general, students have very limited opportunity to have hands-on access to the mechanisms of digital signal processing. In a typical course, the filters are designed non-interactively, which does not provide the student with significant understanding of the design constraints of such filters nor their actual performance characteristics. UW DigiScope 3.0 is the first major update since version 2.0 was released in 1994. This paper provides details on how the new version based on MATLAB! works with signals, including the filter design tool that is the programming interface between UW DigiScope and processing algorithms.

  11. Optical Signal Processing: Poisson Image Restoration and Shearing Interferometry

    NASA Technical Reports Server (NTRS)

    Hong, Yie-Ming

    1973-01-01

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

  12. 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.

  13. Unveiling linearly and nonlinearly correlated signals between gravitational wave detectors and environmental monitors

    NASA Astrophysics Data System (ADS)

    Yuzurihara, Hirotaka; Hayama, Kazuhiro; Mano, Shuhei; Verkindt, Didier; Kanda, Nobuyuki

    2016-08-01

    Noise hunting is a critical requirement for realizing design sensitivity of a detector, and consequently, noise origins and its features have been revealed partially. Among the noise sources to be hunted, sources of nonlinearly correlated noise, such up-conversion noise, are hard to find and can limit the sensitivity of gravitational wave searches with advanced detectors. We propose using a correlation analysis method called maximal information coefficient (MIC) to find both nonlinear and linear correlations. We apply MIC to the scattered light noise correlated between the seismic activity and the strain signal, which limited the sensitivity of the Virgo detector during the first science run. The results show that MIC can find nonlinearly correlated noise more efficiently than the Pearson correlation method. When the data is linearly correlated, the efficiency of the Pearson method and MIC is comparable. On the other hand, when the data is known to be nonlinearly correlated, MIC finds the correlation while the Pearson method fails completely.

  14. Visualizing confusion matrices for multidimensional signal detection correlational methods

    NASA Astrophysics Data System (ADS)

    Zhou, Yue; Wischgoll, Thomas; Blaha, Leslie M.; Smith, Ross; Vickery, Rhonda J.

    2013-12-01

    Advances in modeling and simulation for General Recognition Theory have produced more data than can be easily visualized using traditional techniques. In this area of psychological modeling, domain experts are struggling to find effective ways to compare large-scale simulation results. This paper describes methods that adapt the web-based D3 visualization framework combined with pre-processing tools to enable domain specialists to more easily interpret their data. The D3 framework utilizes Javascript and scalable vector graphics (SVG) to generate visualizations that can run readily within the web browser for domain specialists. Parallel coordinate plots and heat maps were developed for identification-confusion matrix data, and the results were shown to a GRT expert for an informal evaluation of their utility. There is a clear benefit to model interpretation from these visualizations when researchers need to interpret larger amounts of simulated data.

  15. Waveguide Studies for Fiber Optics and Optical Signal Processing Applications.

    DTIC Science & Technology

    1980-04-01

    beam expander is shown in Fig. 2 -i. The beam, which is expanded to approximately 100 Wm, can be deflected acousto - optically to make a spectrum analyzer...3 2 . DBR Lasers for Fiber Optics and Optical Signal Processing Sources ......... ................. 4 4. Studies of LiNbO 3...6 Chapter 1. Wave Beam Expansion ....... ............. 9 Chapter 2 . DBR Lasers for Fiber Optics and Optical Signal Processing Sources

  16. The Signal Processing Firmware for the Low Frequency Aperture Array

    NASA Astrophysics Data System (ADS)

    Comoretto, Gianni; Chiello, Riccardo; Roberts, Matt; Halsall, Rob; Adami, Kristian Zarb; Alderighi, Monica; Aminaei, Amin; Baker, Jeremy; Belli, Carolina; Chiarucci, Simone; D’Angelo, Sergio; De Marco, Andrea; Mura, Gabriele Dalle; Magro, Alessio; Mattana, Andrea; Monari, Jader; Naldi, Giovanni; Pastore, Sandro; Perini, Federico; Poloni, Marco; Pupillo, Giuseppe; Rusticelli, Simone; Schiaffino, Marco; Schillirò, Francesco; Zaccaro, Emanuele

    The signal processing firmware that has been developed for the Low Frequency Aperture Array component of the Square Kilometre Array (SKA) is described. The firmware is implemented on a dual FPGA board, that is capable of processing the streams from 16 dual polarization antennas. Data processing includes channelization of the sampled data for each antenna, correction for instrumental response and for geometric delays and formation of one or more beams by combining the aligned streams. The channelizer uses an oversampling polyphase filterbank architecture, allowing a frequency continuous processing of the input signal without discontinuities between spectral channels. Each board processes the streams from 16 antennas, as part of larger beamforming system, linked by standard Ethernet interconnections. These are envisaged to be 8192 of these signal processing platforms in the first phase of the SKA so particular attention has been devoted to ensure the design is low cost and low power.

  17. The correlated characteristics of micro-seismic and electromagnetic radiation signals on a deep blasting workface

    NASA Astrophysics Data System (ADS)

    Li, Chengwu; Sun, Xiaoyuan; Wang, Chuan; Xu, Xiaomeng; Xie, Beijing; Li, Jing

    2016-12-01

    To date, both micro-seismic (MS) and electromagnetic radiation (EMR) techniques are used as normal, daily safety monitoring tools for coal or rock dynamic disasters in China. In previous studies, these two non-destructive techniques are usually analyzed independently; few works have been done to characterize the correlation or difference between them. This paper aims to analyze the correlated features of the MS and EMR signals obtained from a field site test on a deep blasting workface in Pingdingshan 10# coal colliery. The de-noised signals are firstly compared for their associated features, both in time synchronization and energy correlation, and then the mechanism for the correlated response is also investigated. The results show that: (1) MS and EMR signals have a higher time-synchronization and energy correlation. (2) The EMR signal in a blasting operation is a local signal, near to the location of the detectors. (3) The two orthogonal layout magnetic antennas (along the roadway and vertical to the coal wall) can detect a single pulse signal and group-occurring cluster signals. These two kinds of EMR signals result from coal crack evolution and resistance-capacitance (RC) oscillation circuits respectively, which are triggered by seismic longitudinal waves. (4) The seismic transverse wave, especially for the low frequency component of it, makes a rubbing friction effect on coal, producing a low-frequency electromagnetic oscillation signal. Affected by the power and propagation direction of the energy, the signal can only be captured by the antenna in the vertical direction of the coal wall.

  18. Techniques of EMG signal analysis: detection, processing, classification and applications

    PubMed Central

    Hussain, M.S.; Mohd-Yasin, F.

    2006-01-01

    Electromyography (EMG) signals can be used for clinical/biomedical applications, Evolvable Hardware Chip (EHW) development, and modern human computer interaction. EMG signals acquired from muscles require advanced methods for detection, decomposition, processing, and classification. The purpose of this paper is to illustrate the various methodologies and algorithms for EMG signal analysis to provide efficient and effective ways of understanding the signal and its nature. We further point up some of the hardware implementations using EMG focusing on applications related to prosthetic hand control, grasp recognition, and human computer interaction. A comparison study is also given to show performance of various EMG signal analysis methods. This paper provides researchers a good understanding of EMG signal and its analysis procedures. This knowledge will help them develop more powerful, flexible, and efficient applications. PMID:16799694

  19. Signal-processing theory for the TurboRogue receiver

    NASA Technical Reports Server (NTRS)

    Thomas, J. B.

    1995-01-01

    Signal-processing theory for the TurboRogue receiver is presented. The signal form is traced from its formation at the GPS satellite, to the receiver antenna, and then through the various stages of the receiver, including extraction of phase and delay. The analysis treats the effects of ionosphere, troposphere, signal quantization, receiver components, and system noise, covering processing in both the 'code mode' when the P code is not encrypted and in the 'P-codeless mode' when the P code is encrypted. As a possible future improvement to the current analog front end, an example of a highly digital front end is analyzed.

  20. Neural Correlates of Semantic Competition during Processing of Ambiguous Words

    ERIC Educational Resources Information Center

    Bilenko, Natalia Y.; Grindrod, Christopher M.; Myers, Emily B.; Blumstein, Sheila E.

    2009-01-01

    The current study investigated the neural correlates that underlie the processing of ambiguous words and the potential effects of semantic competition on that processing. Participants performed speeded lexical decisions on semantically related and unrelated prime-target pairs presented in the auditory modality. The primes were either ambiguous…

  1. Conjugate spectrum filters for eddy current signal processing

    SciTech Connect

    Stepinski, T.; Maszi, N. . Dept. of Technology.)

    1993-07-01

    The paper addresses the problem of detection and classification of material defects during eddy current inspection. Digital signal processing algorithms for detection and characterization of flaws are considered and a new type of filter for classification of eddy current data is proposed. In the first part of the paper the signal processing blocks used in modern eddy current instruments are presented and analyzed in terms of information transmission. The processing usually consists of two steps: detection by means of amplitude-phase detectors and filtering of the detector output signals by means of analog signal filters. Distortion introduced by the signal filters is considered and illustrated using real eddy current responses. The nature of the distortion is explained and the way to avoid it is indicated. A novel method for processing the eddy current responses is presented in the second part of the paper. The method employs two-dimensional conjugate spectrum filters (CSFs) that are sensitive both to the phase angle and the shape of the eddy current responses. First the theoretical background of the CSF is presented and then two different ways of application, matched filters and orthogonal conjugate spectrum filters, are considered. The matched CSFs can be used for attenuation of all signals with the phase angle different from the selected prototype. The orthogonal filters are able to suppress completely a specific interference, e.g. the response of supporting plate when testing heat exchanger tubes. The performance of the CSFs is illustrated by means of real and simulated eddy current signals.

  2. UCMS - A new signal parameter measurement system using digital signal processing techniques. [User Constraint Measurement System

    NASA Technical Reports Server (NTRS)

    Choi, H. J.; Su, Y. T.

    1986-01-01

    The User Constraint Measurement System (UCMS) is a hardware/software package developed by NASA Goddard to measure the signal parameter constraints of the user transponder in the TDRSS environment by means of an all-digital signal sampling technique. An account is presently given of the features of UCMS design and of its performance capabilities and applications; attention is given to such important aspects of the system as RF interface parameter definitions, hardware minimization, the emphasis on offline software signal processing, and end-to-end link performance. Applications to the measurement of other signal parameters are also discussed.

  3. Optical correlation of images with signal-dependent noise using constrained-modulation filter devices

    NASA Astrophysics Data System (ADS)

    Downie, John D.

    1995-07-01

    Images with signal-dependent noise present challenges beyond those of images with additive white or colored signal-independent noise in terms of designing the optimal 4-f correlation filter that maximizes correlation-peak signal-to-noise ratio, or combinations of correlation-peak metrics. Determining the proper design becomes more difficult when the filter is to be implemented on a constrained-modulation spatial light modulator device. The design issues involved for updatable optical filters for images with signal-dependent film-grain noise and speckle noise are examined. It is shown that although design of the optimal linear filter in the Fourier domain is impossible for images with signal-dependent noise, proper nonlinear preprocessing of the images allows the application of previously developed design rules for optimal filters to be implemented on constrained-modulation devices. Thus the nonlinear preprocessing becomes necessary for correlation in optical systems with current spatial light modulator technology. These results are illustrated with computer simulations of images with signal-dependent noise correlated with binary-phase-only filters and ternary-phase-amplitude filters.

  4. Investigation of correlation characteristics for random array collaborative beamforming using noise signals

    NASA Astrophysics Data System (ADS)

    Alexander, David B.; Narayanan, Ram M.; Himed, Braham

    2016-05-01

    The performance of different random array geometries is analyzed and compared. Three phased array geometries are considered: linear arrays with non-uniform randomized spacing between elements, circular arrays with non-uniform element radii, and ad hoc sensor networks with elements located randomly within a circular area. For each of these array geometries, computer simulations modeled the transmission, reflection from an arbitrary target, and reception of signals. The effectiveness of each array's beamforming techniques was measured by taking the peak cross-correlation between the received signal and a time-delayed replica of the original transmitted signal. For each array type, the correlation performance was obtained for transmission and reception of both chirp waveforms and ultra-wideband noise signals. It was found that the non-uniform linear array generally produced the highest correlation between transmitted and reflected signals. The non-uniform circular and ad hoc arrays demonstrated the most consistent performance with respect to noise signal bandwidth. The effect of scan angle was found to have a significant impact on the correlation performance of the linear arrays, where the correlation performance declines as the scan angle moves away from broadside to the array.

  5. Optical Correlation of Images With Signal-Dependent Noise Using Constrained-Modulation Filter Devices

    NASA Technical Reports Server (NTRS)

    Downie, John D.

    1995-01-01

    Images with signal-dependent noise present challenges beyond those of images with additive white or colored signal-independent noise in terms of designing the optimal 4-f correlation filter that maximizes correlation-peak signal-to-noise ratio, or combinations of correlation-peak metrics. Determining the proper design becomes more difficult when the filter is to be implemented on a constrained-modulation spatial light modulator device. The design issues involved for updatable optical filters for images with signal-dependent film-grain noise and speckle noise are examined. It is shown that although design of the optimal linear filter in the Fourier domain is impossible for images with signal-dependent noise, proper nonlinear preprocessing of the images allows the application of previously developed design rules for optimal filters to be implemented on constrained-modulation devices. Thus the nonlinear preprocessing becomes necessary for correlation in optical systems with current spatial light modulator technology. These results are illustrated with computer simulations of images with signal-dependent noise correlated with binary-phase-only filters and ternary-phase-amplitude filters.

  6. A comparison of signal processing techniques for Intrinsic Optical Signal imaging in mice.

    PubMed

    Turley, Jordan A; Nilsson, Michael; Walker, Frederick Rohan; Johnson, Sarah J

    2015-01-01

    Intrinsic Optical Signal imaging is a technique which allows the visualisation and mapping of activity related changes within the brain with excellent spatial and temporal resolution. We analysed a variety of signal and image processing techniques applied to real mouse imaging data. The results were compared in an attempt to overcome the unique issues faced when performing the technique on mice and improve the understanding of post processing options available.

  7. Correlation Spectroscopy of Minor Fluorescent Species: Signal Purification and Distribution Analysis

    PubMed Central

    Laurence, Ted A.; Kwon, Youngeun; Yin, Eric; Hollars, Christopher W.; Camarero, Julio A.; Barsky, Daniel

    2007-01-01

    We are performing experiments that use fluorescence resonance energy transfer (FRET) and fluorescence correlation spectroscopy (FCS) to monitor the movement of an individual donor-labeled sliding clamp protein molecule along acceptor-labeled DNA. In addition to the FRET signal sought from the sliding clamp-DNA complexes, the detection channel for FRET contains undesirable signal from free sliding clamp and free DNA. When multiple fluorescent species contribute to a correlation signal, it is difficult or impossible to distinguish between contributions from individual species. As a remedy, we introduce “purified FCS”, which uses single molecule burst analysis to select a species of interest and extract the correlation signal for further analysis. We show that by expanding the correlation region around a burst, the correlated signal is retained and the functional forms of FCS fitting equations remain valid. We demonstrate the use of purified FCS in experiments with DNA sliding clamps. We also introduce “single-molecule FCS”, which obtains diffusion time estimates for each burst using expanded correlation regions. By monitoring the detachment of weakly-bound 30-mer DNA oligomers from a single-stranded DNA plasmid, we show that single-molecule FCS can distinguish between bursts from species that differ by a factor of 5 in diffusion constant. PMID:17189306

  8. Removing Background Noise with Phased Array Signal Processing

    NASA Technical Reports Server (NTRS)

    Podboy, Gary; Stephens, David

    2015-01-01

    Preliminary results are presented from a test conducted to determine how well microphone phased array processing software could pull an acoustic signal out of background noise. The array consisted of 24 microphones in an aerodynamic fairing designed to be mounted in-flow. The processing was conducted using Functional Beam forming software developed by Optinav combined with cross spectral matrix subtraction. The test was conducted in the free-jet of the Nozzle Acoustic Test Rig at NASA GRC. The background noise was produced by the interaction of the free-jet flow with the solid surfaces in the flow. The acoustic signals were produced by acoustic drivers. The results show that the phased array processing was able to pull the acoustic signal out of the background noise provided the signal was no more than 20 dB below the background noise level measured using a conventional single microphone equipped with an aerodynamic forebody.

  9. Common formalism for adaptive identification in signal processing and control

    NASA Astrophysics Data System (ADS)

    Macchi, O.

    1991-08-01

    The transversal and recursive approaches to adaptive identification are compared. ARMA modeling in signal processing, and identification in the indirect approach to control are developed in parallel. Adaptivity succeeds because the estimate is a linear function of the variable parameters for transversal identification. Control and signal processing can be imbedded in a unified well-established formalism that guarantees convergence of the adaptive parameters. For recursive identification, the estimate is a nonlinear function of the parameters, possibly resulting in nonuniqueness of the solution, in wandering and even instability of adaptive algorithms. The requirement for recursivity originates in the structure of the signal (MA-part) in signal processing. It is caused by the output measurement noise in control.

  10. 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.

  11. Random Walks and Branching Processes in Correlated Gaussian Environment

    NASA Astrophysics Data System (ADS)

    Aurzada, Frank; Devulder, Alexis; Guillotin-Plantard, Nadine; Pène, Françoise

    2017-01-01

    We study persistence probabilities for random walks in correlated Gaussian random environment investigated by Oshanin et al. (Phys Rev Lett, 110:100602, 2013). From the persistence results, we can deduce properties of critical branching processes with offspring sizes geometrically distributed with correlated random parameters. More precisely, we obtain estimates on the tail distribution of its total population size, of its maximum population, and of its extinction time.

  12. Interhemispheric support during demanding auditory signal-in-noise processing.

    PubMed

    Stracke, Henning; Okamoto, Hidehiko; Pantev, Christo

    2009-06-01

    We investigated attentional effects on human auditory signal-in-noise processing in a simultaneous masking paradigm using magnetoencephalography. Test signal was a monaural 1000-Hz tone; maskers were binaural band-eliminated noises (BENs) containing stopbands of different widths centered on 1000 Hz. Participants directed attention either to the left or the right ear. In an "irrelevant visual attention" condition subjects focused attention on a screen. Irrespective of attention focus location, the signal appeared randomly either in the left or right ear. During auditory focused attention (left- or right-ear attention), the signal thus randomly appeared either in the attended ("relevant auditory attention" condition) or the nonattended ear ("irrelevant auditory attention" condition). Results showed that N1m source strength was overall increased in the left relative to the right hemisphere, and for right-ear versus left-ear stimulation. Moreover, when attention was focused on the signal ear (relevant auditory attention condition) and the BEN stopbands were narrow, the right-hemispheric N1m source strength was increased, relative to irrelevant auditory attention. Such increments were neither observed in the left hemisphere nor for wide BENs. These novel results indicate 1) left-hemispheric dominance and robustness during auditory signal-in-noise processing, and 2) right-hemispheric assistance during attentive and demanding auditory signal-in-noise processing.

  13. Assess sleep stage by modern signal processing techniques.

    PubMed

    Wu, Hau-tieng; Talmon, Ronen; Lo, Yu-Lun

    2015-04-01

    In this paper, two modern adaptive signal processing techniques, empirical intrinsic geometry and synchrosqueezing transform, are applied to quantify different dynamical features of the respiratory and electroencephalographic signals. We show that the proposed features are theoretically rigorously supported, as well as capture the sleep information hidden inside the signals. The features are used as input to multiclass support vector machines with the radial basis function to automatically classify sleep stages. The effectiveness of the classification based on the proposed features is shown to be comparable to human expert classification-the proposed classification of awake, REM, N1, N2, and N3 sleeping stages based on the respiratory signal (resp. respiratory and EEG signals) has the overall accuracy 81.7% (resp. 89.3%) in the relatively normal subject group. In addition, by examining the combination of the respiratory signal with the electroencephalographic signal, we conclude that the respiratory signal consists of ample sleep information, which supplements to the information stored in the electroencephalographic signal.

  14. Correlation Processing Of Local Seismic Data: Applications for Autonomous Sensor Deployments

    SciTech Connect

    Dodge, D A

    2010-11-16

    Excavation and operation of an underground facility is likely to produce an extensive suite of seismic signals observable at the surface for perhaps several km. Probably a large fraction of such signals will be correlated, so the design of a monitoring framework should include consideration of a correlation processing capability. Correlation detectors have been shown to be significantly more sensitive than beam-forming power detectors. Although correlation detectors have a limited detection footprint, they can be generalized into multi-rank subspace detectors which are sensitive over a much larger range of source mechanisms and positions. Production of subspace detectors can be automated, so their use in an autonomous framework may be contemplated. Waveform correlation also can be used to produce very high precision phase picks which may be jointly inverted to simultaneously relocate groups of events. The relative precision of the resulting hypocenters is sufficient to visualize structural detail at a scale of less than a few tens of meters. Three possible correlation processor systems are presented. All use a subspace signal detection framework. The simplest system uses a single-component sensor and is capable of detection and classification of signals. The most complicated system uses many sensors deployed around the facility, and is capable of detection, classification, and high-precision source location. Data from a deep underground mine are presented to demonstrate the applicability of correlation processing to monitoring an underground facility. Although the source region covers an area of about 600m by 580m, all but two of the events form clusters at a threshold of 0.7. All the events could have been detected and classified by the subspace detection framework, and high-precision picks can be computed for all cluster members.

  15. Trouble at rest: how correlation patterns and group differences become distorted after global signal regression.

    PubMed

    Saad, Ziad S; Gotts, Stephen J; Murphy, Kevin; Chen, Gang; Jo, Hang Joon; Martin, Alex; Cox, Robert W

    2012-01-01

    Resting-state functional magnetic resonance imaging (RS-FMRI) holds the promise of revealing brain functional connectivity without requiring specific tasks targeting particular brain systems. RS-FMRI is being used to find differences between populations even when a specific candidate target for traditional inferences is lacking. However, the problem with RS-FMRI is a lacking definition of what constitutes noise and signal. RS-FMRI is easy to acquire but is not easy to analyze or draw inferences from. In this commentary we discuss a problem that is still treated lightly despite its significant impact on RS-FMRI inferences; global signal regression (GSReg), the practice of projecting out signal averaged over the entire brain, can change resting-state correlations in ways that dramatically alter correlation patterns and hence conclusions about brain functional connectedness. Although Murphy et al. in 2009 demonstrated that GSReg negatively biases correlations, the approach remains in wide use. We revisit this issue to argue the problem that GSReg is more than negative bias or the interpretability of negative correlations. Its usage can fundamentally alter interregional correlations within a group, or their differences between groups. We used an illustrative model to clearly convey our objections and derived equations formalizing our conclusions. We hope this creates a clear context in which counterarguments can be made. We conclude that GSReg should not be used when studying RS-FMRI because GSReg biases correlations differently in different regions depending on the underlying true interregional correlation structure. GSReg can alter local and long-range correlations, potentially spreading underlying group differences to regions that may never have had any. Conclusions also apply to substitutions of GSReg for denoising with decompositions of signals aggregated over the network's regions to the extent they cannot separate signals of interest from noise. We touch on the

  16. Sub-threshold signal processing in arrays of non-identical nanostructures.

    PubMed

    Cervera, Javier; Manzanares, José A; Mafé, Salvador

    2011-10-28

    Weak input signals are routinely processed by molecular-scaled biological networks composed of non-identical units that operate correctly in a noisy environment. In order to show that artificial nanostructures can mimic this behavior, we explore theoretically noise-assisted signal processing in arrays of metallic nanoparticles functionalized with organic ligands that act as tunneling junctions connecting the nanoparticle to the external electrodes. The electronic transfer through the nanostructure is based on the Coulomb blockade and tunneling effects. Because of the fabrication uncertainties, these nanostructures are expected to show a high variability in their physical characteristics and a diversity-induced static noise should be considered together with the dynamic noise caused by thermal fluctuations. This static noise originates from the hardware variability and produces fluctuations in the threshold potential of the individual nanoparticles arranged in a parallel array. The correlation between different input (potential) and output (current) signals in the array is analyzed as a function of temperature, applied voltage, and the variability in the electrical properties of the nanostructures. Extensive kinetic Monte Carlo simulations with nanostructures whose basic properties have been demonstrated experimentally show that variability can enhance the correlation, even for the case of weak signals and high variability, provided that the signal is processed by a sufficiently high number of nanostructures. Moderate redundancy permits us not only to minimize the adverse effects of the hardware variability but also to take advantage of the nanoparticles' threshold fluctuations to increase the detection range at low temperatures. This conclusion holds for the average behavior of a moderately large statistical ensemble of non-identical nanostructures processing different types of input signals and suggests that variability could be beneficial for signal processing

  17. An epidemic process mediated by a decaying diffusing signal

    NASA Astrophysics Data System (ADS)

    Faria, Fernando P.; Dickman, Ronald

    2012-06-01

    We study a stochastic epidemic model consisting of elements (organisms in a community or cells in tissue) with fixed positions, in which damage or disease is transmitted by diffusing agents ('signals') emitted by infected individuals. The signals decay as well as diffuse; since they are assumed to be produced in large numbers, the signal concentration is treated deterministically. The model, which includes four cellular states (susceptible, transformed, depleted, and removed), admits various interpretations: spread of an infection or infectious disease, or of damage in a tissue in which injured cells may themselves provoke further damage, and as a description of the so-called radiation-induced bystander effect, in which the signals are molecules capable of inducing cell damage and/or death in unirradiated cells. The model exhibits a continuous phase transition between spreading and nonspreading phases. We formulate two mean-field theory (MFT) descriptions of the model, one of which ignores correlations between the cellular state and the signal concentration, and another that treats such correlations in an approximate manner. Monte Carlo simulations of the spread of infection on the square lattice yield values for the critical exponents and the fractal dimension consistent with the dynamic percolation universality class.

  18. Signal processing applied to photothermal techniques for materials characterization

    NASA Technical Reports Server (NTRS)

    Rooney, James A.

    1989-01-01

    There is a need to make noncontact measurements of material characteristics in the microgravity environment. Photothermal and photoacoustics techniques offer one approach for attaining this capability since lasers can be used to generate the required thermal or acoustic signals. The perturbations in the materials that can be used for characterization can be detected by optical reflectance, infrared detection or laser detection of photoacoustics. However, some of these laser techniques have disadvantages of either high energy pulsed excitation or low signal-to-noise ratio. Alternative signal processing techniques that have been developed can be applied to photothermal or photoacoustic instrumentation. One fully coherent spread spectrum signal processing technique is called time delay spectrometry (TDS). With TDS the system is excited using a combined frequency-time domain by employing a linear frequency sweep excitation function. The processed received signal can provide either frequency, phase or improved time resolution. This signal processing technique was shown to outperform other time selective techniques with respect to noise rejection and was recently applied to photothermal instrumentation. The technique yields the mathematical equivalent of pulses yet the input irradiances are orders of magnitude less than pulses with the concomitant reduction in perturbation of the sample and can increase the capability of photothermal methods for materials characterization.

  19. Relationships between digital signal processing and control and estimation theory

    NASA Technical Reports Server (NTRS)

    Willsky, A. S.

    1978-01-01

    Research directions in the fields of digital signal processing and modern control and estimation theory are discussed. Stability theory, linear prediction and parameter identification, system synthesis and implementation, two-dimensional filtering, decentralized control and estimation, and image processing are considered in order to uncover some of the basic similarities and differences in the goals, techniques, and philosophy of the disciplines.

  20. Optimal and adaptive methods of processing hydroacoustic signals (review)

    NASA Astrophysics Data System (ADS)

    Malyshkin, G. S.; Sidel'nikov, G. B.

    2014-09-01

    Different methods of optimal and adaptive processing of hydroacoustic signals for multipath propagation and scattering are considered. Advantages and drawbacks of the classical adaptive (Capon, MUSIC, and Johnson) algorithms and "fast" projection algorithms are analyzed for the case of multipath propagation and scattering of strong signals. The classical optimal approaches to detecting multipath signals are presented. A mechanism of controlled normalization of strong signals is proposed to automatically detect weak signals. The results of simulating the operation of different detection algorithms for a linear equidistant array under multipath propagation and scattering are presented. An automatic detector is analyzed, which is based on classical or fast projection algorithms, which estimates the background proceeding from median filtering or the method of bilateral spatial contrast.

  1. Correlation-based pointwise processing of dynamic speckle patterns.

    PubMed

    Stoykova, Elena; Ivanov, Branimir; Nikova, Tania

    2014-01-01

    Correlation-based pointwise processing of dynamic speckle patterns is proposed for spatial characterization of activity in a sample. The result is a set of 2D activity maps of the estimates of temporal correlation, or structure functions, at increasing time lags. Pointwise computation provides spatial resolution, limited by the pixel period of the optical sensor used for acquisition of the speckle patterns. Pointwise normalization of the estimates solves the problem with the nonuniform illumination and varying reflectivity across the sample. The high contrast detailed activity maps obtained from processing of synthetic and experimental speckle patterns confirms efficiency of the proposed approach.

  2. Genomic Signal Processing: Predicting Basic Molecular Biological Principles

    NASA Astrophysics Data System (ADS)

    Alter, Orly

    2005-03-01

    Advances in high-throughput technologies enable acquisition of different types of molecular biological data, monitoring the flow of biological information as DNA is transcribed to RNA, and RNA is translated to proteins, on a genomic scale. Future discovery in biology and medicine will come from the mathematical modeling of these data, which hold the key to fundamental understanding of life on the molecular level, as well as answers to questions regarding diagnosis, treatment and drug development. Recently we described data-driven models for genome-scale molecular biological data, which use singular value decomposition (SVD) and the comparative generalized SVD (GSVD). Now we describe an integrative data-driven model, which uses pseudoinverse projection (1). We also demonstrate the predictive power of these matrix algebra models (2). The integrative pseudoinverse projection model formulates any number of genome-scale molecular biological data sets in terms of one chosen set of data samples, or of profiles extracted mathematically from data samples, designated the ``basis'' set. The mathematical variables of this integrative model, the pseudoinverse correlation patterns that are uncovered in the data, represent independent processes and corresponding cellular states (such as observed genome-wide effects of known regulators or transcription factors, the biological components of the cellular machinery that generate the genomic signals, and measured samples in which these regulators or transcription factors are over- or underactive). Reconstruction of the data in the basis simulates experimental observation of only the cellular states manifest in the data that correspond to those of the basis. Classification of the data samples according to their reconstruction in the basis, rather than their overall measured profiles, maps the cellular states of the data onto those of the basis, and gives a global picture of the correlations and possibly also causal coordination of

  3. GNSS-based bistatic SAR: a signal processing view

    NASA Astrophysics Data System (ADS)

    Antoniou, Michail; Cherniakov, Mikhail

    2013-12-01

    This article presents signal processing algorithms used as a new remote sensing tool, that is passive bistatic SAR with navigation satellites (e.g. GPS, GLONASS or Galileo) as transmitters of opportunity. Signal synchronisation and image formation algorithms are described for two system variants: one where the receiver is moving and one where it is fixed on the ground. The applicability and functionality of the algorithms described is demonstrated through experimental imagery that ultimately confirms the feasibility of the overall technology.

  4. Higher-Dimensional Signal Processing via Multiscale Geometric Analysis

    DTIC Science & Technology

    2010-02-10

    compression, classification, and segmentation. Despite the remarkable advantages of wavelets for analyzing and processing l-D signals, a surprising...perpendicular to β. Our goal in this section is to analyze the phase (θ1, θ2, θ3) of the quaternion wavelet coefficient (e.g., dV`,p for the vertical... wavelet transforms suitable for signals containing low-dimensional manifold structures [22]. The QWT developed here could play an interesting rôle in

  5. Digital signal processing for fiber-optic thermometers

    SciTech Connect

    Fernicola, V.; Crovini, L.

    1994-12-31

    A digital signal processing scheme for measurement of exponentially-decaying signals, such as those found in fluorescence, lifetime-based, fiber-optic sensors, is proposed. The instrument uses a modified digital phase-sensitive-detection technique with the phase locked to a fixed value and the modulation period tracking the measured lifetime. Typical resolution of the system is 0.05% for slow decay (>500 {mu}s) and 0.1% for fast decay.

  6. Calibration of ultra high speed laser engraving processes by correlating influencing variables including correlative evaluation with SEM and CLSM

    NASA Astrophysics Data System (ADS)

    Bohrer, Markus; Vaupel, Matthias; Nirnberger, Robert; Weinberger, Bernhard

    2016-03-01

    Laser engraving is used for decades as a well-established process e. g. for the production of print and embossing forms for many goods in daily life, e. g. decorated cans and printed bank notes. Up to now it is more or less a so-called fire-and-forget process. From the original artist's plan to the digitization, then from the laser source itself (with electronic signals, RF and plasma discharge regarding CO2 lasers) to the behavior of the optical beam delivery — especially if an AOM is used — to the interaction of the laser beam with the material itself is a long process chain. The most recent results using CO2 lasers with AOMs and the research done with scanning electron microscope (SEM) and confocal laser scanning microscope (CLSM) — as a set for correlative microscopy to evaluate the high speed engraving characteristics — are presented in this paper.

  7. Research on mud pulse signal data processing in MWD

    NASA Astrophysics Data System (ADS)

    Tu, Bing; Li, De Sheng; Lin, En Huai; Ji, Miao Miao

    2012-12-01

    Wireless measure while drilling (MWD) transmits data by using mud pulse signal ; the ground decoding system collects the mud pulse signal and then decodes and displays the parameters under the down-hole according to the designed encoding rules and the correct detection and recognition of the ground decoding system towards the received mud pulse signal is one kind of the key technology of MWD. This paper introduces digit of Manchester encoding that transmits data and the format of the wireless transmission of data under the down-hole and develops a set of ground decoding systems. The ground decoding algorithm uses FIR (Finite impulse response) digital filtering to make de-noising on the mud pulse signal, then adopts the related base value modulating algorithm to eliminate the pump pulse base value of the denoised mud pulse signal, finally analyzes the mud pulse signal waveform shape of the selected Manchester encoding in three bits cycles, and applies the pattern similarity recognition algorithm to the mud pulse signal recognition. The field experiment results show that the developed device can make correctly extraction and recognition for the mud pulse signal with simple and practical decoding process and meet the requirements of engineering application.

  8. All-optical signal processing technique for secure optical communication

    NASA Astrophysics Data System (ADS)

    Qian, Feng-chen; Su, Bing; Ye, Ya-lin; Zhang, Qian; Lin, Shao-feng; Duan, Tao; Duan, Jie

    2015-10-01

    Secure optical communication technologies are important means to solve the physical layer security for optical network. We present a scheme of secure optical communication system by all-optical signal processing technique. The scheme consists of three parts, as all-optical signal processing unit, optical key sequence generator, and synchronous control unit. In the paper, all-optical signal processing method is key technology using all-optical exclusive disjunction (XOR) gate based on optical cross-gain modulation effect, has advantages of wide dynamic range of input optical signal, simple structure and so on. All-optical XOR gate composed of two semiconductor optical amplifiers (SOA) is a symmetrical structure. By controlling injection current, input signal power, delay and filter bandwidth, the extinction ratio of XOR can be greater than 8dB. Finally, some performance parameters are calculated and the results are analyzed. The simulation and experimental results show that the proposed method can be achieved over 10Gbps optical signal encryption and decryption, which is simple, easy to implement, and error-free diffusion.

  9. Bicoid Signal Extraction with a Selection of Parametric and Nonparametric Signal Processing Techniques

    PubMed Central

    Ghodsi, Zara; Silva, Emmanuel Sirimal; Hassani, Hossein

    2015-01-01

    The maternal segmentation coordinate gene bicoid plays a significant role during Drosophila embryogenesis. The gradient of Bicoid, the protein encoded by this gene, determines most aspects of head and thorax development. This paper seeks to explore the applicability of a variety of signal processing techniques at extracting bicoid expression signal, and whether these methods can outperform the current model. We evaluate the use of six different powerful and widely-used models representing both parametric and nonparametric signal processing techniques to determine the most efficient method for signal extraction in bicoid. The results are evaluated using both real and simulated data. Our findings show that the Singular Spectrum Analysis technique proposed in this paper outperforms the synthesis diffusion degradation model for filtering the noisy protein profile of bicoid whilst the exponential smoothing technique was found to be the next best alternative followed by the autoregressive integrated moving average. PMID:26197438

  10. Bicoid signal extraction with a selection of parametric and nonparametric signal processing techniques.

    PubMed

    Ghodsi, Zara; Silva, Emmanuel Sirimal; Hassani, Hossein

    2015-06-01

    The maternal segmentation coordinate gene bicoid plays a significant role during Drosophila embryogenesis. The gradient of Bicoid, the protein encoded by this gene, determines most aspects of head and thorax development. This paper seeks to explore the applicability of a variety of signal processing techniques at extracting bicoid expression signal, and whether these methods can outperform the current model. We evaluate the use of six different powerful and widely-used models representing both parametric and nonparametric signal processing techniques to determine the most efficient method for signal extraction in bicoid. The results are evaluated using both real and simulated data. Our findings show that the Singular Spectrum Analysis technique proposed in this paper outperforms the synthesis diffusion degradation model for filtering the noisy protein profile of bicoid whilst the exponential smoothing technique was found to be the next best alternative followed by the autoregressive integrated moving average.

  11. Parallel-Processing Software for Correlating Stereo Images

    NASA Technical Reports Server (NTRS)

    Klimeck, Gerhard; Deen, Robert; Mcauley, Michael; DeJong, Eric

    2007-01-01

    A computer program implements parallel- processing algorithms for cor relating images of terrain acquired by stereoscopic pairs of digital stereo cameras on an exploratory robotic vehicle (e.g., a Mars rove r). Such correlations are used to create three-dimensional computatio nal models of the terrain for navigation. In this program, the scene viewed by the cameras is segmented into subimages. Each subimage is assigned to one of a number of central processing units (CPUs) opera ting simultaneously.

  12. Long-range vibration sensor based on correlation analysis of optical frequency-domain reflectometry signals.

    PubMed

    Ding, Zhenyang; Yao, X Steve; Liu, Tiegen; Du, Yang; Liu, Kun; Han, Qun; Meng, Zhuo; Chen, Hongxin

    2012-12-17

    We present a novel method to achieve a space-resolved long- range vibration detection system based on the correlation analysis of the optical frequency-domain reflectometry (OFDR) signals. By performing two separate measurements of the vibrated and non-vibrated states on a test fiber, the vibration frequency and position of a vibration event can be obtained by analyzing the cross-correlation between beat signals of the vibrated and non-vibrated states in a spatial domain, where the beat signals are generated from interferences between local Rayleigh backscattering signals of the test fiber and local light oscillator. Using the proposed technique, we constructed a standard single-mode fiber based vibration sensor that can have a dynamic range of 12 km and a measurable vibration frequency up to 2 kHz with a spatial resolution of 5 m. Moreover, preliminarily investigation results of two vibration events located at different positions along the test fiber are also reported.

  13. Multichannel optical signal processing using sampled fiber Bragg gratings

    NASA Astrophysics Data System (ADS)

    Zhang, Guiju; Wang, Chinhua; Zhu, Xiaojun

    2008-12-01

    Sampled and linearly chirped fiber Bragg gratings provide multiple wavelength responses and linear group delays (constant dispersions) within each of the wavelength channels. We show that the sampled and chirped fiber Bragg gratings can be used to perform multiwavelength signal processing. In particular, we demonstrate, by numerical simulation, their use for performing real-time Fourier transform (RTFT) and for pulse repetition rate multiplication (PRRM) simultaneously over multiple wavelength channels. To present how the sampled fiber Bragg gratings perform the multichannel optical signal processing, a 9-channel sampled fiber grating with 100GHz channel spacing was designed and the effect of ripples in both amplitude and the group delay channel on the performance of the signal processing was examined and discussed.

  14. Parallel Signal Processing and System Simulation using aCe

    NASA Technical Reports Server (NTRS)

    Dorband, John E.; Aburdene, Maurice F.

    2003-01-01

    Recently, networked and cluster computation have become very popular for both signal processing and system simulation. A new language is ideally suited for parallel signal processing applications and system simulation since it allows the programmer to explicitly express the computations that can be performed concurrently. In addition, the new C based parallel language (ace C) for architecture-adaptive programming allows programmers to implement algorithms and system simulation applications on parallel architectures by providing them with the assurance that future parallel architectures will be able to run their applications with a minimum of modification. In this paper, we will focus on some fundamental features of ace C and present a signal processing application (FFT).

  15. Detectors and signal processing for high-energy physics

    SciTech Connect

    Rehak, P.

    1981-01-01

    Basic principles of the particle detection and signal processing for high-energy physics experiments are presented. It is shown that the optimum performance of a properly designed detector system is not limited by incidental imperfections, but solely by more fundamental limitations imposed by the quantum nature and statistical behavior of matter. The noise sources connected with the detection and signal processing are studied. The concepts of optimal filtering and optimal detector/amplifying device matching are introduced. Signal processing for a liquid argon calorimeter is analyzed in some detail. The position detection in gas counters is studied. Resolution in drift chambers for the drift coordinate measurement as well as the second coordinate measurement is discussed.

  16. Why optics students should take digital signal processing courses and why digital signal processing students should take optics courses

    NASA Astrophysics Data System (ADS)

    Cathey, W. Thomas, Jr.

    2000-06-01

    This paper is based on the claim that future major contributions in the field of imaging systems will be made by those who have a background in both optics and digital signal processing. As the introduction of Fourier transforms and linear systems theory to optics had a major impact on the design of hybrid optical/digital imaging systems, the introduction of digital signal processing into optics programs will have a major impact. Examples are given of new hybrid imaging systems that have unique performance. By jointly designing the optics and the signal processing in a digital camera, a new paradigm arises where aberration balancing takes into consideration not only the number of surfaces and indices of refraction, but also the processing capability.

  17. Distributed Signal Processing for Wireless EEG Sensor Networks.

    PubMed

    Bertrand, Alexander

    2015-11-01

    Inspired by ongoing evolutions in the field of wireless body area networks (WBANs), this tutorial paper presents a conceptual and exploratory study of wireless electroencephalography (EEG) sensor networks (WESNs), with an emphasis on distributed signal processing aspects. A WESN is conceived as a modular neuromonitoring platform for high-density EEG recordings, in which each node is equipped with an electrode array, a signal processing unit, and facilities for wireless communication. We first address the advantages of such a modular approach, and we explain how distributed signal processing algorithms make WESNs more power-efficient, in particular by avoiding data centralization. We provide an overview of distributed signal processing algorithms that are potentially applicable in WESNs, and for illustration purposes, we also provide a more detailed case study of a distributed eye blink artifact removal algorithm. Finally, we study the power efficiency of these distributed algorithms in comparison to their centralized counterparts in which all the raw sensor signals are centralized in a near-end or far-end fusion center.

  18. Neural Correlates of Bridging Inferences and Coherence Processing

    ERIC Educational Resources Information Center

    Kim, Sung-il; Yoon, Misun; Kim, Wonsik; Lee, Sunyoung; Kang, Eunjoo

    2012-01-01

    We explored the neural correlates of bridging inferences and coherence processing during story comprehension using Positron Emission Tomography (PET). Ten healthy right-handed volunteers were visually presented three types of stories (Strong Coherence, Weak Coherence, and Control) consisted of three sentences. The causal connectedness among…

  19. Neural Correlates of Sublexical Processing in Phonological Working Memory

    ERIC Educational Resources Information Center

    McGettigan, Carolyn; Warren, Jane E.; Eisner, Frank; Marshall, Chloe R.; Shanmugalingam, Pradheep; Scott, Sophie K.

    2011-01-01

    This study investigated links between working memory and speech processing systems. We used delayed pseudoword repetition in fMRI to investigate the neural correlates of sublexical structure in phonological working memory (pWM). We orthogonally varied the number of syllables and consonant clusters in auditory pseudowords and measured the neural…

  20. Analysis of Low Probability of Intercept (LPI) Radar Signals Using Cyclostationary Processing

    NASA Astrophysics Data System (ADS)

    Lime, Antonio F., Jr.

    2002-09-01

    LPI (Low Probability of Intercept) radar is a class of radar systems that possess certain performance characteristics that make them nearly undetectable by today's digital intercept receivers. This presents a significant tactical problem in the battle space. To detect these types of radar, new digital receivers that use sophisticated signal processing techniques are required This thesis investigates the use of cyclostationary processing to extract the modulation parameters from a variety of continuous-wave (CW) low-probability-of-intercept (LPI) radar waveforms. The cyclostationary detection techniques described exploit the fact that digital signals vary in time with single or multiple periodicities, because they have spectral correlation, namely, non-zero correlation between certain frequency components, at certain frequency shifts. The use of cyclostationary signal processing in a non-cooperative intercept receiver can help identify the particular emitter and can help develop electronic attacks. LPI CW waveforms examined include Frank codes, polyphase codes (Pt through P4), Frequency Modulated CW (FMCW), Costas frequencies as well as several frequency-shift-keying/phase-shift-keying (FSK/PSK) waveforms. It is shown that for signal-to-noise ratios of OdB and -6 dB, the cyclostationary signal processing can extract the modulation parameters necessary in order to distinguish among the various types of LPI modulations.

  1. ISLE (Image and Signal Processing LISP Environment) reference manual

    SciTech Connect

    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 the 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.

  2. The evolution of signal-reward correlations in bee- and hummingbird-pollinated species of Salvia.

    PubMed

    Benitez-Vieyra, Santiago; Fornoni, Juan; Pérez-Alquicira, Jessica; Boege, Karina; Domínguez, César A

    2014-05-07

    Within-individual variation in floral advertising and reward traits is a feature experienced by pollinators that visit different flowers of the same plant. Pollinators can use advertising traits to gather information about the quality and amount of rewards, leading to the evolution of signal-reward correlations. As long as plants differ in the reliability of their signals and pollinators base their foraging decisions on this information, natural selection should act on within-individual correlations between signals and rewards. Because birds and bees differ in their cognitive capabilities, and use different floral traits as signals, we tested the occurrence of adaptive divergence of the within-individual signal-reward correlations among Salvia species that are pollinated either by bees or by hummingbirds. They are expected to use different floral advertising traits: frontal traits in the case of bees and side traits in the case of hummingbirds. We confirmed this expectation as bee- and hummingbird-pollinated species differed in which specific traits are predominantly associated with nectar reward at the within-individual level. Our findings highlight the adaptive value of within-individual variation and covariation patterns, commonly disregarded as 'environmental noise', and are consistent with the hypothesis that pollinator-mediated selection affects the correlation pattern among floral traits.

  3. Signal Processing For Chemical Sensing: Statistics or Biological Inspiration

    NASA Astrophysics Data System (ADS)

    Marco, Santiago

    2011-09-01

    Current analytical instrumentation and continuous sensing can provide huge amounts of data. Automatic signal processing and information evaluation is needed to overcome drowning in data. Today, statistical techniques are typically used to analyse and extract information from continuous signals. However, it is very interesting to note that biology (insects and vertebrates) has found alternative solutions for chemical sensing and information processing. This is a brief introduction to the developments in the European Project: Bio-ICT NEUROCHEM: Biologically Inspired Computation for Chemical Sensing (grant no. 216916) Fp7 project devoted to biomimetic olfactory systems.

  4. Using image processing techniques on proximity probe signals in rotordynamics

    NASA Astrophysics Data System (ADS)

    Diamond, Dawie; Heyns, Stephan; Oberholster, Abrie

    2016-06-01

    This paper proposes a new approach to process proximity probe signals in rotordynamic applications. It is argued that the signal be interpreted as a one dimensional image. Existing image processing techniques can then be used to gain information about the object being measured. Some results from one application is presented. Rotor blade tip deflections can be calculated through localizing phase information in this one dimensional image. It is experimentally shown that the newly proposed method performs more accurately than standard techniques, especially where the sampling rate of the data acquisition system is inadequate by conventional standards.

  5. Non-linear canonical correlation for joint analysis of MEG signals from two subjects.

    PubMed

    Campi, Cristina; Parkkonen, Lauri; Hari, Riitta; Hyvärinen, Aapo

    2013-01-01

    Traditional stimulus-based analysis methods of magnetoencephalography (MEG) data are often dissatisfactory when applied to naturalistic experiments where two or more subjects are measured either simultaneously or sequentially. To uncover the commonalities in the brain activity of the two subjects, we propose a method that searches for linear transformations that output maximally correlated signals between the two brains. Our method is based on canonical correlation analysis (CCA), which provides linear transformations, one for each subject, such that the temporal correlation between the transformed MEG signals is maximized. Here, we present a non-linear version of CCA which measures the correlation of energies and allows for a variable delay between the time series to accommodate, e.g., leader-follower changes. We test the method with simulations and with MEG data from subjects who received the same naturalistic stimulus sequence. The method may help analyse future experiments where the two subjects are measured simultaneously while engaged in social interaction.

  6. Does Signal Degradation Affect Top-Down Processing of Speech?

    PubMed

    Wagner, Anita; Pals, Carina; de Blecourt, Charlotte M; Sarampalis, Anastasios; Başkent, Deniz

    2016-01-01

    Speech perception is formed based on both the acoustic signal and listeners' knowledge of the world and semantic context. Access to semantic information can facilitate interpretation of degraded speech, such as speech in background noise or the speech signal transmitted via cochlear implants (CIs). This paper focuses on the latter, and investigates the time course of understanding words, and how sentential context reduces listeners' dependency on the acoustic signal for natural and degraded speech via an acoustic CI simulation.In an eye-tracking experiment we combined recordings of listeners' gaze fixations with pupillometry, to capture effects of semantic information on both the time course and effort of speech processing. Normal-hearing listeners were presented with sentences with or without a semantically constraining verb (e.g., crawl) preceding the target (baby), and their ocular responses were recorded to four pictures, including the target, a phonological (bay) competitor and a semantic (worm) and an unrelated distractor.The results show that in natural speech, listeners' gazes reflect their uptake of acoustic information, and integration of preceding semantic context. Degradation of the signal leads to a later disambiguation of phonologically similar words, and to a delay in integration of semantic information. Complementary to this, the pupil dilation data show that early semantic integration reduces the effort in disambiguating phonologically similar words. Processing degraded speech comes with increased effort due to the impoverished nature of the signal. Delayed integration of semantic information further constrains listeners' ability to compensate for inaudible signals.

  7. Calcium Signals: The Lead Currency of Plant Information Processing

    PubMed Central

    Kudla, Jörg; Batistič, Oliver; Hashimoto, Kenji

    2010-01-01

    Ca2+ signals are core transducers and regulators in many adaptation and developmental processes of plants. Ca2+ signals are represented by stimulus-specific signatures that result from the concerted action of channels, pumps, and carriers that shape temporally and spatially defined Ca2+ elevations. Cellular Ca2+ signals are decoded and transmitted by a toolkit of Ca2+ binding proteins that relay this information into downstream responses. Major transduction routes of Ca2+ signaling involve Ca2+-regulated kinases mediating phosphorylation events that orchestrate downstream responses or comprise regulation of gene expression via Ca2+-regulated transcription factors and Ca2+-responsive promoter elements. Here, we review some of the remarkable progress that has been made in recent years, especially in identifying critical components functioning in Ca2+ signal transduction, both at the single-cell and multicellular level. Despite impressive progress in our understanding of the processing of Ca2+ signals during the past years, the elucidation of the exact mechanistic principles that underlie the specific recognition and conversion of the cellular Ca2+ currency into defined changes in protein–protein interaction, protein phosphorylation, and gene expression and thereby establish the specificity in stimulus response coupling remain to be explored. PMID:20354197

  8. Demystifying biomedical signals: a student centred approach to learning signal processing.

    PubMed

    Simpson, D M; De Stefano, A; Allen, R; Lutman, M E

    2005-09-01

    The processing and analysis of physiological signals has become firmly established in clinical medicine and biomedical research. Many of the users of this technology however do not come from an engineering or science background, and traditional approaches in teaching signal processing are thus not appropriate for them. We have therefore developed a series of modular courses that are aimed specifically at an audience with a background in medicine, health-care or the life-sciences. In these courses, we focus on the concepts, principles and rationale of applying signal processing methods, rather than the mathematical foundations of the techniques. Thus, we aim to remove some of the perceived 'mystery' often surrounding this subject. The very practical approach, with hands-on experience using the MATLAB software, has been well received, with strong evidence that students have learnt to apply their knowledge. This paper describes the learning and teaching approach taken, and some of the experience acquired.

  9. Design of multichannel filter banks for subband coding of audio signals using multirate signal processing techniques

    NASA Astrophysics Data System (ADS)

    Goel, Aditya

    2007-09-01

    This paper presents a design technique for multi channel filter banks for subband coding of audio signal. In sub-band coding, the speech is first split into frequency bands using a bank of bandpass filters. The individual band pass signals are then decimated by a factor 'N' and encoded for transmission. A filter bank is a collection of bandpass filters, all processing the same input signal. The important parameters in sub-band coders are the number of frequency bands and the frequency range of the system, and the sub-band coding technique. The total number of filters required are 2N. The sub-band signals can be reconstructed perfectly with linear-phase FIR filters. The filter bank is designed so as to overcome the effect of non-ideal transition-band and stop-bands filtering. With real-world filters, the non-zero signal energy in the transition and stop bands is reflected back into the pass-band during the interpolation process at the receiver causing aliasing. This aliasing is canceled in the filter bank during reconstruction of the signal. This paper deals with the designing of 8 band filter banks and coding the subband signals at various bit rates using DPCM technique. In this we used a sampling rate of 44.1Khz. The first two bands are coded at 8 bits/sample, next three bands are coded at 4bits/sample and last 3 bands are coded at 2 bits/sample. Lower frequency spectrum is encoded at higher bit rate, as more energy is concentrated in the lower range. Simulated results using MATLAB Software shows that a compression ratio of 3.76:1 is achieved with perceptual quality. Beyond this we find that the signal quality degraded to reasonable extent, which is not recommended. There has to be a tradeoff between the compression ratio and Quality of transmitted signal.

  10. Detecting nonuniformity in small welds and solder seams using optical correlation and electronic processing.

    PubMed

    Wagner, J W

    1981-10-15

    Using holographic matched filtering and electronic processing, small variations in surface displacement along the seam of a hermetic microcircuit package can be detected when the seam is stressed. Destructive analysis of a solder-sealed package reveals a strong correlation between optical signal variations and nonuniformity of solder adhesion and wetting along the seam. The technique promises potential application as a means of nondestructively inspecting for flaws in small welded or soldered seams.

  11. The COBRA/CARMA Correlator Data Processing System

    NASA Astrophysics Data System (ADS)

    Scott, S. L.; Hobbs, R.; Beard, A.; Daniel, P.; Mehringer, D.; Plante, R.; Kraybill, J. C.; Wright, M.; Leitch, E.; Amarnath, N. S.; Pound, M. W.; Rauch, K. P.; Teuben, P. J.

    The Caltech Owens Valley Broadband Reprogrammable Array (COBRA) digital correlator is an FPGA based spectrometer with 16 MHz resolution and 4 GHz total bandwidth that will be commissioned on the Caltech Millimeter-wave Array in November, 2002. The Combined Array for Research in Millimeter-Wave Astronomy (CARMA) will join the Caltech array with the BIMA array on a new high elevation site in 2005. The COBRA hardware and computing architecture described here will be the basis for the two CARMA correlators. The COBRA architecture uses nine computers to provide the hardware interface and initial processing. Data is transported using CORBA to a tenth machine that implements the data processing pipeline as multiple processes passing data through shared memory.

  12. Electrophysiological correlates of aesthetic music processing: comparing experts with laypersons.

    PubMed

    Müller, Mira; Höfel, Lea; Brattico, Elvira; Jacobsen, Thomas

    2009-07-01

    We analyzed the processes of making aesthetic judgments of music, focusing on the differences between music experts and laypersons. Sixteen students of musicology and 16 control subjects (also students) judged the aesthetic value as well as the harmonic correctness of chord sequences. Event-related potential (ERP) data indicate differences between experts and laypersons in making aesthetic judgments at three different processing stages. Additionally, effects of expertise on ERP components that have previously been proven to be sensitive to musical training were replicated. The study thus provides insights into the effects of musical expertise on neural correlates of aesthetic music processing.

  13. dNSP: a biologically inspired dynamic Neural network approach to Signal Processing.

    PubMed

    Cano-Izquierdo, José Manuel; Ibarrola, Julio; Pinzolas, Miguel; Almonacid, Miguel

    2008-09-01

    The arriving order of data is one of the intrinsic properties of a signal. Therefore, techniques dealing with this temporal relation are required for identification and signal processing tasks. To perform a classification of the signal according with its temporal characteristics, it would be useful to find a feature vector in which the temporal attributes were embedded. The correlation and power density spectrum functions are suitable tools to manage this issue. These functions are usually defined with statistical formulation. On the other hand, in biology there can be found numerous processes in which signals are processed to give a feature vector; for example, the processing of sound by the auditory system. In this work, the dNSP (dynamic Neural Signal Processing) architecture is proposed. This architecture allows representing a time-varying signal by a spatial (thus statical) vector. Inspired by the aforementioned biological processes, the dNSP performs frequency decomposition using an analogical parallel algorithm carried out by simple processing units. The architecture has been developed under the paradigm of a multilayer neural network, where the different layers are composed by units whose activation functions have been extracted from the theory of Neural Dynamic [Grossberg, S. (1988). Nonlinear neural networks principles, mechanisms and architectures. Neural Networks, 1, 17-61]. A theoretical study of the behavior of the dynamic equations of the units and their relationship with some statistical functions allows establishing a parallelism between the unit activations and correlation and power density spectrum functions. To test the capabilities of the proposed approach, several testbeds have been employed, i.e. the frequencial study of mathematical functions. As a possible application of the architecture, a highly interesting problem in the field of automatic control is addressed: the recognition of a controlled DC motor operating state.

  14. The Analysis of Surface EMG Signals with the Wavelet-Based Correlation Dimension Method

    PubMed Central

    Zhang, Yanyan; Wang, Jue

    2014-01-01

    Many attempts have been made to effectively improve a prosthetic system controlled by the classification of surface electromyographic (SEMG) signals. Recently, the development of methodologies to extract the effective features still remains a primary challenge. Previous studies have demonstrated that the SEMG signals have nonlinear characteristics. In this study, by combining the nonlinear time series analysis and the time-frequency domain methods, we proposed the wavelet-based correlation dimension method to extract the effective features of SEMG signals. The SEMG signals were firstly analyzed by the wavelet transform and the correlation dimension was calculated to obtain the features of the SEMG signals. Then, these features were used as the input vectors of a Gustafson-Kessel clustering classifier to discriminate four types of forearm movements. Our results showed that there are four separate clusters corresponding to different forearm movements at the third resolution level and the resulting classification accuracy was 100%, when two channels of SEMG signals were used. This indicates that the proposed approach can provide important insight into the nonlinear characteristics and the time-frequency domain features of SEMG signals and is suitable for classifying different types of forearm movements. By comparing with other existing methods, the proposed method exhibited more robustness and higher classification accuracy. PMID:24868240

  15. The analysis of surface EMG signals with the wavelet-based correlation dimension method.

    PubMed

    Wang, Gang; Zhang, Yanyan; Wang, Jue

    2014-01-01

    Many attempts have been made to effectively improve a prosthetic system controlled by the classification of surface electromyographic (SEMG) signals. Recently, the development of methodologies to extract the effective features still remains a primary challenge. Previous studies have demonstrated that the SEMG signals have nonlinear characteristics. In this study, by combining the nonlinear time series analysis and the time-frequency domain methods, we proposed the wavelet-based correlation dimension method to extract the effective features of SEMG signals. The SEMG signals were firstly analyzed by the wavelet transform and the correlation dimension was calculated to obtain the features of the SEMG signals. Then, these features were used as the input vectors of a Gustafson-Kessel clustering classifier to discriminate four types of forearm movements. Our results showed that there are four separate clusters corresponding to different forearm movements at the third resolution level and the resulting classification accuracy was 100%, when two channels of SEMG signals were used. This indicates that the proposed approach can provide important insight into the nonlinear characteristics and the time-frequency domain features of SEMG signals and is suitable for classifying different types of forearm movements. By comparing with other existing methods, the proposed method exhibited more robustness and higher classification accuracy.

  16. CHIRP-Like Signals: Estimation, Detection and Processing A Sequential Model-Based Approach

    SciTech Connect

    Candy, J. V.

    2016-08-04

    Chirp signals have evolved primarily from radar/sonar signal processing applications specifically attempting to estimate the location of a target in surveillance/tracking volume. The chirp, which is essentially a sinusoidal signal whose phase changes instantaneously at each time sample, has an interesting property in that its correlation approximates an impulse function. It is well-known that a matched-filter detector in radar/sonar estimates the target range by cross-correlating a replicant of the transmitted chirp with the measurement data reflected from the target back to the radar/sonar receiver yielding a maximum peak corresponding to the echo time and therefore enabling the desired range estimate. In this application, we perform the same operation as a radar or sonar system, that is, we transmit a “chirp-like pulse” into the target medium and attempt to first detect its presence and second estimate its location or range. Our problem is complicated by the presence of disturbance signals from surrounding broadcast stations as well as extraneous sources of interference in our frequency bands and of course the ever present random noise from instrumentation. First, we discuss the chirp signal itself and illustrate its inherent properties and then develop a model-based processing scheme enabling both the detection and estimation of the signal from noisy measurement data.

  17. Advanced study of video signal processing in low signal to noise environments

    NASA Technical Reports Server (NTRS)

    Carden, F.; Gilbert, A.

    1972-01-01

    The frame to frame correlation properties of the video process are utilized to reduce the mean squared error of the demodulated video where zero mean noise is a factor. An interpolative estimator is used for continuous estimation with the output process delayed in time by one frame. Theoretical development shows that for the model herein developed reduction of the mean squared error by 1.0 to 4.0 db possible for parameter ranges of interest. Interpolative estimation using inter-frame correlation properties of a video process is then applied to the Apollo 17 parameters to yield a model for application on that mission.

  18. P-code enhanced method for processing encrypted GPS signals without knowledge of the encryption code

    NASA Technical Reports Server (NTRS)

    Meehan, Thomas K. (Inventor); Thomas, Jr., Jess Brooks (Inventor); Young, Lawrence E. (Inventor)

    2000-01-01

    In the preferred embodiment, an encrypted GPS signal is down-converted from RF to baseband to generate two quadrature components for each RF signal (L1 and L2). Separately and independently for each RF signal and each quadrature component, the four down-converted signals are counter-rotated with a respective model phase, correlated with a respective model P code, and then successively summed and dumped over presum intervals substantially coincident with chips of the respective encryption code. Without knowledge of the encryption-code signs, the effect of encryption-code sign flips is then substantially reduced by selected combinations of the resulting presums between associated quadrature components for each RF signal, separately and independently for the L1 and L2 signals. The resulting combined presums are then summed and dumped over longer intervals and further processed to extract amplitude, phase and delay for each RF signal. Precision of the resulting phase and delay values is approximately four times better than that obtained from straight cross-correlation of L1 and L2. This improved method provides the following options: separate and independent tracking of the L1-Y and L2-Y channels; separate and independent measurement of amplitude, phase and delay L1-Y channel; and removal of the half-cycle ambiguity in L1-Y and L2-Y carrier phase.

  19. The influence of signals correlation on the long-term stability of a tandem of quantum magnetometers with laser pumping

    NASA Astrophysics Data System (ADS)

    Fedorov, M. I.; Ermak, S. V.; Petrenko, M. V.; Semenov, V. V.

    2016-08-01

    The results of studies of the long-term frequency stability as a function of the correlation coefficient for a tandem of two quantum magnetometers with laser pumping of 87Rb in wall-coated vapour cell are represented. Measurement scheme includes a low-frequency self-generating magnetometer and a quantum microwave discriminator working at magnetic dipole transitions of radio-optical end state resonance. The difference of synchronously detected signals is processed to determine the Allan variance as a function of averaging time and correlation coefficient of signals. These parameters are essentially dependent both on the pumping light intensity and polarization and the intensity of radio fields that are produced in the working cell.

  20. 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.

  1. SoC-based architecture for biomedical signal processing.

    PubMed

    Gutiérrez-Rivas, R; Hernández, A; García, J J; Marnane, W

    2015-01-01

    Over the last decades, many algorithms have been proposed for processing biomedical signals. Most of these algorithms have been focused on the elimination of noise and artifacts existing in these signals, so they can be used for automatic monitoring and/or diagnosis applications. With regard to remote monitoring, the use of portable devices often requires a reduced number of resources and power consumption, being necessary to reach a trade-off between the accuracy of algorithms and their computational complexity. This paper presents a SoC (System-on-Chip) architecture, based on a FPGA (Field-Programmable Gate Array) device, suitable for the implementation of biomedical signal processing. The proposal has been successfully validated by implementing an efficient QRS complex detector. The results show that, using a reduced amount of resources, values of sensitivity and positive predictive value above 99.49% are achieved, which make the proposed approach suitable for telemedicine applications.

  2. 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.

  3. Reconfigurable high-speed optical signal processing and high-capacity optical transmitter

    NASA Astrophysics Data System (ADS)

    Chitgarha, Mohammad Reza

    The field of optics and photonics enables several technologies including communication, bioimaging, spectroscopy, Ladars, microwave photonics and data processing [1-139]. The ability to use and manipulate large amounts of data is transforming many vital areas of society. The high capacity that optics brought to communications might also bring advantages to increase performance in signal processing by using a novel all-optical implementation of a tapped-delay-line, a fundamental building block for digital signal processing. This all-optical alternative provides real-time processing of amplitude- and phase-encoded optical fields, such that the overall potential speed-up is 10-100 fold faster than individual electronic processors with 5 GHz clock speeds. It can also enhance the optical data generation and transmission techniques by using different optical nonlinear processes to achieve higher baud rate data with more complex modulation format. Here, we demonstrate a reconfigurable high- speed optical tapped-delay-line, enabling several fundamental real-time signal processing functions such as equalization, correlation and discrete Fourier transform. Using nonlinear optics and dispersive elements, continuous tunability in time, amplitude and phase of the tapped-delay-line can be achieved at high speed. We also demonstrate a reconfigurable optical generation of higher-order modulation formats including pulse-amplitude-modulation (PAM) signals and quadrature-amplitude-modulation (QAM) signals [140-195].

  4. Parallel Processing of Broad-Band PPM Signals

    NASA Technical Reports Server (NTRS)

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

    2010-01-01

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

  5. Fault Detection of Gearbox from Inverter Signals Using Advanced Signal Processing Techniques

    NASA Astrophysics Data System (ADS)

    Pislaru, C.; Lane, M.; Ball, A. D.; Gu, F.

    2012-05-01

    The gear faults are time-localized transient events so time-frequency analysis techniques (such as the Short-Time Fourier Transform, Wavelet Transform, motor current signature analysis) are widely used to deal with non-stationary and nonlinear signals. Newly developed signal processing techniques (such as empirical mode decomposition and Teager Kaiser Energy Operator) enabled the recognition of the vibration modes that coexist in the system, and to have a better understanding of the nature of the fault information contained in the vibration signal. However these methods require a lot of computational power so this paper presents a novel approach of gearbox fault detection using the inverter signals to monitor the load, rather than the motor current. The proposed technique could be used for continuous monitoring as well as on-line damage detection systems for gearbox maintenance.

  6. Signal processing techniques for clutter filtering and wind shear detection

    NASA Technical Reports Server (NTRS)

    Baxa, Ernest G., Jr.; Deshpande, Manohar D

    1991-01-01

    An extended Prony algorithm applicable to signal processing techniques for clutter filtering and windshear detection is discussed. The algorithm is based upon modelling the radar return as a time series, and appears to offer potential for improving hazard factor estimates in the presence of strong clutter returns.

  7. Cancer systems biology: signal processing for cancer research.

    PubMed

    Yli-Harja, Olli; Ylipää, Antti; Nykter, Matti; Zhang, Wei

    2011-04-01

    In this editorial we introduce the research paradigms of signal processing in the era of systems biology. Signal processing is a field of science traditionally focused on modeling electronic and communications systems, but recently it has turned to biological applications with astounding results. The essence of signal processing is to describe the natural world by mathematical models and then, based on these models, develop efficient computational tools for solving engineering problems. Here, we underline, with examples, the endless possibilities which arise when the battle-hardened tools of engineering are applied to solve the problems that have tormented cancer researchers. Based on this approach, a new field has emerged, called cancer systems biology. Despite its short history, cancer systems biology has already produced several success stories tackling previously impracticable problems. Perhaps most importantly, it has been accepted as an integral part of the major endeavors of cancer research, such as analyzing the genomic and epigenomic data produced by The Cancer Genome Atlas (TCGA) project. Finally, we show that signal processing and cancer research, two fields that are seemingly distant from each other, have merged into a field that is indeed more than the sum of its parts.

  8. An Evaluation of Two Signal-Processing Hearing Aids.

    ERIC Educational Resources Information Center

    Dempsey, James J.; Linzalone, Tanya G.

    1991-01-01

    This study, involving 15 older adults with hearing impairments, investigated the relationship between sentence recognition ability and two types of signal processing in hearing aids. Results indicated a significant improvement in sentence recognition when employing an instrument with adaptive compression versus an instrument with an adaptive…

  9. An Interactive Graphics Program for Investigating Digital Signal Processing.

    ERIC Educational Resources Information Center

    Miller, Billy K.; And Others

    1983-01-01

    Describes development of an interactive computer graphics program for use in teaching digital signal processing. The program allows students to interactively configure digital systems on a monitor display and observe their system's performance by means of digital plots on the system's outputs. A sample program run is included. (JN)

  10. Advanced Digital Signal Processing for Hybrid Lidar FY 2013

    DTIC Science & Technology

    2013-01-01

    Report 4. TITLE AND SUBTITLE Advance Digital Signal Processing for Hybrid Lidar 6. AUTHOR(S) William D. Jemison 7. PERFORMING ORGANIZATION NAME(S...development of signed processing algorithms for hybrid lidar - radar designed to improve detection performance. i , 15. SUBJECT TERMS Hybrid... Lidar - Radar 16. SECURITY CLASSIFICATION OF: a. REPORT b. ABSTRACT c. THIS PAGE 17. LIMITATION OF ABSTRACT 18. NUMBER OF PAGES 19a. NAME OF

  11. SEMICONDUCTOR TECHNOLOGY A signal processing method for the friction-based endpoint detection system of a CMP process

    NASA Astrophysics Data System (ADS)

    Chi, Xu; Dongming, Guo; Zhuji, Jin; Renke, Kang

    2010-12-01

    A signal processing method for the friction-based endpoint detection system of a chemical mechanical polishing (CMP) process is presented. The signal process method uses the wavelet threshold denoising method to reduce the noise contained in the measured original signal, extracts the Kalman filter innovation from the denoised signal as the feature signal, and judges the CMP endpoint based on the feature of the Kalman filter innovation sequence during the CMP process. Applying the signal processing method, the endpoint detection experiments of the Cu CMP process were carried out. The results show that the signal processing method can judge the endpoint of the Cu CMP process.

  12. Biomechanical Correlates of Surface Electromyography Signals Obtained during Swallowing by Healthy Adults

    ERIC Educational Resources Information Center

    Crary, Michael A.; Carnaby (Mann), Giselle D.; Groher, Michael E.

    2006-01-01

    Purpose: The purpose of this study was to describe biomechanical correlates of the surface electromyographic signal obtained during swallowing by healthy adult volunteers. Method: Seventeen healthy adults were evaluated with simultaneous videofluoroscopy and surface electromyography (sEMG) while swallowing 5 mL of liquid barium sulfate. Three…

  13. Cross-correlation analysis of mechanomyographic signals detected in two axes.

    PubMed

    Beck, Travis W; Dillon, Michael A; DeFreitas, Jason M; Stock, Matt S

    2009-12-01

    The purpose of this study was to use laser displacement sensors to examine the cross-correlation of surface mechanomyographic (MMG) signals detected from the rectus femoris muscle in perpendicular and transverse axes during isometric muscle actions of the leg extensors. Ten healthy men (mean +/- SD age = 22.1 +/- 1.6 years) and ten healthy women (age = 24.4 +/- 2.8 years) volunteered to perform submaximal to maximal isometric muscle actions of the dominant leg extensors. During each muscle action, two separate MMG signals were detected from the rectus femoris with laser displacement sensors. One MMG sensor was oriented in an axis that was perpendicular (PERP) to the muscle surface, and the second sensor was oriented in an axis that was transverse (TRAN) to the muscle surface. For each subject and force level, the MMG signals from the PERP and TRAN sensors were cross-correlated. The results showed maximum cross-correlation coefficients that ranged from R(x)(,y) = 0.273 to 0.989, but all subjects demonstrated at least one coefficient greater than 0.89. These findings showed a high level of association between the MMG signals detected in the perpendicular and transverse axes. Thus, it may not be necessary to detect MMG signals in multiple axes.

  14. Signal correlation in the tandem of a spin oscillator and microwave frequency discriminator with laser-pumped alkali atoms

    NASA Astrophysics Data System (ADS)

    Baranov, A. A.; Ermak, S. V.; Sagitov, E. A.; Smolin, R. V.; Semenov, V. V.

    2016-02-01

    We have studied the influence of low-frequency noise on the stability of resonance frequency of a self-oscillating magnetometer on 87Rb vapor with simultaneous monitoring of the signal of radio-optical resonance on the magnetic-field-dependent microwave transition under laser pumping at the D 2 line of the head doublet. The difference of synchronous records of detected signals reduced to the same scale in magnetic field units was processed to determine the Allan variance as a function of the averaging time. The correlation coefficient characterizing the coupling of detected signals determined by the pumping rate and intensity of radio fields generated in the region of the absorption chamber. The self-oscillating magnetometer can only operate provided that there is laser tuning to the long-wavelength component of the electric-dipole transition.

  15. Limitations of signal averaging due to temporal correlation in laser remote-sensing measurements.

    PubMed

    Menyuk, N; Killinger, D K; Menyuk, C R

    1982-09-15

    Laser remote sensing involves the measurement of laser-beam transmission through the atmosphere and is subject to uncertainties caused by strong fluctuations due primarily to speckle, glint, and atmospheric-turbulence effects. These uncertainties are generally reduced by taking average values of increasing numbers of measurements. An experiment was carried out to directly measure the effect of signal averaging on back-scattered laser return signals from a diffusely reflecting target using a direct-detection differential-absorption lidar (DIAL) system. The improvement in accuracy obtained by averaging over increasing numbers of data points was found to be smaller than that predicted for independent measurements. The experimental results are shown to be in excellent agreement with a theoretical analysis which considers the effect of temporal correlation. The analysis indicates that small but long-term temporal correlation severely limits the improvement available through signal averaging.

  16. Pre-Processing and Cross-Correlation Techniques for Time-Distance Helioseismology

    NASA Astrophysics Data System (ADS)

    Wang, N.; de Ridder, S.; Zhao, J.

    2014-12-01

    In chaotic wave fields excited by a random distribution of noise sources a cross-correlation of the recordings made at two stations yield the interstation wave-field response. After early successes in helioseismology, laboratory studies and earth-seismology, this technique found broad application in global and regional seismology. This development came with an increasing understanding of pre-processing and cross-correlation workflows to yield an optimal signal-to-noise ratio (SNR). Helioseismologist rely heavily on stacking to increase the SNR. Until now, they have not studied different spectral-whitening and cross-correlation workflows and relies heavily on stacking to increase the SNR. The recordings vary considerably between sunspots and regular portions of the sun. Within the sunspot the periodic effects of the observation satellite orbit are difficult to remove. We remove a running alpha-mean from the data and apply a soft clip to deal with data glitches. The recordings contain energy of both flow and waves. A frequency domain filter selects the wave energy. Then the data is input to several pre-processing and cross-correlation techniques, common to earth seismology. We anticipate that spectral whitening will flatten the energy spectrum of the cross-correlations. We also expect that the cross-correlations converge faster to their expected value when the data is processed over overlapping windows. The result of this study are expected to aid in decreasing the stacking while maintaining good SNR.

  17. Correlational analysis of electroencephalographic and end-tidal carbon dioxide signals during breath-hold exercise.

    PubMed

    Morelli, Maria Sole; Vanello, Nicola; Giannoni, Alberto; Frijia, Francesca; Hartwig, Valentina; Maestri, Michelangelo; Bonanni, Enrica; Carnicelli, Luca; Positano, Vincenzo; Passino, Claudio; Emdin, Michele; Landini, Luigi

    2015-01-01

    The central mechanism of breathing control is not totally understood. Several studies evaluated the correlation between electroencephalographic (EEG) power spectra and respiratory signals by performing resting state tasks or adopting hypercapnic/hypoxic stimuli. The observation of brain activity during voluntary breath hold tasks, might be an useful approach to highlight the areas involved in mechanism of breath regulation. Nevertheless, studies of brain activity with EEG could present some limitations due to presence of severe artifacts. When artifact rejection methods, as independent component analysis, cannot reliably clean EEG data, it is necessary to exclude noisy segments. In this study, global field power in the delta band and end-tidal CO2 were derived from EEG and CO2 signals respectively in 4 healthy subjects during a breath-hold task. The cross correlation function between the two signals was estimated taking into account the presence of missing samples. The statistical significance of the correlation coefficients at different time lags was assessed using surrogate data. Some simulations are introduced to evaluate the effect of missing data on the correlational analysis and their results are discussed. Results obtained on subjects show a significant correlation between changes in EEG power in the delta band and end-tidal CO2. Moreover, the changes in end-tidal CO2 were found to precede those of global field power. These results might help to better understand the cortical mechanisms involved in the control of breathing.

  18. Evaluation of correlation property of linear-frequency-modulated signals coded by maximum-length sequences

    NASA Astrophysics Data System (ADS)

    Yamanaka, Kota; Hirata, Shinnosuke; Hachiya, Hiroyuki

    2016-07-01

    Ultrasonic distance measurement for obstacles has been recently applied in automobiles. The pulse-echo method based on the transmission of an ultrasonic pulse and time-of-flight (TOF) determination of the reflected echo is one of the typical methods of ultrasonic distance measurement. Improvement of the signal-to-noise ratio (SNR) of the echo and the avoidance of crosstalk between ultrasonic sensors in the pulse-echo method are required in automotive measurement. The SNR of the reflected echo and the resolution of the TOF are improved by the employment of pulse compression using a maximum-length sequence (M-sequence), which is one of the binary pseudorandom sequences generated from a linear feedback shift register (LFSR). Crosstalk is avoided by using transmitted signals coded by different M-sequences generated from different LFSRs. In the case of lower-order M-sequences, however, the number of measurement channels corresponding to the pattern of the LFSR is not enough. In this paper, pulse compression using linear-frequency-modulated (LFM) signals coded by M-sequences has been proposed. The coding of LFM signals by the same M-sequence can produce different transmitted signals and increase the number of measurement channels. In the proposed method, however, the truncation noise in autocorrelation functions and the interference noise in cross-correlation functions degrade the SNRs of received echoes. Therefore, autocorrelation properties and cross-correlation properties in all patterns of combinations of coded LFM signals are evaluated.

  19. Dynamic force signal processing system of a robot manipulator

    NASA Technical Reports Server (NTRS)

    Uchiyama, M.; Kitagaki, K.; Hakomori, K.

    1987-01-01

    If dynamic noises such as those caused by the inertia forces of the hand can be eliminated from the signal of the force sensor installed on the wrist of the robot manipulator and if the necessary information of the external force can be detected with high sensitivity and high accuracy, a fine force feedback control for robots used in high speed and various fields will be possible. As the dynamic force sensing system, an external force estimate method with the extended Kalman filter is suggested and simulations and tests for a one axis force were performed. Later a dynamic signal processing system of six axes was composed and tested. The results are presented.

  20. Mass spectral peak distortion due to Fourier transform signal processing.

    PubMed

    Rockwood, Alan L; Erve, John C L

    2014-12-01

    Distortions of peaks can occur when one uses the standard method of signal processing of data from the Orbitrap and other FT-based methods of mass spectrometry. These distortions arise because the standard method of signal processing is not a linear process. If one adds two or more functions, such as time-dependent signals from a Fourier transform mass spectrometer and performs a linear operation on the sum, the result is the same as if the operation was performed on separate functions and the results added. If this relationship is not valid, the operation is non-linear and can produce unexpected and/or distorted results. Although the Fourier transform itself is a linear operator, the standard algorithm for processing spectra in Fourier transform-based methods include non-linear mathematical operators such that spectra processed by the standard algorithm may become distorted. The most serious consequence is that apparent abundances of the peaks in the spectrum may be incorrect. In light of these considerations, we performed theoretical modeling studies to illustrate several distortion effects that can be observed, including abundance distortions. In addition, we discuss experimental systems where these effects may manifest, including suggested systems for study that should demonstrate these peak distortions. Finally, we point to several examples in the literature where peak distortions may be rationalized by the phenomena presented here.

  1. New challenges in signal processing in astrophysics: the SKA case

    NASA Astrophysics Data System (ADS)

    Faulkner, Andrew; Zarb-Adami, Kristian; Geralt Bij de Vaate, Jan

    2015-07-01

    Signal processing and communications are driving the latest generation of radio telescopes with major developments taking place for use on the Square Kilometre Array, SKA, the next generation low frequency radio telescope. The data rates and processing performance that can be achieved with currently available components means that concepts from the earlier days of radio astronomy, phased arrays, can be used at higher frequencies, larger bandwidths and higher numbers of beams. Indeed it has been argued that the use of dishes as a mechanical beamformer only gained strong acceptance to mitigate the processing load from phased array technology. The balance is changing and benefits in both performance and cost can be realised. In this paper we will mostly consider the signal processing implementation and control for very large phased arrays consisting of hundreds of thousands of antennas or even millions of antennas. They can use current technology for the initial deployments. These systems are very large extending to hundreds of racks with thousands of signal processing modules that link through high-speed, but commercially available data networking devices. There are major challenges to accurately calibrate the arrays, mitigate power consumption and make the system maintainable.

  2. The Open Host Network Packet Process Correlator for Windows

    SciTech Connect

    2014-06-17

    The Hone sensors are packet-process correlation engines that log the relationships between applications and the communications they are responsible for. Hone sensors are available for a variety of platforms including Linux, Windows, and MacOSX. Hone sensors are designed to help analysts understand the meaning of communications on a deeper level by associating the origin or destination process to the communication. They do this by tracing communications on a per-packet basis, through the kernel of the operating system to determine their ultimate source/destination on the monitored machine.

  3. Modern Techniques in Acoustical Signal and Image Processing

    SciTech Connect

    Candy, J V

    2002-04-04

    Acoustical signal processing problems can lead to some complex and intricate techniques to extract the desired information from noisy, sometimes inadequate, measurements. The challenge is to formulate a meaningful strategy that is aimed at performing the processing required even in the face of uncertainties. This strategy can be as simple as a transformation of the measured data to another domain for analysis or as complex as embedding a full-scale propagation model into the processor. The aims of both approaches are the same--to extract the desired information and reject the extraneous, that is, develop a signal processing scheme to achieve this goal. In this paper, we briefly discuss this underlying philosophy from a ''bottom-up'' approach enabling the problem to dictate the solution rather than visa-versa.

  4. 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.

  5. Snore related signals processing in a private cloud computing system.

    PubMed

    Qian, Kun; Guo, Jian; Xu, Huijie; Zhu, Zhaomeng; Zhang, Gongxuan

    2014-09-01

    Snore related signals (SRS) have been demonstrated to carry important information about the obstruction site and degree in the upper airway of Obstructive Sleep Apnea-Hypopnea Syndrome (OSAHS) patients in recent years. To make this acoustic signal analysis method more accurate and robust, big SRS data processing is inevitable. As an emerging concept and technology, cloud computing has motivated numerous researchers and engineers to exploit applications both in academic and industry field, which could have an ability to implement a huge blue print in biomedical engineering. Considering the security and transferring requirement of biomedical data, we designed a system based on private cloud computing to process SRS. Then we set the comparable experiments of processing a 5-hour audio recording of an OSAHS patient by a personal computer, a server and a private cloud computing system to demonstrate the efficiency of the infrastructure we proposed.

  6. Toward optical signal processing using photonic reservoir computing.

    PubMed

    Vandoorne, Kristof; Dierckx, Wouter; Schrauwen, Benjamin; Verstraeten, David; Baets, Roel; Bienstman, Peter; Van Campenhout, Jan

    2008-07-21

    We propose photonic reservoir computing as a new approach to optical signal processing in the context of large scale pattern recognition problems. Photonic reservoir computing is a photonic implementation of the recently proposed reservoir computing concept, where the dynamics of a network of nonlinear elements are exploited to perform general signal processing tasks. In our proposed photonic implementation, we employ a network of coupled Semiconductor Optical Amplifiers (SOA) as the basic building blocks for the reservoir. Although they differ in many key respects from traditional software-based hyperbolic tangent reservoirs, we show using simulations that such a photonic reservoir can outperform traditional reservoirs on a benchmark classification task. Moreover, a photonic implementation offers the promise of massively parallel information processing with low power and high speed.

  7. Anomalous diffusion for a correlated process with long jumps

    NASA Astrophysics Data System (ADS)

    Srokowski, Tomasz

    2011-09-01

    We discuss diffusion properties of a dynamical system, which is characterised by long-tail distributions and finite correlations. The particle velocity has the stable Lévy distribution; it is assumed as a jumping process (the kangaroo process) with a variable jumping rate. Both the exponential and the algebraic form of the covariance-defined for the truncated distribution-are considered. It is demonstrated by numerical calculations that the stationary solution of the master equation for the case of power-law correlations decays with time, but a simple modification of the process makes the tails stable. The main result of the paper is a finding that-in contrast to the velocity fluctuations-the position variance may be finite. It rises with time faster than linearly: the diffusion is anomalously enhanced. On the other hand, a process which follows from a superposition of the Ornstein-Uhlenbeck-Lévy processes always leads to position distributions with a divergent variance which means accelerated diffusion.

  8. Passive correlation ranging of a geostationary satellite using DVB-S payload signals.

    NASA Astrophysics Data System (ADS)

    Shakun, Leonid; Shulga, Alexandr; Sybiryakova, Yevgeniya; Bushuev, Felix; Kaliuzhnyi, Mykola; Bezrukovs, Vladislavs; Moskalenko, Sergiy; Kulishenko, Vladislav; Balagura, Oleg

    2016-07-01

    Passive correlation ranging (PaCoRa) for geostationary satellites is now considered as an alternate to tone-ranging (https://artes.esa.int/search/node/PaCoRa). The PaCoRa method has been employed in the Research Institute "Nikolaev astronomical observatory" since the first experiment in August 2011 with two stations spatially separated on 150 km. The PaCoRa has been considered as an independent method for tracking the future Ukrainian geostationary satellite "Lybid'. Now a radio engineering complex (RC) for passive ranging consists of five spatially separated stations of receiving digital satellite television and a data processing center located in Mykolaiv. The stations are located in Kyiv, Kharkiv, Mukacheve, Mykolaiv (Ukraine) and in Ventspils (Latvia). Each station has identical equipment. The equipment allows making synchronous recording of fragments of the DVB-S signal from the quadrature detector output of a satellite television receiver. The fragments are recorded every second. Synchronization of the stations is performed using GPS receivers. Samples of the complex signal obtained in this way are archived and are sent to the data processing center over the Internet. Here the time differences of arrival (TDOA) for pairs of the stations are determined as a result of correlation processing of received signals. The values of the TDOA that measured every second are used for orbit determination (OD) of the satellite. The results of orbit determination of the geostationary telecommunication satellite "Eutelsat-13B" (13º East) obtained during about four months of observations in 2015 are presented in the report. The TDOA and OD accuracies are also given. Single-measurement error (1 sigma) of the TDOA is equal about 8.7 ns for all pairs of the stations. Standard deviations and average values of the residuals between the observed TDOA and the TDOA computed using the orbit elements obtained from optical measurements are estimated for the pairs Kharkiv-Mykolaiv and

  9. Comparative effects of optical-correlator signal-dependent and signal-independent noise on pattern-recognition performance with the phase-only filter

    NASA Astrophysics Data System (ADS)

    Terrillon, Jean-Christophe

    1995-11-01

    The comparative effects of optical-correlator signal-dependent and additive signal-independent noise on correlation-filter performance are analyzed by three different performance measures. For an identical value of the signal-to-noise ratio imposed on each type of noise in a binary input image, computer simulations performed with the phase-only filter show (i) that additive Gaussian signal-independent noise yields a much larger correlation-performance degradation than signal-dependent noise and (ii) that the different types of signal-dependent noise lead to similar correlation results because of similar effects on the input image that are inherent to the nature of the noise.

  10. On-Board Spaceborne Real-time Digital Signal Processing

    NASA Astrophysics Data System (ADS)

    Gao, G.; Long, F.; Liu, L.

    begin center Abstract end center This paper reports a preliminary study result of an on-board digital signal processing system It consists of the on-board processing requirement analysis functional specifications and implementation with the radiation tolerant field-programmable gate array FPGA technology The FPGA program is designed in the VHDL hardware description language and implemented onto a high density F PGA chip The design takes full advantage of the massively parallel architecture of the VirtexII FPGA logic slices to achieve real-time processing at a big data rate Further more an FFT algorithm s implementation with the system is provided as an illustration

  11. Improved motion contrast and processing efficiency in OCT angiography using complex-correlation algorithm

    NASA Astrophysics Data System (ADS)

    Guo, Li; Li, Pei; Pan, Cong; Liao, Rujia; Cheng, Yuxuan; Hu, Weiwei; Chen, Zhong; Ding, Zhihua; Li, Peng

    2016-02-01

    The complex-based OCT angiography (Angio-OCT) offers high motion contrast by combining both the intensity and phase information. However, due to involuntary bulk tissue motions, complex-valued OCT raw data are processed sequentially with different algorithms for correcting bulk image shifts (BISs), compensating global phase fluctuations (GPFs) and extracting flow signals. Such a complicated procedure results in massive computational load. To mitigate such a problem, in this work, we present an inter-frame complex-correlation (CC) algorithm. The CC algorithm is suitable for parallel processing of both flow signal extraction and BIS correction, and it does not need GPF compensation. This method provides high processing efficiency and shows superiority in motion contrast. The feasibility and performance of the proposed CC algorithm is demonstrated using both flow phantom and live animal experiments.

  12. Minimum variance imaging based on correlation analysis of Lamb wave signals.

    PubMed

    Hua, Jiadong; Lin, Jing; Zeng, Liang; Luo, Zhi

    2016-08-01

    In Lamb wave imaging, MVDR (minimum variance distortionless response) is a promising approach for the detection and monitoring of large areas with sparse transducer network. Previous studies in MVDR use signal amplitude as the input damage feature, and the imaging performance is closely related to the evaluation accuracy of the scattering characteristic. However, scattering characteristic is highly dependent on damage parameters (e.g. type, orientation and size), which are unknown beforehand. The evaluation error can degrade imaging performance severely. In this study, a more reliable damage feature, LSCC (local signal correlation coefficient), is established to replace signal amplitude. In comparison with signal amplitude, one attractive feature of LSCC is its independence of damage parameters. Therefore, LSCC model in the transducer network could be accurately evaluated, the imaging performance is improved subsequently. Both theoretical analysis and experimental investigation are given to validate the effectiveness of the LSCC-based MVDR algorithm in improving imaging performance.

  13. Analog integrated circuits design for processing physiological signals.

    PubMed

    Li, Yan; Poon, Carmen C Y; Zhang, Yuan-Ting

    2010-01-01

    Analog integrated circuits (ICs) designed for processing physiological signals are important building blocks of wearable and implantable medical devices used for health monitoring or restoring lost body functions. Due to the nature of physiological signals and the corresponding application scenarios, the ICs designed for these applications should have low power consumption, low cutoff frequency, and low input-referred noise. In this paper, techniques for designing the analog front-end circuits with these three characteristics will be reviewed, including subthreshold circuits, bulk-driven MOSFETs, floating gate MOSFETs, and log-domain circuits to reduce power consumption; methods for designing fully integrated low cutoff frequency circuits; as well as chopper stabilization (CHS) and other techniques that can be used to achieve a high signal-to-noise performance. Novel applications using these techniques will also be discussed.

  14. The high speed low noise multi-data processing signal process circuit research of remote sensing

    NASA Astrophysics Data System (ADS)

    Su, Lei; Jiang, Haibin; Dong, Wang

    2013-08-01

    The high speed, low noise and integration characteristic are the main technology and the main development directions on the signal process circuit of the image sensor, especially in high resolution remote sensing. With these developments, the high noise limiting circuits, high speed data transfer system and the integrated design of the signal process circuit become more and more important. Therefore the requirement of the circuit system simulation is more and more important during the system design and PCB board design process. A CCD signal process circuit system which has the high speed, low noise and several selectable operate modes function was designed and certificated in this paper, during the CCD signal process circuit system design, simulation was made which include the signal integrity and the power integrity. The important devices such as FPGA and the DDR2 device were simulated, using the power integrity simulation the sensitive power planes of the FPGA on the PCB was modified to make the circuit operate more stabilize on a higher frequency. The main clock path and the high speed data path of the PCB board were simulated with the signal integrity. All the simulation works make the signal process circuit system's image's SNR value get higher and make the circuit system could operate well on higher frequency. In the board testing process, the PCB time diagrams were listed on the testing chapter and the wave's parameter meets the request. The real time diagram and the simulated result of the PCB board was listed respectively. The CCD signal process circuit system's images' SNR (Signal Noise Ratio) value, the 14bit AFE slew rate and the data transfer frequency is listed in the paper respective.

  15. Method and apparatus for a single channel digital communications system. [synchronization of received PCM signal by digital correlation with reference signal

    NASA Technical Reports Server (NTRS)

    Couvillon, L. A., Jr.; Carl, C.; Goldstein, R. M.; Posner, E. C.; Green, R. R. (Inventor)

    1973-01-01

    A method and apparatus are described for synchronizing a received PCM communications signal without requiring a separate synchronizing channel. The technique provides digital correlation of the received signal with a reference signal, first with its unmodulated subcarrier and then with a bit sync code modulated subcarrier, where the code sequence length is equal in duration to each data bit.

  16. Synthetic aperture radar signal processing on the MPP

    NASA Technical Reports Server (NTRS)

    Ramapriyan, H. K.; Seiler, E. J.

    1987-01-01

    Satellite-borne Synthetic Aperture Radars (SAR) sense areas of several thousand square kilometers in seconds and transmit phase history signal data several tens of megabits per second. The Shuttle Imaging Radar-B (SIR-B) has a variable swath of 20 to 50 km and acquired data over 100 kms along track in about 13 seconds. With the simplification of separability of the reference function, the processing still requires considerable resources; high speed I/O, large memory and fast computation. Processing systems with regular hardware take hours to process one Seasat image and about one hour for a SIR-B image. Bringing this processing time closer to acquisition times requires an end-to-end system solution. For the purpose of demonstration, software was implemented on the present Massively Parallel Processor (MPP) configuration for processing Seasat and SIR-B data. The software takes advantage of the high processing speed offered by the MPP, the large Staging Buffer, and the high speed I/O between the MPP array unit and the Staging Buffer. It was found that with unoptimized Parallel Pascal code, the processing time on the MPP for a 4096 x 4096 sample subset of signal data ranges between 18 and 30.2 seconds depending on options.

  17. Nasal airflow measurement using a compensated thermistor anemometer. Part 2. Computer signal processing and quantitative analysis.

    PubMed

    Besar, S S; Kelly, S W; Manley, M C

    1990-03-01

    A nasal anemometer is a useful tool for speech therapists in their assessment of treatment effectiveness. This work is the second part of a research scheme which describes how the system is compatible with the use of an IBM PC-AT microcomputer using a suitable analogue-to-digital convertor. This enables the system to perform signal processing and to display, draw, and calculate a numerical 'figure of merit' using Kendall's tau nonparametric correlation.

  18. Signal Processing in Periodically Forced Gradient Frequency Neural Networks.

    PubMed

    Kim, Ji Chul; Large, Edward W

    2015-01-01

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

  19. 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.

  20. Signal Processing in Periodically Forced Gradient Frequency Neural Networks

    PubMed Central

    Kim, Ji Chul; Large, Edward W.

    2015-01-01

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

  1. 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.

  2. Nonlinear signal processing of electroencephalograms for automated sleep monitoring

    NASA Astrophysics Data System (ADS)

    Wilson, D.; Rowlands, D. D.; James, Daniel A.; Cutmore, T.

    2005-02-01

    An automated classification technique is desirable to identify the different stages of sleep. In this paper a technique for differentiating the characteristics of each sleep phase has been developed. This is an ideal pre-processor stage for classifying systems such as neural networks. A wavelet based continuous Morlet transform was developed to analyse the EEG signal in both the time and frequency domain. Test results using two 100 epoch EEG test data sets from pre-recorded EEG data are presented. Key rhythms in the EEG signal were identified and classified using the continuous wavelet transform. The wavelet results indicated each sleep phase contained different rhythms and artefacts (noise from muscle movement in the EEG); providing proof that an EEG can be classified accordingly. The coefficients founded by the wavelet transform have been emphasised by statistical techniques. Hypothesis testing was used to highlight major differences between adjacent sleep stages. Various signal processing methods such as power spectrum density and the discrete wavelet transform have been used to emphasise particular characteristics in an EEG. By implementing signal processing methods on an EEG data set specific rules for each sleep stage have been developed suitable for a neural network classification solution.

  3. Biological signal processing with a genetic toggle switch.

    PubMed

    Hillenbrand, Patrick; Fritz, Georg; Gerland, Ulrich

    2013-01-01

    Complex gene regulation requires responses that depend not only on the current levels of input signals but also on signals received in the past. In digital electronics, logic circuits with this property are referred to as sequential logic, in contrast to the simpler combinatorial logic without such internal memory. In molecular biology, memory is implemented in various forms such as biochemical modification of proteins or multistable gene circuits, but the design of the regulatory interface, which processes the input signals and the memory content, is often not well understood. Here, we explore design constraints for such regulatory interfaces using coarse-grained nonlinear models and stochastic simulations of detailed biochemical reaction networks. We test different designs for biological analogs of the most versatile memory element in digital electronics, the JK-latch. Our analysis shows that simple protein-protein interactions and protein-DNA binding are sufficient, in principle, to implement genetic circuits with the capabilities of a JK-latch. However, it also exposes fundamental limitations to its reliability, due to the fact that biological signal processing is asynchronous, in contrast to most digital electronics systems that feature a central clock to orchestrate the timing of all operations. We describe a seemingly natural way to improve the reliability by invoking the master-slave concept from digital electronics design. This concept could be useful to interpret the design of natural regulatory circuits, and for the design of synthetic biological systems.

  4. Deterring watermark collusion attacks using signal processing techniques

    NASA Astrophysics Data System (ADS)

    Lemma, Aweke N.; van der Veen, Michiel

    2007-02-01

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

  5. Neural correlates of processing "self-conscious" vs. "basic" emotions.

    PubMed

    Gilead, Michael; Katzir, Maayan; Eyal, Tal; Liberman, Nira

    2016-01-29

    Self-conscious emotions are prevalent in our daily lives and play an important role in both normal and pathological behavior. Despite their immense significance, the neural substrates that are involved in the processing of such emotions are surprisingly under-studied. In light of this, we conducted an fMRI study in which participants thought of various personal events which elicited feelings of negative and positive self-conscious (i.e., guilt, pride) or basic (i.e., anger, joy) emotions. We performed a conjunction analysis to investigate the neural correlates associated with processing events that are related to self-conscious vs. basic emotions, irrespective of valence. The results show that processing self-conscious emotions resulted in activation within frontal areas associated with self-processing and self-control, namely, the mPFC extending to the dACC, and within the lateral-dorsal prefrontal cortex. Processing basic emotions resulted in activation throughout relatively phylogenetically-ancient regions of the cortex, namely in visual and tactile processing areas and in the insular cortex. Furthermore, self-conscious emotions differentially activated the mPFC such that the negative self-conscious emotion (guilt) was associated with a more dorsal activation, and the positive self-conscious emotion (pride) was associated with a more ventral activation. We discuss how these results shed light on the nature of mental representations and neural systems involved in self-reflective and affective processing.

  6. Information processing correlates of a size-contrast illusion.

    PubMed

    Gold, Jason M

    2014-01-01

    Perception is often influenced by context. A well-known class of perceptual context effects is perceptual contrast illusions, in which proximate stimulus regions interact to alter the perception of various stimulus attributes, such as perceived brightness, color and size. Although the phenomenal reality of contrast effects is well documented, in many cases the connection between these illusions and how information is processed by perceptual systems is not well understood. Here, we use noise as a tool to explore the information processing correlates of one such contrast effect: the Ebbinghaus-Titchener size-contrast illusion. In this illusion, the perceived size of a central dot is significantly altered by the sizes of a set of surrounding dots, such that the presence of larger surrounding dots tends to reduce the perceived size of the central dot (and vise versa). In our experiments, we first replicated previous results that have demonstrated the subjective reality of the Ebbinghaus-Titchener illusion. We then used visual noise in a detection task to probe the manner in which observers processed information when experiencing the illusion. By correlating the noise with observers' classification decisions, we found that the sizes of the surrounding contextual elements had a direct influence on the relative weight observers assigned to regions within and surrounding the central element. Specifically, observers assigned relatively more weight to the surrounding region and less weight to the central region in the presence of smaller surrounding contextual elements. These results offer new insights into the connection between the subjective experience of size-contrast illusions and their associated information processing correlates.

  7. Analysis of cross-correlations in electroencephalogram signals as an approach to proactive diagnosis of schizophrenia

    NASA Astrophysics Data System (ADS)

    Timashev, Serge F.; Panischev, Oleg Yu.; Polyakov, Yuriy S.; Demin, Sergey A.; Kaplan, Alexander Ya.

    2012-02-01

    We apply flicker-noise spectroscopy (FNS), a time series analysis method operating on structure functions and power spectrum estimates, to study the clinical electroencephalogram (EEG) signals recorded in children/adolescents (11 to 14 years of age) with diagnosed schizophrenia-spectrum symptoms at the National Center for Psychiatric Health (NCPH) of the Russian Academy of Medical Sciences. The EEG signals for these subjects were compared with the signals for a control sample of chronically depressed children/adolescents. The purpose of the study is to look for diagnostic signs of subjects' susceptibility to schizophrenia in the FNS parameters for specific electrodes and cross-correlations between the signals simultaneously measured at different points on the scalp. Our analysis of EEG signals from scalp-mounted electrodes at locations F3 and F4, which are symmetrically positioned in the left and right frontal areas of cerebral cortex, respectively, demonstrates an essential role of frequency-phase synchronization, a phenomenon representing specific correlations between the characteristic frequencies and phases of excitations in the brain. We introduce quantitative measures of frequency-phase synchronization and systematize the values of FNS parameters for the EEG data. The comparison of our results with the medical diagnoses for 84 subjects performed at NCPH makes it possible to group the EEG signals into 4 categories corresponding to different risk levels of subjects' susceptibility to schizophrenia. We suggest that the introduced quantitative characteristics and classification of cross-correlations may be used for the diagnosis of schizophrenia at the early stages of its development.

  8. Blind I/Q Signal Separation-Based Solutions for Receiver Signal Processing

    NASA Astrophysics Data System (ADS)

    Valkama, Mikko; Renfors, Markku; Koivunen, Visa

    2005-12-01

    This paper introduces some novel digital signal processing (DSP)-based approaches to some of the most fundamental tasks of radio receivers, namely, channel equalization, carrier synchronization, and I/Q mismatch compensation. The leading principle is to show that all these problems can be solved blindly (i.e., without training signals) by forcing the I and Q components of the observed data as independent as possible. Blind signal separation (BSS) is then introduced as an efficient tool to carry out these tasks, and simulation examples are used to illustrate the performance of the proposed approaches. The main application area of the presented carrier synchronization and I/Q mismatch compensation techniques is in direct-conversion type receivers, while the proposed channel equalization principles basically apply to any radio architecture.

  9. The effects of notch filters on the correlation properties of a PN signal

    NASA Technical Reports Server (NTRS)

    Sussman, S. M.; Ferrari, E. J.

    1974-01-01

    With wideband pseudo-noise (PN) communications systems, it is sometimes desirable to supplement the inherent interference rejection capabilities by adding notch filters to attenuate relatively narrowband interference. This correspondence presents an investigation of the effects of notch filters on the performance of PN correlation receivers. A theoretical analysis of the correlation drop due to filter distortion has been conducted and confirmed by experimentation. Additional measurements and analysis have established the trade-off between correlation drop and interference suppression as a function of interference bandwidth. A typical result is that by incurring a penalty of a 1-dB drop in correlation peak, interfering signals having bandwidths of 2 to 3% of the PN chip rate can be attenuated by 25 dB.

  10. 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.

  11. Autofocusing system based on signal processing of single chip microprocessor

    NASA Astrophysics Data System (ADS)

    Xu, Xiangdong; Zeng, Chao; Li, Feng; Huang, GuiZao

    2002-09-01

    In this paper, an auto-focusing system based on Signal Processing of Single-chip Microprocessor is introduced to realize auto-focusing. The system can automatically get the distance information of the worktable and drive the step motor to reach the aim of auto-focusing. The auto-focusing system is loaded in the original CMOS-based measuring system. After the AV signals from CMOS image sensor pass through the analog filter, the single-chip microprocessor samples and processes them, then controls the lens to be in focus. As a result, this method can not only achieve all functions of focusing, but also avoid complicated calculations. The system is low power consuming, programming rapidly. Here we analyse the key technique of the system and the results of the experiments are given. It can be practical applied and the further perfection of algorithm and software will result in the system having more function.

  12. Communications, Signal Processing, and Telemetering Research Program Review

    NASA Technical Reports Server (NTRS)

    1999-01-01

    A Communications, Signal Processing, and Telemetering Research Program Review was held on February 23, 1999. Research conducted under the grant was presented and reviewed, for progress, and for possible technology transfers. The research reviewed was in the following areas: (1) Bandwidth-efficient Modulation and nonlinear equalization; (2) Investigation of an architecture for parallel signal processing applicable to communications problems; (3)Coded partial response over satellites; (4) synchronization at Low SNR; (5) Serial concatenated convolutional codes and some implementation issues on high rate turbo codes; (6) Flight experiments; (7) Real time doppler tracking; (8) Space protocol testing; (9) Lightweight optical communications without carrying a laser in space. The presentations are given by the graduate students who performed the research.

  13. TOF-LIDAR signal processing using the CFAR detector

    NASA Astrophysics Data System (ADS)

    Ogawa, Takashi; Wanielik, Gerd

    2016-09-01

    In recent years, the lidar sensor has been receiving greater attention as being one of the prospective sensors for future intelligent vehicles. In order to enable advanced applications in a variety of road environments, it has become more important to detect various objects at a wider distance. Therefore, in this research we have focused on lidar signal processing to detect low signal-to-noise ratio (SNR) targets and proposed a higher sensitive detector. The detector is based on the constant false alarm rate (CFAR) processing framework in which an additional functionality of adaptive intensity integration is incorporated. Fundamental results through static experiments have shown a significant advantage in the detection performance in comparison to a conventional detector with constant thresholding.

  14. Relevant modes selection method based on Spearman correlation coefficient for laser signal denoising using empirical mode decomposition

    NASA Astrophysics Data System (ADS)

    Duan, Yabo; Song, Chengtian

    2016-12-01

    Empirical mode decomposition (EMD) is a recently proposed nonlinear and nonstationary laser signal denoising method. A noisy signal is broken down using EMD into oscillatory components that are called intrinsic mode functions (IMFs). Thresholding-based denoising and correlation-based partial reconstruction of IMFs are the two main research directions for EMD-based denoising. Similar to other decomposition-based denoising approaches, EMD-based denoising methods require a reliable threshold to determine which IMFs are noise components and which IMFs are noise-free components. In this work, we propose a new approach in which each IMF is first denoised using EMD interval thresholding (EMD-IT), and then a robust thresholding process based on Spearman correlation coefficient is used for relevant modes selection. The proposed method tackles the problem using a thresholding-based denoising approach coupled with partial reconstruction of the relevant IMFs. Other traditional denoising methods, including correlation-based EMD partial reconstruction (EMD-Correlation), discrete Fourier transform and wavelet-based methods, are investigated to provide a comparison with the proposed technique. Simulation and test results demonstrate the superior performance of the proposed method when compared with the other methods.

  15. Coupled Research in Ocean Acoustics and Signal Processing for the Next Generation of Underwater Acoustic Communication Systems

    DTIC Science & Technology

    2015-08-09

    Coupled Research in Ocean Acoustics and Signal Processing for the Next Generation of Underwater Acoustic Communication Systems 5a. CONTRACT NUMBER 5b...Processing for the Next Generation of Underwater Acoustic Communication Systems Principal Investigator’s Name: Dr. James Preisig Period Covered By...correlation structure of received communications signals after they have been converted to the frequency domain via Fourier Transforms as de- scribed in

  16. UniBoard: generic hardware for radio astronomy signal processing

    NASA Astrophysics Data System (ADS)

    Hargreaves, J. E.

    2012-09-01

    UniBoard is a generic high-performance computing platform for radio astronomy, developed as a Joint Research Activity in the RadioNet FP7 Programme. The hardware comprises eight Altera Stratix IV Field Programmable Gate Arrays (FPGAs) interconnected by a high speed transceiver mesh. Each FPGA is connected to two DDR3 memory modules and three external 10Gbps ports. In addition, a total of 128 low voltage differential input lines permit connection to external ADC cards. The DSP capability of the board exceeds 644E9 complex multiply-accumulate operations per second. The first production run of eight boards was distributed to partners in The Netherlands, France, Italy, UK, China and Korea in May 2011, with a further production runs completed in December 2011 and early 2012. The function of the board is determined by the firmware loaded into its FPGAs. Current applications include beamformers, correlators, digital receivers, RFI mitigation for pulsar astronomy, and pulsar gating and search machines The new UniBoard based correlator for the European VLBI network (EVN) uses an FX architecture with half the resources of the board devoted to station based processing: delay and phase correction and channelization, and half to the correlation function. A single UniBoard can process a 64MHz band from 32 stations, 2 polarizations, sampled at 8 bit. Adding more UniBoards can expand the total bandwidth of the correlator. The design is able to process both prerecorded and real time (eVLBI) data.

  17. Study of Photochromic Materials for Use in Optical Signal Processing.

    DTIC Science & Technology

    1987-11-01

    LDFP 07 C6 11. TITLE (kIclude Security Classification) STUDY OF PHOTOCHROMIC MATERIALS FOR USE IN OPZfCAL SIGNAL PROCESSING 12. PERSONAL AUTHOR(S) Dr...the feasibility of using photochromic materials for programmable spatial filters and optical data storage/ applications. Write and erase times...Mercuay Dithizonate 35 V. General Experimental Behavior of Photochromic Materials 39 VI. Kinetics of the Relaxation Reaction 44 VII. Dependence of the

  18. Enhanced Multistatic Active Sonar via Innovative Signal Processing

    DTIC Science & Technology

    2014-09-30

    DATES COVERED (From - To) Oct. 01. 2013-Sept. 30, 2014 4. TITLE AND SUBTITLE Enhanced Multistatic Active Sonar via Innovative Signal Processing 5a...DISTRIBUTION AVAILABILITY STATEMENT Approved for Public Release; Distribution is Unlimited. 13. SUPPLEMENTARY NOTES 14. ABSTRACT Pulsed active sonar ...PAS) and continuous active sonar (CAS) in the presence of strong direct blast are studied for the Doppler-tolerant linear frequency modulation

  19. Benchmarking Microprocessors for High-End Signal Processing

    DTIC Science & Technology

    2005-02-01

    skycomputers.com There are a number of general- purpose microprocessor architectures which, while not designed for high-end signal processing, might...bandwidth of the processors considered, a trivial vector-sum computation was developed . In this simple benchmark, as well as in others, all of the...efficiency of the 970’s L2 cache and automatic pre-fetch engines . The bandwidth falloff between L1 and L2 caches of this processor is quite minor, whereas

  20. Programmable rate modem utilizing digital signal processing techniques

    NASA Technical Reports Server (NTRS)

    Naveh, Arad

    1992-01-01

    The need for a Programmable Rate Digital Satellite Modem capable of supporting both burst and continuous transmission modes with either Binary Phase Shift Keying (BPSK) or Quadrature Phase Shift Keying (QPSK) modulation is discussed. The preferred implementation technique is an all digital one which utilizes as much digital signal processing (DSP) as possible. The design trade-offs in each portion of the modulator and demodulator subsystem are outlined.

  1. Impaired Pain Processing Correlates with Cognitive Impairment in Parkinson's Disease

    PubMed Central

    Okada, Akinori; Nakamura, Tomohiko; Suzuki, Junichiro; Suzuki, Masashi; Hirayama, Masaaki; Katsuno, Masahisa; Sobue, Gen

    2016-01-01

    Objective Pain and cognitive impairment are important clinical features in patients with Parkinson's disease (PD). Although pain processing is associated with the limbic system, which is also closely linked to the cognitive function, the association between pain and cognitive impairment in PD is still not well understood. The aim of the study was to investigate the association between pain processing and cognitive impairment in patients with PD. Methods Forty-three patients with PD and 22 healthy subjects were studied. Pain-related somatosensory evoked potentials (SEPs) were generated using a thin needle electrode to stimulate epidermal Aδ fibers. Cognitive impairment was evaluated using the Mini-Mental State Examination (MMSE), the Frontal Assessment Battery, and Japanese version of the Montreal Cognitive Assessment (MoCA-J), and their correlation with pain-related SEPs was investigated. Results The N1/P1 amplitude was significantly lower in PD patients than the controls. N1/P1 peak-to-peak amplitudes correlated with the MMSE (r=0.66, p<0.001) and MoCA-J scores (r=0.38, p<0.01) in patients with PD. These amplitudes also strongly correlated with the domains of attention and memory in the MMSE (attention, r=0.52, p<0.001; memory, r=0.40, p<0.01) and MoCA-J (attention, r=0.45, p<0.005; memory, r=0.48, p<0.001), but not in control subjects. Conclusion A good correlation was observed between the decreased amplitudes of pain-related SEPs and an impairment of attention and memory in patients with PD. Our results suggest that pathological abnormalities of the pain pathway are significantly linked to cognitive impairment in PD. PMID:27803403

  2. Correlation between BOLD-fMRI and EEG signal changes in response to visual stimulus frequency in humans.

    PubMed

    Singh, Manbir; Kim, Sungheon; Kim, Tae-Seong

    2003-01-01

    The correlation between signals acquired using electroencephalography (EEG) and fMRI was investigated in humans during visual stimulation. Evoked potential EEG and BOLD fMRI data were acquired independently under similar conditions from eight subjects during stimulation by a checkerboard flashed at frequencies ranging from 2-12 Hz. The results indicate highly correlated changes in the strength of the EEG signal averaged over two occipital electrodes and the BOLD signal within the occipital lobe as a function of flash frequency for 7/8 subjects (average linear correlation coefficient of 0.76). Both signals peaked at approximately 8 Hz. For one subject the correlation coefficient was 0.20; the EEG signal peaked at 6 Hz and the BOLD signal peaked at 10 Hz. Overall, the EEG and BOLD signals, each averaged over 40-sec stimulation periods, appear to be coupled linearly during visual stimulation by a flashing checkerboard.

  3. Tracking of electroencephalography signals across brain lobes using motion estimation and cross-correlation

    NASA Astrophysics Data System (ADS)

    Lim, Seng Hooi; Nisar, Humaira; Yap, Vooi Voon; Shim, Seong-O.

    2015-11-01

    Electroencephalography (EEG) is the signal generated by electrical activity in the human brain. EEG topographic maps (topo-maps) give an idea of brain activation. Functional connectivity helps to find functionally integrated relationship between spatially separated brain regions. Brain connectivity can be measured by several methods. The classical methods calculate the coherence and correlation of the signal. We have developed an algorithm to map functional neural connectivity in the brain by using a full search block matching motion estimation algorithm. We have used oddball paradigm to examine the flow of activation across brain lobes for a specific activity. In the first step, the EEG signal is converted into topo-maps. The flow of activation between consecutive frames is tracked using full search block motion estimation, which appears in the form of motion vectors. In the second step, vector median filtering is used to obtain a smooth motion field by removing the unwanted noise. For each topo-map, several activation paths are tracked across various brain lobes. We have also developed correlation activity maps by following the correlation coefficient paths between electrodes. These paths are selected when the correlation coefficient between electrodes is >70%. We have compared the motion estimation path with the correlation coefficient activation maps. The tracked paths obtained by using motion estimation and correlation give very similar results. The inter-subject comparison shows that four out of five subjects tracked path involves all four (occipital, temporal, parietal, frontal) brain lobes for the same stimuli. The intra-subject analysis shows that three out of five subjects show different tracked lobes for different stimuli.

  4. Nonlinear fiber applications for ultrafast all-optical signal processing

    NASA Astrophysics Data System (ADS)

    Kravtsov, Konstantin

    In the present dissertation different aspects of all-optical signal processing, enabled by the use of nonlinear fibers, are studied. In particular, we focus on applications of a novel heavily GeO2-doped (HD) nonlinear fiber, that appears to be superior to many other types of nonlinear fibers because of its high nonlinearity and suitability for the use in nonlinear optical loop mirrors (NOLMs). Different functions, such as all-optical switching, thresholding, and wavelength conversion, are demonstrated with the HD fibers in the NOLM configuration. These basic functions are later used for realization of ultrafast time-domain demultiplexers, clock recovery, detectors of short pulses in stealth communications, and primitive elements for analog computations. Another important technology that benefits from the use of nonlinear fiber-based signal processing is optical code-division multiple access (CDMA). It is shown in both theory and experiment that all-optical thresholding is a unique way of improving existing detection methods for optical CDMA. Also, it is the way of implementation of true asynchronous optical spread-spectrum networks, which allows full realization of optical CDMA potential. Some aspects of quantum signal processing and manipulation of quantum states are also studied in this work. It is shown that propagation and collisions of Thirring solitons lead to a substantial squeezing of quantum states, which may find applications for generation of squeezed light.

  5. Signal Processing Effects for Ultrasonic Guided Wave Scanning of Composites

    SciTech Connect

    Roth, D.J.; Cosgriff, L.M.; Martin, R.E.; Burns, E.A.; Teemer, L.

    2005-04-09

    The goal of this ongoing work is to optimize experimental variables for a guided wave scanning method to obtain the most revealing and accurate images of defect conditions in composite materials. This study focuses on signal processing effects involved in forming guided wave scan images. Signal processing is involved at two basic levels for deriving ultrasonic guided wave scan images. At the primary level, NASA GRC has developed algorithms to extract over 30 parameters from the multimode signal and its power spectral density. At the secondary level, there are many variables for which values must be chosen that affect actual computation of these parameters. In this study, a ceramic matrix composite sample having a delamination is characterized using the ultrasonic guided wave scan method. Energy balance and decay rate parameters of the guided wave at each scan location are calculated to form images. These images are compared with ultrasonic c-scan and thermography images. The effect of the time portion of the waveform processed on image quality is assessed by comparing with images formed using the total waveform acquired.

  6. Advanced signal processing technique for damage detection in steel tubes

    NASA Astrophysics Data System (ADS)

    Amjad, Umar; Yadav, Susheel Kumar; Dao, Cac Minh; Dao, Kiet; Kundu, Tribikram

    2016-04-01

    In recent years, ultrasonic guided waves gained attention for reliable testing and characterization of metals and composites. Guided wave modes are excited and detected by PZT (Lead Zirconate Titanate) transducers either in transmission or reflection mode. In this study guided waves are excited and detected in the transmission mode and the phase change of the propagating wave modes are recorded. In most of the other studies reported in the literature, the change in the received signal strength (amplitude) is investigated with varying degrees of damage while in this study the change in phase is correlated with the extent of damage. Feature extraction techniques are used for extracting phase and time-frequency information. The main advantage of this approach is that the bonding condition between the transducer and the specimen does not affect the phase while it can affect the strength of recorded signal. Therefore, if the specimen is not damaged but the transducer-specimen bonding is deteriorated then the received signal strength is altered but the phase remains same and thus false positive predictions for damage can be avoided.

  7. Low power signal processing electronics for wearable medical devices.

    PubMed

    Casson, Alexander J; Rodriguez-Villegas, Esther

    2010-01-01

    Custom designed microchips, known as Application Specific Integrated Circuits (ASICs), offer the lowest possible power consumption electronics. However, this comes at the cost of a longer, more complex and more costly design process compared to one using generic, off-the-shelf components. Nevertheless, their use is essential in future truly wearable medical devices that must operate for long periods of time from physically small, energy limited batteries. This presentation will demonstrate the state-of-the-art in ASIC technology for providing online signal processing for use in these wearable medical devices.

  8. Signal Processing with Degenrate Four-Wave Mixing.

    DTIC Science & Technology

    1987-03-17

    which mann geometry, the four -wave mixing signal observed limits the process to pulses of 100 ps or less. Note also was due to heating of the metal film... four -wave mixing to produced grating. With pulses 28 ps long. 0.6 ns decay real-time processing is time reversal of an optical wave- times were...34’Continuous backward-wave generation by degenerate four -wave the heating effects which dominated their experiment.miigiopca bes--prLt.-vl. 4p .4--419

  9. Method for measuring radial impurity emission profiles using correlations of line integrated signals

    NASA Astrophysics Data System (ADS)

    Kuldkepp, M.; Brunsell, P. R.; Drake, J.; Menmuir, S.; Rachlew, E.

    2006-04-01

    A method of determining radial impurity emission profiles is outlined. The method uses correlations between line integrated signals and is based on the assumption of cylindrically symmetric fluctuations. Measurements at the reversed field pinch EXTRAP T2R show that emission from impurities expected to be close to the edge is clearly different in raw as well as analyzed data to impurities expected to be more central. Best fitting of experimental data to simulated correlation coefficients yields emission profiles that are remarkably close to emission profiles determined using more conventional techniques. The radial extension of the fluctuations is small enough for the method to be used and bandpass filtered signals indicate that fluctuations below 10kHz are cylindrically symmetric. The novel method is not sensitive to vessel window attenuation or wall reflections and can therefore complement the standard methods in the impurity emission reconstruction procedure.

  10. Influence of probe pressure on the diffuse correlation spectroscopy blood flow signal: extra-cerebral contributions

    PubMed Central

    Mesquita, Rickson C.; Schenkel, Steven S.; Minkoff, David L.; Lu, Xiangping; Favilla, Christopher G.; Vora, Patrick M.; Busch, David R.; Chandra, Malavika; Greenberg, Joel H.; Detre, John A.; Yodh, A. G.

    2013-01-01

    A pilot study explores relative contributions of extra-cerebral (scalp/skull) versus brain (cerebral) tissues to the blood flow index determined by diffuse correlation spectroscopy (DCS). Microvascular DCS flow measurements were made on the head during baseline and breath-holding/hyperventilation tasks, both with and without pressure. Baseline (resting) data enabled estimation of extra-cerebral flow signals and their pressure dependencies. A simple two-component model was used to derive baseline and activated cerebral blood flow (CBF) signals, and the DCS flow indices were also cross-correlated with concurrent Transcranial Doppler Ultrasound (TCD) blood velocity measurements. The study suggests new pressure-dependent experimental paradigms for elucidation of blood flow contributions from extra-cerebral and cerebral tissues. PMID:23847725

  11. Correlated and uncorrelated invisible temporal white noise alters mesopic rod signaling.

    PubMed

    Hathibelagal, Amithavikram R; Feigl, Beatrix; Kremers, Jan; Zele, Andrew J

    2016-03-01

    We determined how rod signaling at mesopic light levels is altered by extrinsic temporal white noise that is correlated or uncorrelated with the activity of one (magnocellular, parvocellular, or koniocellular) postreceptoral pathway. Rod and cone photoreceptor excitations were independently controlled using a four-primary photostimulator. Psychometric (Weibull) functions were measured for incremental rod pulses (50 to 250 ms) in the presence (or absence; control) of perceptually invisible subthreshold extrinsic noise. Uncorrelated (rod) noise facilitates rod detection. Correlated postreceptoral pathway noise produces differential changes in rod detection thresholds and decreases the slope of the psychometric functions. We demonstrate that invisible extrinsic noise changes rod-signaling characteristics within the three retinogeniculate pathways at mesopic illumination depending on the temporal profile of the rod stimulus and the extrinsic noise type.

  12. Innovative surface NMR signal processing to significantly improve data quality

    NASA Astrophysics Data System (ADS)

    Neyer, F. M.; Hertrich, M.; Greenhalgh, S. A.

    2010-12-01

    Surface Nuclear Magnetic Resonance (SNMR) is a relatively new geophysical technique primarily used for water detection in the shallow subsurface. Magnetic fields arising from current pulses in a surface loop antenna penetrate the subsurface and interact with the hydrogen protons of liquid water. Among the various geophysical methods, surface NMR is unique in that it is directly sensitive to water molecules. Hence it has the powerful potential to quantitatively map the water distribution with depth. The signal measurement relies on the principle of induction that creates a weak voltage in the range of nV to a few μV in the surface receiver loop. However, the record is obscured by (i) man-made, industrial, and cultural (harmonic) noise such as power-lines and railway tracks, (ii) spike events (incoherent noise), and (iii) atmospheric background noise (random). Extreme hardware requirements and the weakness of the signal cause the records to be heavily noise contaminated in general. As a consequence, efficient noise suppression techniques are required to extract the weak surface NMR signal, i.e. stacking, loop design, and digital post-processing. In this study, we present a state-of-the-art workflow for full time series NMR data processing. As a first step, random spike events are removed from all records. Reference channels are further used to create a shaping filter by which the noise component in signal record is largely reduced. In the latter stage, signal extraction is performed using digital quadrature detection with an additional phase correction. The filter design is based on a least-squares approach using different input channels. This multi-dimensional Wiener filter method allows for a multi-channel noise reduction. Today, state-of-the-art full bandwidth multi-channel recording systems offer the possibility to record four channels simultaneously. Therefore, it is possible to use up to three reference channels for noise attenuation. By analyzing the optimal

  13. Identification and Classification of OFDM Based Signals Using Preamble Correlation and Cyclostationary Feature Extraction

    DTIC Science & Technology

    2009-09-01

    rapidly advancing technologies of wireless communication networks are providing enormous opportunities. A large number of users in emerging markets ...base element of the 802.16 frame is the physical slot, having the duration 4ps s t f  (2.10) where sf is the sampling frequency. The number of ...CLASSIFICATION OF OFDM BASED SIGNALS USING PREAMBLE CORRELATION AND CYCLOSTATIONARY FEATURE EXTRACTION by Steven R. Schnur September 2009

  14. A Signal Processing Analysis of Purkinje Cells in vitro

    PubMed Central

    Abrams, Ze'ev R.; Warrier, Ajithkumar; Trauner, Dirk; Zhang, Xiang

    2010-01-01

    Cerebellar Purkinje cells in vitro fire recurrent sequences of Sodium and Calcium spikes. Here, we analyze the Purkinje cell using harmonic analysis, and our experiments reveal that its output signal is comprised of three distinct frequency bands, which are combined using Amplitude and Frequency Modulation (AM/FM). We find that the three characteristic frequencies – Sodium, Calcium and Switching – occur in various combinations in all waveforms observed using whole-cell current clamp recordings. We found that the Calcium frequency can display a frequency doubling of its frequency mode, and the Switching frequency can act as a possible generator of pauses that are typically seen in Purkinje output recordings. Using a reversibly photo-switchable kainate receptor agonist, we demonstrate the external modulation of the Calcium and Switching frequencies. These experiments and Fourier analysis suggest that the Purkinje cell can be understood as a harmonic signal oscillator, enabling a higher level of interpretation of Purkinje signaling based on modern signal processing techniques. PMID:20508748

  15. Stochastic simulation of spatially correlated geo-processes

    USGS Publications Warehouse

    Christakos, G.

    1987-01-01

    In this study, developments in the theory of stochastic simulation are discussed. The unifying element is the notion of Radon projection in Euclidean spaces. This notion provides a natural way of reconstructing the real process from a corresponding process observable on a reduced dimensionality space, where analysis is theoretically easier and computationally tractable. Within this framework, the concept of space transformation is defined and several of its properties, which are of significant importance within the context of spatially correlated processes, are explored. The turning bands operator is shown to follow from this. This strengthens considerably the theoretical background of the geostatistical method of simulation, and some new results are obtained in both the space and frequency domains. The inverse problem is solved generally and the applicability of the method is extended to anisotropic as well as integrated processes. Some ill-posed problems of the inverse operator are discussed. Effects of the measurement error and impulses at origin are examined. Important features of the simulated process as described by geomechanical laws, the morphology of the deposit, etc., may be incorporated in the analysis. The simulation may become a model-dependent procedure and this, in turn, may provide numerical solutions to spatial-temporal geologic models. Because the spatial simu??lation may be technically reduced to unidimensional simulations, various techniques of generating one-dimensional realizations are reviewed. To link theory and practice, an example is computed in detail. ?? 1987 International Association for Mathematical Geology.

  16. Fiber-Optic Delay Line Signal Processing: Coherent and Incoherent Systems.

    NASA Astrophysics Data System (ADS)

    Jackson, Kenneth Paul

    Single-mode optical fiber is an attractive delay line medium due to its extremely low-loss (fractional dB/km) and large modulation bandwidth ((GREATERTHEQ)100 GHz(.)km). By connecting lengths of single-mode fiber in prescribed ways, two basic delay line devices can be constructed: the tapped delay line and the recirculating delay line.These two devices form the basis of fiber-optic delay line signal processing in which a variety of operations can be performed. The operations include coded sequence generation, convolution, correlation, matrix-vector multiplication, frequency filtering and many other operations based on delay line concepts. Because of the unique characteristics of single-mode fiber (low -loss and large modulation bandwidth), these operations can be performed at speeds far higher than those that are possible with more conventional signal processing techniques such as surface acoustic wave or charge-coupled devices. Fiber delay line devices can be operated either coherently or incoherently. If incoherent, the device discards optical phase whereas if coherent, the device retains phase. Coherent and incoherent fiber delay line processors each have advantages depending on the application. The goal of this work has been to demonstrate the feasibility of single-mode fibers for delay line signal processing. This goal was achieved through the development of several delay line devices capable of providing elementary processing functions. The work described here develops and analyzes the basic concepts of fiber-optic delay line signal processing with both coherent and incoherent systems. Prototype devices are presented that demonstrate simple processing capabilities. Presently, the processing speed of these fiber -optic devices is limited by the electro-optic interfaces (i.e. sources, modulators and detectors). However, with recent developments in high-speed sources, modulators and detectors, the possibility of performing real time signal processing operations

  17. Adaptive Signal Processing Testbed application software: User's manual

    NASA Astrophysics Data System (ADS)

    Parliament, Hugh A.

    1992-05-01

    The Adaptive Signal Processing Testbed (ASPT) application software is a set of programs that provide general data acquisition and minimal processing functions on live digital data. The data are obtained from a digital input interface whose data source is the DAR4000 digital quadrature receiver that receives a phase shift keying signal at 21.4 MHz intermediate frequency. The data acquisition software is used to acquire raw unprocessed data from the DAR4000 and store it on disk in the Sun workstation based ASPT. File processing utilities are available to convert the stored files for analysis. The data evaluation software is used for the following functions: acquisition of data from the DAR4000, conversion to IEEE format, and storage to disk; acquisition of data from the DAR4000, power spectrum estimation, and on-line plotting on the graphics screen; and processing of disk file data, power spectrum estimation, and display and/or storage to disk in the new format. A user's guide is provided that describes the acquisition and evaluation programs along with how to acquire, evaluate, and use the data.

  18. Biophoton signal transmission and processing in the brain.

    PubMed

    Tang, Rendong; Dai, Jiapei

    2014-10-05

    The transmission and processing of neural information in the nervous system plays a key role in neural functions. It is well accepted that neural communication is mediated by bioelectricity and chemical molecules via the processes called bioelectrical and chemical transmission, respectively. Indeed, the traditional theories seem to give valuable explanations for the basic functions of the nervous system, but difficult to construct general accepted concepts or principles to provide reasonable explanations of higher brain functions and mental activities, such as perception, learning and memory, emotion and consciousness. Therefore, many unanswered questions and debates over the neural encoding and mechanisms of neuronal networks remain. Cell to cell communication by biophotons, also called ultra-weak photon emissions, has been demonstrated in several plants, bacteria and certain animal cells. Recently, both experimental evidence and theoretical speculation have suggested that biophotons may play a potential role in neural signal transmission and processing, contributing to the understanding of the high functions of nervous system. In this paper, we review the relevant experimental findings and discuss the possible underlying mechanisms of biophoton signal transmission and processing in the nervous system.

  19. Predicting protein subcellular location using digital signal processing.

    PubMed

    Pan, Yu-Xi; Li, Da-Wei; Duan, Yun; Zhang, Zhi-Zhou; Xu, Ming-Qing; Feng, Guo-Yin; He, Lin

    2005-02-01

    The biological functions of a protein are closely related to its attributes in a cell. With the rapid accumulation of newly found protein sequence data in databanks, it is highly desirable to develop an automated method for predicting the subcellular location of proteins. The establishment of such a predictor will expedite the functional determination of newly found proteins and the process of prioritizing genes and proteins identified by genomic efforts as potential molecular targets for drug design. The traditional algorithms for predicting these attributes were based solely on amino acid composition in which no sequence order effect was taken into account. To improve the prediction quality, it is necessary to incorporate such an effect. However, the number of possible patterns in protein sequences is extremely large, posing a formidable difficulty for realizing this goal. To deal with such difficulty, a well-developed tool in digital signal processing named digital Fourier transform (DFT) [1] was introduced. After being translated to a digital signal according to the hydrophobicity of each amino acid, a protein was analyzed by DFT within the frequency domain. A set of frequency spectrum parameters, thus obtained, were regarded as the factors to represent the sequence order effect. A significant improvement in prediction quality was observed by incorporating the frequency spectrum parameters with the conventional amino acid composition. One of the crucial merits of this approach is that many existing tools in mathematics and engineering can be easily applied in the predicting process. It is anticipated that digital signal processing may serve as a useful vehicle for many other protein science areas.

  20. Generation and processing of peripheral temperature signals in mammals

    NASA Astrophysics Data System (ADS)

    Pierau, Fr.-K.; Wurster, R. D.; Neya, T.; Yamasato, T.; Ulrich, J.

    1980-09-01

    Temperature transduction in peripheral cold receptors and processing of peripheral temperature signals in the spinal cord were studied in cats and rats. The temperature dependence of the generator potential is attributed to different temperature coefficients of an electrogenic Na-efflux and the passive Na-influx. Cold receptor activity and particularly its bursting pattern is considerably modulated by the local Ca-concentration, but the effect of elevated Ca-concentration is abolished by the ATPase blocker ouabain. — The peripheral temperature signals from the scrotal skin of rats are transformed in dorsal horn neurones (DHN) into temperature reactions, which occur only above (warm reaction) or below (cold reaction) a certain temperature threshold and are limited to an operational range of 1 4°C. Convergency of different temperature inputs were observed in one and the same DHN. Supraspinal control of temperature reactive DHN appears to be complex but predominantly excitatory.

  1. Information processing and signal integration in bacterial quorum sensing

    NASA Astrophysics Data System (ADS)

    Mehta, Pankaj

    2009-03-01

    Bacteria communicate with each other using secreted chemical signaling molecules called autoinducers (AIs) in a process known as quorum sensing. Quorum sensing enables bacteria to collectively regulate their behavior depending on the number and/or species of bacteria present. The quorum-sensing network of the marine-bacteria Vibrio harveyi consists of three AIs encoding distinct ecological information, each detected by its own histidine-kinase sensor protein. The sensor proteins all phosphorylate a common response regulator and transmit sensory information through a shared phosphorelay that regulates expression of downstream quorum-sensing genes. Despite detailed knowledge of the Vibrio quorum-sensing circuit, it is still unclear how and why bacteria integrate information from multiple input signals to coordinate collective behaviors. Here we develop a mathematical framework for analyzing signal integration based on Information Theory and use it to show that bacteria must tune the kinase activities of sensor proteins in order to transmit information from multiple inputs. This is demonstrated within a quantitative model that allows us to quantify how much Vibrio's learn about individual inputs and explains experimentally measured input-output relations. Furthermore, we predicted and experimentally verified that bacteria manipulate the production rates of AIs in order to increase information transmission and argue that the quorum-sensing circuit is designed to coordinate a multi-cellular developmental program. Our results show that bacteria can successfully learn about multiple signals even when they are transmitted through a shared pathway and suggest that Information Theory may be a powerful tool for analyzing biological signaling networks.

  2. Detecting a stochastic background of gravitational radiation: Signal processing strategies and sensitivities

    NASA Astrophysics Data System (ADS)

    Allen, Bruce; Romano, Joseph D.

    1999-05-01

    We analyze the signal processing required for the optimal detection of a stochastic background of gravitational radiation using laser interferometric detectors. Starting with basic assumptions about the statistical properties of a stochastic gravity-wave background, we derive expressions for the optimal filter function and signal-to-noise ratio for the cross-correlation of the outputs of two gravity-wave detectors. Sensitivity levels required for detection are then calculated. Issues related to (i) calculating the signal-to-noise ratio for arbitrarily large stochastic backgrounds, (ii) performing the data analysis in the presence of nonstationary detector noise, (iii) combining data from multiple detector pairs to increase the sensitivity of a stochastic background search, (iv) correlating the outputs of 4 or more detectors, and (v) allowing for the possibility of correlated noise in the outputs of two detectors are discussed. We briefly describe a computer simulation that was used to ``experimentally'' verify the theoretical calculations derived in the paper, and which mimics the generation and detection of a simulated stochastic gravity-wave signal in the presence of simulated detector noise. Numerous graphs and tables of numerical data for the five major interferometers (LIGO-WA, LIGO-LA, VIRGO, GEO-600, and TAMA-300) are also given. This information consists of graphs of the noise power spectra, overlap reduction functions, and optimal filter functions; also included are tables of the signal-to-noise ratios and sensitivity levels for cross-correlation measurements between different detector pairs. The treatment given in this paper should be accessible to both theorists involved in data analysis and experimentalists involved in detector design and data acquisition.

  3. Dysphagia Screening: Contributions of Cervical Auscultation Signals and Modern Signal-Processing Techniques

    PubMed Central

    Dudik, Joshua M.; Coyle, James L.

    2015-01-01

    Cervical auscultation is the recording of sounds and vibrations caused by the human body from the throat during swallowing. While traditionally done by a trained clinician with a stethoscope, much work has been put towards developing more sensitive and clinically useful methods to characterize the data obtained with this technique. The eventual goal of the field is to improve the effectiveness of screening algorithms designed to predict the risk that swallowing disorders pose to individual patients’ health and safety. This paper provides an overview of these signal processing techniques and summarizes recent advances made with digital transducers in hopes of organizing the highly varied research on cervical auscultation. It investigates where on the body these transducers are placed in order to record a signal as well as the collection of analog and digital filtering techniques used to further improve the signal quality. It also presents the wide array of methods and features used to characterize these signals, ranging from simply counting the number of swallows that occur over a period of time to calculating various descriptive features in the time, frequency, and phase space domains. Finally, this paper presents the algorithms that have been used to classify this data into ‘normal’ and ‘abnormal’ categories. Both linear as well as non-linear techniques are presented in this regard. PMID:26213659

  4. Dysphagia Screening: Contributions of Cervical Auscultation Signals and Modern Signal-Processing Techniques.

    PubMed

    Dudik, Joshua M; Coyle, James L; Sejdić, Ervin

    2015-08-01

    Cervical auscultation is the recording of sounds and vibrations caused by the human body from the throat during swallowing. While traditionally done by a trained clinician with a stethoscope, much work has been put towards developing more sensitive and clinically useful methods to characterize the data obtained with this technique. The eventual goal of the field is to improve the effectiveness of screening algorithms designed to predict the risk that swallowing disorders pose to individual patients' health and safety. This paper provides an overview of these signal processing techniques and summarizes recent advances made with digital transducers in hopes of organizing the highly varied research on cervical auscultation. It investigates where on the body these transducers are placed in order to record a signal as well as the collection of analog and digital filtering techniques used to further improve the signal quality. It also presents the wide array of methods and features used to characterize these signals, ranging from simply counting the number of swallows that occur over a period of time to calculating various descriptive features in the time, frequency, and phase space domains. Finally, this paper presents the algorithms that have been used to classify this data into 'normal' and 'abnormal' categories. Both linear as well as non-linear techniques are presented in this regard.

  5. Coherent detection and digital signal processing for fiber optic communications

    NASA Astrophysics Data System (ADS)

    Ip, Ezra

    The drive towards higher spectral efficiency in optical fiber systems has generated renewed interest in coherent detection. We review different detection methods, including noncoherent, differentially coherent, and coherent detection, as well as hybrid detection methods. We compare the modulation methods that are enabled and their respective performances in a linear regime. An important system parameter is the number of degrees of freedom (DOF) utilized in transmission. Polarization-multiplexed quadrature-amplitude modulation maximizes spectral efficiency and power efficiency as it uses all four available DOF contained in the two field quadratures in the two polarizations. Dual-polarization homodyne or heterodyne downconversion are linear processes that can fully recover the received signal field in these four DOF. When downconverted signals are sampled at the Nyquist rate, compensation of transmission impairments can be performed using digital signal processing (DSP). Software based receivers benefit from the robustness of DSP, flexibility in design, and ease of adaptation to time-varying channels. Linear impairments, including chromatic dispersion (CD) and polarization-mode dispersion (PMD), can be compensated quasi-exactly using finite impulse response filters. In practical systems, sampling the received signal at 3/2 times the symbol rate is sufficient to enable an arbitrary amount of CD and PMD to be compensated for a sufficiently long equalizer whose tap length scales linearly with transmission distance. Depending on the transmitted constellation and the target bit error rate, the analog-to-digital converter (ADC) should have around 5 to 6 bits of resolution. Digital coherent receivers are naturally suited for the implementation of feedforward carrier recovery, which has superior linewidth tolerance than phase-locked loops, and does not suffer from feedback delay constraints. Differential bit encoding can be used to prevent catastrophic receiver failure due

  6. [A modified speech enhancement algorithm for electronic cochlear implant and its digital signal processing realization].

    PubMed

    Wang, Yulin; Tian, Xuelong

    2014-08-01

    In order to improve the speech quality and auditory perceptiveness of electronic cochlear implant under strong noise background, a speech enhancement system used for electronic cochlear implant front-end was constructed. Taking digital signal processing (DSP) as the core, the system combines its multi-channel buffered serial port (McBSP) data transmission channel with extended audio interface chip TLV320AIC10, so speech signal acquisition and output with high speed are realized. Meanwhile, due to the traditional speech enhancement method which has the problems as bad adaptability, slow convergence speed and big steady-state error, versiera function and de-correlation principle were used to improve the existing adaptive filtering algorithm, which effectively enhanced the quality of voice communications. Test results verified the stability of the system and the de-noising performance of the algorithm, and it also proved that they could provide clearer speech signals for the deaf or tinnitus patients.

  7. Angiogenic and signalling proteins correlate with sensitivity to sequential treatment in renal cell cancer

    PubMed Central

    Rosa, R; Damiano, V; Nappi, L; Formisano, L; Massari, F; Scarpa, A; Martignoni, G; Bianco, R; Tortora, G

    2013-01-01

    Background: We aimed to study key signalling proteins involved in angiogenesis and proliferation on the response to inhibitors of tyrosine kinases and mammalian target of rapamycin in first- and in second-line treatment of renal cell carcinoma (RCC). Methods: In a panel of human RCC tumours, in vitro and in nude mice, we evaluated the effect of sunitinib, sorafenib and everolimus, alone and in sequence, on tumour growth and expression of signalling proteins involved in proliferation and resistance to treatment. Results: We demonstrated that, as single agents, sunitinib, sorafenib and everolimus share similar activity in inhibiting cell proliferation, signal transduction and vascular endothelial growth factor (VEGF) secretion in different RCC models, both in vitro and in tumour xenografts. Pre-treatment with sunitinib reduced the response to subsequent sunitinib and sorafenib but not to everolimus. Inability by sunitinib to persistently inhibit HIF-1, VEGF and pMAPK anticipated treatment resistance in xenografted tumours. After first-line sunitinib, second-line treatment with everolimus was more effective than either sorafenib or rechallenge with sunitinib in interfering with signalling proteins, VEGF and interleukin-8, translating into a significant advantage in tumour growth inhibition and mice survival. Conclusion: We demonstrated that a panel of angiogenic and signalling proteins can correlate with the onset of resistance to sunitinib and the activity of everolimus in second line. PMID:23839492

  8. Correlation technique for the compensation of diffraction widening of optical reference signals.

    PubMed

    Sáez-Landete, José; Alonso, José; Sanchez-Brea, Luis Miguel; Morlanes, Tomás; Bernabeu, Eusebio

    2009-09-01

    Two-grating measurement systems are routinely employed for high-resolution measurements of angular and linear displacement. Usually, these systems incorporate zero reference codes (ZRCs) to obtain a zero reference signal (ZRS), which is used as a stage-homing signal. This signal provides absolute information of the position to the otherwise relative information provided by the two-grating incremental subsystems. A zero reference signal is commonly obtained illuminating the superposition of two identical pseudorandom codes and registering the transmitted light by means of a photodiode. To increase the resolution of the system, a reduction of the grating period and the ZRC widths is required. Due to this reduction, the diffractive effects produce a widening of the ZRS and, in turn, a loss of the measuring accuracy. In this work, we propose a method to narrow the distorted signal obtained with a Lau-based encoder, reinstating the accuracy of the ZRS. The method consists of the inclusion of a correlation mask on the detector. A theoretical model to design the mask has been developed, and experimental results have been obtained that validate the proposed technique.

  9. Linear correlation between fractal dimension of EEG signal and handgrip force.

    PubMed

    Liu, J Z; Yang, Q; Yao, B; Brown, R W; Yue, G H

    2005-08-01

    Fractal dimension (FD) has been proved useful in quantifying the complexity of dynamical signals in biology and medicine. In this study, we measured FDs of human electroencephalographic (EEG) signals at different levels of handgrip forces. EEG signals were recorded from five major motor-related cortical areas in eight normal healthy subjects. FDs were calculated using three different methods. The three physiological periods of handgrip (command preparation, movement and holding periods) were analyzed and compared. The results showed that FDs of the EEG signals during the movement and holding periods increased linearly with handgrip force, whereas FD during the preparation period had no correlation with force. The results also demonstrated that one method (Katz's) gave greater changes in FD, and thus, had more power in capturing the dynamic changes in the signal. The linear increase of FD, together with results from other EEG and neuroimaging studies, suggest that under normal conditions the brain recruits motor neurons at a linear progress when increasing the force.

  10. Bunyamwera orthobunyavirus glycoprotein precursor is processed by cellular signal peptidase and signal peptide peptidase

    PubMed Central

    Shi, Xiaohong; Botting, Catherine H.; Li, Ping; Niglas, Mark; Brennan, Benjamin; Shirran, Sally L.; Szemiel, Agnieszka M.; Elliott, Richard M.

    2016-01-01

    The M genome segment of Bunyamwera virus (BUNV)—the prototype of both the Bunyaviridae family and the Orthobunyavirus genus—encodes the glycoprotein precursor (GPC) that is proteolytically cleaved to yield two viral structural glycoproteins, Gn and Gc, and a nonstructural protein, NSm. The cleavage mechanism of orthobunyavirus GPCs and the host proteases involved have not been clarified. In this study, we investigated the processing of BUNV GPC and found that both NSm and Gc proteins were cleaved at their own internal signal peptides (SPs), in which NSm domain I functions as SPNSm and NSm domain V as SPGc. Moreover, the domain I was further processed by a host intramembrane-cleaving protease, signal peptide peptidase, and is required for cell fusion activities. Meanwhile, the NSm domain V (SPGc) remains integral to NSm, rendering the NSm topology as a two-membrane-spanning integral membrane protein. We defined the cleavage sites and boundaries between the processed proteins as follows: Gn, from residue 17–312 or nearby residues; NSm, 332–477; and Gc, 478–1433. Our data clarified the mechanism of the precursor cleavage process, which is important for our understanding of viral glycoprotein biogenesis in the genus Orthobunyavirus and thus presents a useful target for intervention strategies. PMID:27439867

  11. Use of fuzzy logic in signal processing and validation

    SciTech Connect

    Heger, A.S.; Alang-Rashid, N.K. ); Holbert, K.E. )

    1993-01-01

    The advent of fuzzy logic technology has afforded another opportunity to reexamine the signal processing and validation process (SPV). The features offered by fuzzy logic can lend themselves to a more reliable and perhaps fault-tolerant approach to SPV. This is particularly attractive to complex system operations, where optimal control for safe operation depends on reliable input data. The reason for the use of fuzzy logic as the tool for SPV is its ability to transform information from the linguistic domain to a mathematical domain for processing and then transformation of its result back into the linguistic domain for presentation. To ensure the safe and optimal operation of a nuclear plant, for example, reliable and valid data must be available to the human and computer operators. Based on these input data, the operators determine the current state of the power plant and project corrective actions for future states. This determination is based on available data and the conceptual and mathematical models for the plant. A fault-tolerant SPV based on fuzzy logic can help the operators meet the objective of effective, efficient, and safe operation of the nuclear power plant. The ultimate product of this project will be a code that will assist plant operators in making informed decisions under uncertain conditions when conflicting signals may be present.

  12. Living ordered neural networks as model systems for signal processing

    NASA Astrophysics Data System (ADS)

    Villard, C.; Amblard, P. O.; Becq, G.; Gory-Fauré, S.; Brocard, J.; Roth, S.

    2007-06-01

    Neural circuit architecture is a fundamental characteristic of the brain, and how architecture is bound to biological functions is still an open question. Some neuronal geometries seen in the retina or the cochlea are intriguing: information is processed in parallel by several entities like in "pooling" networks which have recently drawn the attention of signal processing scientists. These systems indeed exhibit the noise-enhanced processing effect, which is also actively discussed in the neuroscience community at the neuron scale. The aim of our project is to use in-vitro ordered neuron networks as living paradigms to test ideas coming from the computational science. The different technological bolts that have to be solved are enumerated and the first results are presented. A neuron is a polarised cell, with an excitatory axon and a receiving dendritic tree. We present how soma confinement and axon differentiation can be induced by surface functionalization techniques. The recording of large neuron networks, ordered or not, is also detailed and biological signals shown. The main difficulty to access neural noise in the case of weakly connected networks grown on micro electrode arrays is explained. This open the door to a new detection technology suitable for sub-cellular analysis and stimulation, whose development will constitute the next step of this project.

  13. 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.

  14. Cramer-Rao Bound for Gaussian Random Processes and Applications to Radar Processing of Atmospheric Signals

    NASA Technical Reports Server (NTRS)

    Frehlich, Rod

    1993-01-01

    Calculations of the exact Cramer-Rao Bound (CRB) for unbiased estimates of the mean frequency, signal power, and spectral width of Doppler radar/lidar signals (a Gaussian random process) are presented. Approximate CRB's are derived using the Discrete Fourier Transform (DFT). These approximate results are equal to the exact CRB when the DFT coefficients are mutually uncorrelated. Previous high SNR limits for CRB's are shown to be inaccurate because the discrete summations cannot be approximated with integration. The performance of an approximate maximum likelihood estimator for mean frequency approaches the exact CRB for moderate signal to noise ratio and moderate spectral width.

  15. Signal Processing System for the CASA Integrated Project I Radars

    SciTech Connect

    Bharadwaj, Nitin; Chandrasekar, V.; Junyent, Francesc

    2010-09-01

    This paper describes the waveform design space and signal processing system for dual-polarization Doppler weather radar operating at X band. The performance of the waveforms is presented with ground clutter suppression capability and mitigation of range velocity ambiguity. The operational waveform is designed based on operational requirements and system/hardware requirements. A dual Pulse Repetition Frequency (PRF) waveform was developed and implemented for the first generation X-band radars deployed by the Center for Collaborative Adaptive Sensing of the Atmosphere (CASA). This paper presents an evaluation of the performance of the waveforms based on simulations and data collected by the first-generation CASA radars during operations.

  16. Digital Methods of the Optimum Processing of Radar Signals,

    DTIC Science & Technology

    1985-02-07

    Transliteration System ......................... ii *Preface ..................................................... 0................... 3 Chapter 1. Command of...Troops and the Tasks of Processing Radar Signals,........7 *Chapter 2. Arithmetic Operations with the Binary Numbers ...................... 16 Chapter 3 ...kh -%V Zh, zh Q LtaL Ts, ts 3 3 j Z, z H 4. i Ch, ch M A# M,9 b b HNHnH X N, nE, e 0 o 0 0 0,P0 hji 10 1 Yu, yu n fn 17 it P, p A R jr Ya, ya *ye

  17. Photonics for microwave systems and ultra-wideband signal processing

    NASA Astrophysics Data System (ADS)

    Ng, W.

    2016-08-01

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

  18. Signal processing for an optical wide band data transmission system

    NASA Astrophysics Data System (ADS)

    Nakamura, M.; Leskovar, B.; Turko, B. T.

    1987-07-01

    The signal processing for an optical wide band transmission system using gallium arsenide (GaAs) digital integrated circuits and optical fibers has been investigated. Multiplexing, coding, synchronization, demultiplexing, and error checking at 780 Mbit/s data rates are described. Data storage in memory for linking to a computer is also considered. The design uses available GaAs and silicon components. The reliability of GaAs components is discussed as well as the layout and thermal considerations required for a high speed system.

  19. DSPSR: Digital Signal Processing Software for Pulsar Astronomy

    NASA Astrophysics Data System (ADS)

    van Straten, W.; Bailes, M.

    2010-10-01

    DSPSR, written primarily in C++, is an open-source, object-oriented, digital signal processing software library and application suite for use in radio pulsar astronomy. The library implements an extensive range of modular algorithms for use in coherent dedispersion, filterbank formation, pulse folding, and other tasks. The software is installed and compiled using the standard GNU configure and make system, and is able to read astronomical data in 18 different file formats, including FITS, S2, CPSR, CPSR2, PuMa, PuMa2, WAPP, ASP, and Mark5.

  20. High-Speed Digital Signal Processing Method for Detection of Repeating Earthquakes Using GPGPU-Acceleration

    NASA Astrophysics Data System (ADS)

    Kawakami, Taiki; Okubo, Kan; Uchida, Naoki; Takeuchi, Nobunao; Matsuzawa, Toru

    2013-04-01

    Repeating earthquakes are occurring on the similar asperity at the plate boundary. These earthquakes have an important property; the seismic waveforms observed at the identical observation site are very similar regardless of their occurrence time. The slip histories of repeating earthquakes could reveal the existence of asperities: The Analysis of repeating earthquakes can detect the characteristics of the asperities and realize the temporal and spatial monitoring of the slip in the plate boundary. Moreover, we are expecting the medium-term predictions of earthquake at the plate boundary by means of analysis of repeating earthquakes. Although the previous works mostly clarified the existence of asperity and repeating earthquake, and relationship between asperity and quasi-static slip area, the stable and robust method for automatic detection of repeating earthquakes has not been established yet. Furthermore, in order to process the enormous data (so-called big data) the speedup of the signal processing is an important issue. Recently, GPU (Graphic Processing Unit) is used as an acceleration tool for the signal processing in various study fields. This movement is called GPGPU (General Purpose computing on GPUs). In the last few years the performance of GPU keeps on improving rapidly. That is, a PC (personal computer) with GPUs might be a personal supercomputer. GPU computing gives us the high-performance computing environment at a lower cost than before. Therefore, the use of GPUs contributes to a significant reduction of the execution time in signal processing of the huge seismic data. In this study, first, we applied the band-limited Fourier phase correlation as a fast method of detecting repeating earthquake. This method utilizes only band-limited phase information and yields the correlation values between two seismic signals. Secondly, we employ coherence function using three orthogonal components (East-West, North-South, and Up-Down) of seismic data as a

  1. Social signal processing for studying parent-infant interaction.

    PubMed

    Avril, Marie; Leclère, Chloë; Viaux, Sylvie; Michelet, Stéphane; Achard, Catherine; Missonnier, Sylvain; Keren, Miri; Cohen, David; Chetouani, Mohamed

    2014-01-01

    Studying early interactions is a core issue of infant development and psychopathology. Automatic social signal processing theoretically offers the possibility to extract and analyze communication by taking an integrative perspective, considering the multimodal nature and dynamics of behaviors (including synchrony). This paper proposes an explorative method to acquire and extract relevant social signals from a naturalistic early parent-infant interaction. An experimental setup is proposed based on both clinical and technical requirements. We extracted various cues from body postures and speech productions of partners using the IMI2S (Interaction, Multimodal Integration, and Social Signal) Framework. Preliminary clinical and computational results are reported for two dyads (one pathological in a situation of severe emotional neglect and one normal control) as an illustration of our cross-disciplinary protocol. The results from both clinical and computational analyzes highlight similar differences: the pathological dyad shows dyssynchronic interaction led by the infant whereas the control dyad shows synchronic interaction and a smooth interactive dialog. The results suggest that the current method might be promising for future studies.

  2. Social signal processing for studying parent–infant interaction

    PubMed Central

    Avril, Marie; Leclère, Chloë; Viaux, Sylvie; Michelet, Stéphane; Achard, Catherine; Missonnier, Sylvain; Keren, Miri; Cohen, David; Chetouani, Mohamed

    2014-01-01

    Studying early interactions is a core issue of infant development and psychopathology. Automatic social signal processing theoretically offers the possibility to extract and analyze communication by taking an integrative perspective, considering the multimodal nature and dynamics of behaviors (including synchrony). This paper proposes an explorative method to acquire and extract relevant social signals from a naturalistic early parent–infant interaction. An experimental setup is proposed based on both clinical and technical requirements. We extracted various cues from body postures and speech productions of partners using the IMI2S (Interaction, Multimodal Integration, and Social Signal) Framework. Preliminary clinical and computational results are reported for two dyads (one pathological in a situation of severe emotional neglect and one normal control) as an illustration of our cross-disciplinary protocol. The results from both clinical and computational analyzes highlight similar differences: the pathological dyad shows dyssynchronic interaction led by the infant whereas the control dyad shows synchronic interaction and a smooth interactive dialog. The results suggest that the current method might be promising for future studies. PMID:25540633

  3. Processing events: behavioral and neuromagnetic correlates of Aspectual Coercion.

    PubMed

    Brennan, Jonathan; Pylkkänen, Liina

    2008-08-01

    Much recent psycho- and neuro-linguistic work has aimed to elucidate the mechanisms by which sentence meanings are composed by investigating the processing of semantic mismatch. One controversial case for theories of semantic composition is expressions such as the clown jumped for ten minutes, in which the aspectual properties of a punctual verb clash with those of a durative modifier. Such sentences have been proposed to involve a coercion operation which shifts the punctual meaning of the verb to an iterative one. However, processing studies addressing this hypothesis have yielded mixed results. In this study, we tested four hypotheses of how aspectual mismatch is resolved with self-paced reading and magnetoencephalography. Using a set of verbs normed for punctuality, we identified an immediate behavioral cost of mismatch. The neural correlates of this processing were found to match effects in midline prefrontal regions previously implicated in the resolution of complement coercion. We also identified earlier effects in right-lateral frontal and temporal sites. We suggest that of the representational hypotheses currently in the literature, these data are most consistent with an account where aspectual mismatch initially involves the composition of an anomalous meaning that is later repaired via coercion.

  4. The Accuratre Signal Model and Imaging Processing in Geosynchronous SAR

    NASA Astrophysics Data System (ADS)

    Hu, Cheng

    With the development of synthetic aperture radar (SAR) application, the disadvantage of low earth orbit (LEO) SAR becomes more and more apparent. The increase of orbit altitude can shorten the revisit time and enlarge the coverage area in single look, and then satisfy the application requirement. The concept of geosynchronous earth orbit (GEO) SAR system is firstly presented and deeply discussed by K.Tomiyasi and other researchers. A GEO SAR, with its fine temporal resolution, would overcome the limitations of current imaging systems, allowing dense interpretation of transient phenomena as GPS time-series analysis with a spatial density several orders of magnitude finer. Until now, the related literatures about GEO SAR are mainly focused in the system parameter design and application requirement. As for the signal characteristic, resolution calculation and imaging algorithms, it is nearly blank in the related literatures of GEO SAR. In the LEO SAR, the signal model analysis adopts the `Stop-and-Go' assumption in general, and this assumption can satisfy the imaging requirement in present advanced SAR system, such as TerraSAR, Radarsat2 and so on. However because of long propagation distance and non-negligible earth rotation, the `Stop-and-Go' assumption does not exist and will cause large propagation distance error, and then affect the image formation. Furthermore the long propagation distance will result in the long synthetic aperture time such as hundreds of seconds, therefore the linear trajectory model in LEO SAR imaging will fail in GEO imaging, and the new imaging model needs to be proposed for the GEO SAR imaging processing. In this paper, considering the relative motion between satellite and earth during signal propagation time, the accurate analysis method for propagation slant range is firstly presented. Furthermore, the difference between accurate analysis method and `Stop-and-Go' assumption is analytically obtained. Meanwhile based on the derived

  5. Electrophysiological correlates of emotional processing in sensation seeking.

    PubMed

    Zheng, Ya; Xu, Jing; Jia, Hongning; Tan, Fei; Chang, Yi; Zhou, Li; Shen, Huijuan; Qu, Benqing

    2011-09-01

    Previous studies have consistently reported a relationship between sensation seeking and emotional reactivity. However, little is known about the neural correlates and the time course of emotional processing in sensation seeking. The present study addressed these issues by recording event-related potentials (ERPs) during an emotional oddball task. Valence effect was significant at N2, P3 and LPP whereas arousal effect was significant at P3 and LPP. More importantly, low sensation seekers (LSSs) exhibited an increased emotional N2 whereas high sensation seekers (HSSs) showed an enhanced emotional P3. Furthermore, the arousal effect was similar across the two groups, but the valence effect at N2 stage was significant in LSSs instead of HSSs. These findings suggest that LSSs tend to show a more active general alerting system toward emotional stimuli, particularly for negative stimuli, whereas HSSs tend to display a stronger preference for intense stimulation irrespective of the emotional valence.

  6. Correlation dynamics and enhanced signals for the identification of serial biomolecules and DNA bases

    NASA Astrophysics Data System (ADS)

    Ahmed, Towfiq; Haraldsen, Jason T.; Rehr, John J.; Di Ventra, Massimiliano; Schuller, Ivan; Balatsky, Alexander V.

    2014-03-01

    Nanopore-based sequencing has demonstrated a significant potential for the development of fast, accurate, and cost-efficient fingerprinting techniques for next generation molecular detection and sequencing. We propose a specific multilayered graphene-based nanopore device architecture for the recognition of single biomolecules. Molecular detection and analysis can be accomplished through the detection of transverse currents as the molecule or DNA base translocates through the nanopore. To increase the overall signal-to-noise ratio and the accuracy, we implement a new ‘multi-point cross-correlation’ technique for identification of DNA bases or other molecules on the single molecular level. We demonstrate that the cross-correlations between each nanopore will greatly enhance the transverse current signal for each molecule. We implement first-principles transport calculations for DNA bases surveyed across a multilayered graphene nanopore system to illustrate the advantages of the proposed geometry. A time-series analysis of the cross-correlation functions illustrates the potential of this method for enhancing the signal-to-noise ratio. This work constitutes a significant step forward in facilitating fingerprinting of single biomolecules using solid state technology.

  7. TOPICAL REVIEW: A survey of signal processing algorithms in brain computer interfaces based on electrical brain signals

    NASA Astrophysics Data System (ADS)

    Bashashati, Ali; Fatourechi, Mehrdad; Ward, Rabab K.; Birch, Gary E.

    2007-06-01

    Brain computer interfaces (BCIs) aim at providing a non-muscular channel for sending commands to the external world using the electroencephalographic activity or other electrophysiological measures of the brain function. An essential factor in the successful operation of BCI systems is the methods used to process the brain signals. In the BCI literature, however, there is no comprehensive review of the signal processing techniques used. This work presents the first such comprehensive survey of all BCI designs using electrical signal recordings published prior to January 2006. Detailed results from this survey are presented and discussed. The following key research questions are addressed: (1) what are the key signal processing components of a BCI, (2) what signal processing algorithms have been used in BCIs and (3) which signal processing techniques have received more attention?

  8. Ultrasonic Detection of Cracks in a Complex Aircraft Structure Using a Local Correlation Method for Signals from a Moving Transducer

    NASA Astrophysics Data System (ADS)

    Aldrin, John C.; Mandeville, John R.; Kropas-Hughes, Claudia V.

    2004-02-01

    A challenge in nondestructive evaluation is the ability to discern signals that are closely spaced or superimposed in time. A feature extraction methodology is proposed where signals from a moving transducer are accurately aligned to a primary part feature and analyzed within multiple time gates for shifting signals from a defect. The local correlation method functions to detect the relative shift of signals in time for adjacent transducer locations due to differing echo dynamics from cracks and part geometries.

  9. Bacteriorhodopsin films for optical signal processing and data storage

    NASA Technical Reports Server (NTRS)

    Walkup, John F. (Principal Investigator); Mehrl, David J. (Principal Investigator)

    1996-01-01

    This report summarizes the research results obtained on NASA Ames Grant NAG 2-878 entitled 'Investigations of Bacteriorhodopsin Films for Optical Signal Processing and Data Storage.' Specifically we performed research, at Texas Tech University, on applications of Bacteriorhodopisin film to both (1) dynamic spatial filtering and (2) holographic data storage. In addition, measurements of the noise properties of an acousto-optical matrix-vestor multiplier built for NASA Ames by Photonic Systems Inc. were performed at NASA Ames' Photonics Laboratory. This research resulted in two papers presented at major optical data processing conferences and a journal paper which is to appear in APPLIED OPTICS. A new proposal for additional BR research has recently been submitted to NASA Ames Research Center.

  10. Tunable photonic filters: a digital signal processing design approach.

    PubMed

    Binh, Le Nguyen

    2009-05-20

    Digital signal processing techniques are used for synthesizing tunable optical filters with variable bandwidth and centered reference frequency including the tunability of the low-pass, high-pass, bandpass, and bandstop optical filters. Potential applications of such filters are discussed, and the design techniques and properties of recursive digital filters are outlined. The basic filter structures, namely, the first-order all-pole optical filter (FOAPOF) and the first-order all-zero optical filter (FOAZOF), are described, and finally the design process of tunable optical filters and the designs of the second-order Butterworth low-pass, high-pass, bandpass, and bandstop tunable optical filters are presented. Indeed, we identify that the all-zero and all-pole networks are equivalent with well known principles of optics of interference and resonance, respectively. It is thus very straightforward to implement tunable optical filters, which is a unique feature.

  11. Parametric design and correlational analyses help integrating fMRI and electrophysiological data during face processing.

    PubMed

    Horovitz, Silvina G; Rossion, Bruno; Skudlarski, Pawel; Gore, John C

    2004-08-01

    Face perception is typically associated with activation in the inferior occipital, superior temporal (STG), and fusiform gyri (FG) and with an occipitotemporal electrophysiological component peaking around 170 ms on the scalp, the N170. However, the relationship between the N170 and the multiple face-sensitive activations observed in neuroimaging is unclear. It has been recently shown that the amplitude of the N170 component monotonically decreases as gaussian noise is added to a picture of a face [Jemel et al., 2003]. To help clarify the sources of the N170 without a priori assumptions regarding their number and locations, ERPs and fMRI were recorded in five subjects in the same experiment, in separate sessions. We used a parametric paradigm in which the amplitude of the N170 was modulated by varying the level of noise in a picture, and identified regions where the percent signal change in fMRI correlated with the ERP data. N170 signals were observed for pictures of both cars and faces but were stronger for faces. A monotonic decrease with added noise was observed for the N170 at right hemisphere sites but was less clear on the left and occipital central sites. Correlations between fMRI signal and N170 amplitudes for faces were highly significant (P < 0.001) in bilateral fusiform gyrus and superior temporal gyrus. For cars, the strongest correlations were observed in the parahippocampal region and in the STG (P < 0.005). Besides contributing to clarify the spatiotemporal course of face processing, this study illustrates how ERP information may be used synergistically in fMRI analyses. Parametric designs may be developed further to provide some timing information on fMRI activity and help identify the generators of ERP signals.

  12. High efficiency processing for reduced amplitude zones detection in the HRECG signal

    NASA Astrophysics Data System (ADS)

    Dugarte, N.; Álvarez, A.; Balacco, J.; Mercado, G.; Gonzalez, A.; Dugarte, E.; Olivares, A.

    2016-04-01

    Summary - This article presents part of a more detailed research proposed in the medium to long term, with the intention of establishing a new philosophy of electrocardiogram surface analysis. This research aims to find indicators of cardiovascular disease in its early stage that may go unnoticed with conventional electrocardiography. This paper reports the development of a software processing which collect some existing techniques and incorporates novel methods for detection of reduced amplitude zones (RAZ) in high resolution electrocardiographic signal (HRECG).The algorithm consists of three stages, an efficient processing for QRS detection, averaging filter using correlation techniques and a step for RAZ detecting. Preliminary results show the efficiency of system and point to incorporation of techniques new using signal analysis with involving 12 leads.

  13. Optical fibre sensors based on multi-mode fibres and MIMO signal processing: an experimental approach

    NASA Astrophysics Data System (ADS)

    Ahrens, Andreas; Sandmann, Andre; Bremer, Kort; Roth, Bernhard; Lochmann, Steffen

    2015-09-01

    In this paper multiple-input multiple-output (MIMO) signal processing is investigated for fibre optic sensor applications. A (2 × 2) MIMO implementation is realized by using lower-order and higher-order mode groups of a graded-index (GI) multi-mode fibre (MMF) as separate transmission channels. A micro-bending pressure sensor changes these separate transmission characteristics and introduces additional crosstalk. By observing the weight-factors of the MIMO system the amount of load applied was determined. Experiments verified a good correlation between the change of the MIMO weight coefficients and the load applied to the sensor and thus verified that MIMO signal processing can beneficially be used for fibre optic sensor applications.

  14. Phase resolved digital signal processing in optical coherence tomography

    NASA Astrophysics Data System (ADS)

    de Boer, Johannes F.; Tripathi, Renu; Park, Boris H.; Nassif, Nader

    2002-06-01

    We present phase resolved digital signal processing techniques for Optical Coherence Tomography to correct for the non Gaussian shape of source spectra and for Group Delay Dispersion (GDD). A broadband source centered at 820 nm was synthesized by combining the spectra of two superluminescent diodes to improve axial image resolution in an optical coherence tomography (OCT) system. Spectral shaping was used to reduce the side lobes (ringing) in the axial point spread function due to the non-Gaussian shape of the spectra. Images of onion cells taken with each individual source and the combined sources, respectively, show the improved resolution and quality enhancement in a turbid biological sample. An OCT system operating at 1310 nm was used to demonstrate that the broadening effect of group delay dispersion (GDD) on the coherence function could be eliminated completely by introducing a quadratic phase shift in the Fourier domain of the interferometric signal. The technique is demonstrated by images of human skin grafts with group delay dispersion mismatch between sample and reference arm before and after digital processing.

  15. Observer-based beamforming algorithm for acoustic array signal processing.

    PubMed

    Bai, Long; Huang, Xun

    2011-12-01

    In the field of noise identification with microphone arrays, conventional delay-and-sum (DAS) beamforming is the most popular signal processing technique. However, acoustic imaging results that are generated by DAS beamforming are easily influenced by background noise, particularly for in situ wind tunnel tests. Even when arithmetic averaging is used to statistically remove the interference from the background noise, the results are far from perfect because the interference from the coherent background noise is still present. In addition, DAS beamforming based on arithmetic averaging fails to deliver real-time computational capability. An observer-based approach is introduced in this paper. This so-called observer-based beamforming method has a recursive form similar to the state observer in classical control theory, thus holds a real-time computational capability. In addition, coherent background noise can be gradually rejected in iterations. Theoretical derivations of the observer-based beamforming algorithm are carefully developed in this paper. Two numerical simulations demonstrate the good coherent background noise rejection and real-time computational capability of the observer-based beamforming, which therefore can be regarded as an attractive algorithm for acoustic array signal processing.

  16. CoSi: Correlation of signals-A new measure to assess the correlation of history response curves

    NASA Astrophysics Data System (ADS)

    Murmann, Robert; Harzheim, Lothar; Dominico, Stefan; Immel, Rainer

    2016-12-01

    In the context of CAE work it is often required to assess the level of agreement of two curves objectively, e.g. measured against numerically computed results. Therefore a new comprehensive measure is proposed in this paper. The new measure 'CoSi' (Correlation of Signals) allows to account for uncertainties in both curves. This is achieved by constructing a corridor around one curve which considers deviations in direction of both abscissa and ordinate. Here CoSi differs from other common corridor approaches which consider only the deviation on the ordinate. It is explained how CoSi aligns the two curves taking the uncertainties of the second curve by scaling and shifting into account. This leads to the best theoretical achievable agreement between the two curves. Based on the aligned curves, quality factors are calculated to evaluate the results in terms of amplitudes of the curves, their overall match in shape, the phase between the curves, and all these combined into a comprehensive quality factor. The properties and results of CoSi are compared with other metrics from literature using various examples.

  17. Multidimensional optical signal processing using optical coherent transient spatial-spectral holography

    NASA Astrophysics Data System (ADS)

    Anderson, Kenneth Edward

    This thesis presents analysis and experimental demonstrations of several new optical signal processing architectures that are based on optical coherent transient (OCT) technology and investigates many system design issues that must be taken into account when building such systems. OCT materials have the potential to optically process both high bandwidth (>10 GHz) and high time-bandwidth (>106) signals with the ability to potentially store huge amounts of data (up to 1000's of TB/cm3 using spatial-temporal holography. Several OCT system architectures are proposed and discussed including: raster image correlators, scanners, RF spectrum analyzers, time integrating correlators, image sequence correlators, and dynamic optical switches. In addition, some of the first experimental demonstrations of multiple channel spatial-temporal signal processing using OCT materials are shown. Novel system architectures for performing chromatic, polarization mode, and modal dispersion compensation are discussed, analyzed, and initial experimental results are shown demonstrating chromatic dispersion compensation of up to 5 mus of dispersion. A new approach for multiplexing 100's of individual DWDM channels of information down one multimode fiber is proposed and analyzed. In addition, a high bandwidth adaptive phased array beam steering system is also proposed and investigated along with experimental results showing the first demonstration of simultaneous time delay and processing of information with OCT materials. Lastly, results are presented for several stabilized lasers systems that have been built throughout the course of this research. The techniques used for stabilizing these lasers systems included optical feedback from gratings and Fabry-Perot cavities and electronic feedback techniques using Pound-Drever-Hall frequency locking.

  18. Correlation between a loss of auxin signaling and a loss of proliferation in maize antipodal cells

    PubMed Central

    Chettoor, Antony M.; Evans, Matthew M. S.

    2015-01-01

    The plant life cycle alternates between two genetically active generations: the diploid sporophyte and the haploid gametophyte. In angiosperms the gametophytes are sexually dimorphic and consist of only a few cells. The female gametophyte, or embryo sac, is comprised of four cell types: two synergids, an egg cell, a central cell, and a variable number of antipodal cells. In some species the antipodal cells are indistinct and fail to proliferate, so many aspects of antipodal cell function and development have been unclear. In maize and many other grasses, the antipodal cells proliferate to produce a highly distinct cluster at the chalazal end of the embryo sac that persists at the apex of the endosperm after fertilization. The antipodal cells are a site of auxin accumulation in the maize embryo sac. Analysis of different families of genes involved in auxin biosynthesis, distribution, and signaling for expression in the embryo sac demonstrates that all steps are expressed within the embryo sac. In contrast to auxin signaling, cytokinin signaling is absent in the embryo sac and instead occurs adjacent to but outside of the antipodal cells. Mutant analysis shows a correlation between a loss of auxin signaling and a loss of proliferation of the antipodal cells. The leaf polarity mutant Laxmidrib1 causes a lack of antipodal cell proliferation coupled with a loss of DR5 and PIN1a expression in the antipodal cells. PMID:25859254

  19. Chemical library screening for WNK signalling inhibitors using fluorescence correlation spectroscopy.

    PubMed

    Mori, Takayasu; Kikuchi, Eriko; Watanabe, Yuko; Fujii, Shinya; Ishigami-Yuasa, Mari; Kagechika, Hiroyuki; Sohara, Eisei; Rai, Tatemitsu; Sasaki, Sei; Uchida, Shinichi

    2013-11-01

    WNKs (with-no-lysine kinases) are the causative genes of a hereditary hypertensive disease, PHAII (pseudohypoaldosteronism type II), and form a signal cascade with OSR1 (oxidative stress-responsive 1)/SPAK (STE20/SPS1-related proline/alanine-rich protein kinase) and Slc12a (solute carrier family 12) transporters. We have shown that this signal cascade regulates blood pressure by controlling vascular tone as well as renal NaCl excretion. Therefore agents that inhibit this signal cascade could be a new class of antihypertensive drugs. Since the binding of WNK to OSR1/SPAK kinases was postulated to be important for signal transduction, we sought to discover inhibitors of WNK/SPAK binding by screening chemical compounds that disrupt the binding. For this purpose, we developed a high-throughput screening method using fluorescent correlation spectroscopy. As a result of screening 17000 compounds, we discovered two novel compounds that reproducibly disrupted the binding of WNK to SPAK. Both compounds mediated dose-dependent inhibition of hypotonicity-induced activation of WNK, namely the phosphorylation of SPAK and its downstream transporters NKCC1 (Na/K/Cl cotransporter 1) and NCC (NaCl cotransporter) in cultured cell lines. The two compounds could be the promising seeds of new types of antihypertensive drugs, and the method that we developed could be applied as a general screening method to identify compounds that disrupt the binding of two molecules.

  20. Quantum correlation dynamics in photosynthetic processes assisted by molecular vibrations

    SciTech Connect

    Giorgi, G.L.; Roncaglia, M.; Raffa, F.A.; Genovese, M.

    2015-10-15

    During the long course of evolution, nature has learnt how to exploit quantum effects. In fact, recent experiments reveal the existence of quantum processes whose coherence extends over unexpectedly long time and space ranges. In particular, photosynthetic processes in light-harvesting complexes display a typical oscillatory dynamics ascribed to quantum coherence. Here, we consider the simple model where a dimer made of two chromophores is strongly coupled with a quasi-resonant vibrational mode. We observe the occurrence of wide oscillations of genuine quantum correlations, between electronic excitations and the environment, represented by vibrational bosonic modes. Such a quantum dynamics has been unveiled through the calculation of the negativity of entanglement and the discord, indicators widely used in quantum information for quantifying the resources needed to realize quantum technologies. We also discuss the possibility of approximating additional weakly-coupled off-resonant vibrational modes, simulating the disturbances induced by the rest of the environment, by a single vibrational mode. Within this approximation, one can show that the off-resonant bath behaves like a classical source of noise.

  1. Neural correlates of semantic competition during processing of ambiguous words.

    PubMed

    Bilenko, Natalia Y; Grindrod, Christopher M; Myers, Emily B; Blumstein, Sheila E

    2009-05-01

    The current study investigated the neural correlates that underlie the processing of ambiguous words and the potential effects of semantic competition on that processing. Participants performed speeded lexical decisions on semantically related and unrelated prime-target pairs presented in the auditory modality. The primes were either ambiguous words (e.g., ball) or unambiguous words (e.g., athlete), and targets were either semantically related to the dominant (i.e., most frequent) meaning of the ambiguous prime word (e.g., soccer) or to the subordinate (i.e., less frequent) meaning (e.g., dance). Results showed increased activation in the bilateral inferior frontal gyrus (IFG) for ambiguous-related compared to unambiguous-related stimulus pairs, demonstrating that prefrontal areas are activated even in an implicit task where participants are not required to explicitly analyze the semantic content of the stimuli and to make an overt selection of a particular meaning based on this analysis. Additionally, increased activation was found in the left IFG and the left cingulate gyrus for subordinate meaning compared to dominant meaning conditions, suggesting that additional resources are recruited in order to resolve increased competition demands in accessing the subordinate meaning of an ambiguous word.

  2. Color interpolation algorithm of CCD based on green components and signal correlation

    NASA Astrophysics Data System (ADS)

    Liang, Xiaofen; Qiao, Weidong; Yang, Jianfeng; Xue, Bin; Qin, Jia

    2013-09-01

    Signal CCD/CMOS sensors capture image information by covering the sensor surface with a color filter array(CFA). For each pixel, only one of three primary colors(red, green and blue) can pass through the color filter array(CFA). The other two missing color components are estimated by the values of the surrounding pixels. In Bayer array, the green components are half of the total pixels, but both red pixel and blue pixel components are quarter, so green components contain more information, which can be reference to color interpolation of red components and blue components. Based on this principle, in this paper, a simple and effective color interpolation algorithm based on green components and signal correlation for Bayer pattern images was proposed. The first step is to interpolate R, G and B components using the method-bilinear interpolation. The second step is to revise the results of bilinear interpolation by adding some green components on the results of bilinear interpolation. The calculation of the values to be added should consider the influence of correlation between the three channels. There are two major contributions in the paper. The first one is to demosaick G component more precisely. The second one is the spectral-spatial correlations between the three color channels is taken into consideration. At last, through MATLAB simulation experiments, experimental pictures and quantitative data for performance evaluation-Peak Signal to Noise Ratio(PSNR) were gotten. The results of simulation experiments show, compared with other color interpolation algorithms, the proposed algorithm performs well in both visual perception and PSNR measurement. And the proposed algorithm does not increase the complexity of calculation but ensures the real-time of system. Theory and experiments show the method is reasonable and has important engineering significance.

  3. MR of Toxoplasma encephalitis: Signal characteristics on T2-weighted images and pathologic correlation

    SciTech Connect

    Brightbill, T.C.; Hensley, G.T.; Ruiz, A.

    1996-05-01

    Our goal was to determine if there are any T2-weighted MR signal characteristics of Toxoplasma encephalitis that might be useful in diagnosis and/or in gauging the effectiveness of medical therapy. We retrospectively analyzed the MR, CT, thallium-201 SPECT brain scans, and medical records of 27 patients with medically proven (26) and biopsy proven (1) Toxoplasma encephalitis, supplemented by autopsy findings in 4 additional patients, 2 of whom had postmortem MR correlation. The neuropathologic literature was also reviewed. Among the 27 patients, we discovered three distinct imaging patterns. Ten (37%) patients had predominantly T2-weighted hyperintense lesions and had been on medical therapy an average of 3 days (excluding one outlier). Ten (37%) patients had T2-weighted isointense lesions and had received medical therapy an average of 61 days. Seven (26%) patients had lesions with mixed signal on T2-weighted images and bad been on treatment an average of 6 days. Analysis of autopsy material from the four additional patients revealed the presence of organizing abscesses in three and necrotizing encephalitis in one, while the patient who had a brain biopsy demonstrated both types of pathologic lesions. In both cases having postmortem MRI, organizing abscesses appeared isointense to hypointense on T2-weighted images. There is a definite variation in the appearance of lesions of Toxoplasma encephalitis on T2-weighted images that precludes a definitive diagnosis based on signal characteristics alone. Pathologically, our data suggest that T2-weighted hyperintensity correlates with necrotizing encephalitis and T2-weighted isointensity with organizing abscesses. Furthermore, in patients on medical therapy the T2-weighted MR appearance may be a transition from hyperintensity to isointensity as a function of a positive response to antibiotic treatment, indicating that the signal change might be used to gauge the effectiveness of medical therapy. 15 refs., 6 figs.

  4. Control mechanism to prevent correlated message arrivals from degrading signaling no. 7 network performance

    NASA Astrophysics Data System (ADS)

    Kosal, Haluk; Skoog, Ronald A.

    1994-04-01

    Signaling System No. 7 (SS7) is designed to provide a connection-less transfer of signaling messages of reasonable length. Customers having access to user signaling bearer capabilities as specified in the ANSI T1.623 and CCITT Q.931 standards can send bursts of correlated messages (e.g., by doing a file transfer that results in the segmentation of a block of data into a number of consecutive signaling messages) through SS7 networks. These message bursts with short interarrival times could have an adverse impact on the delay performance of the SS7 networks. A control mechanism, Credit Manager, is investigated in this paper to regulate incoming traffic to the SS7 network by imposing appropriate time separation between messages when the incoming stream is too bursty. The credit manager has a credit bank where credits accrue at a fixed rate up to a prespecified credit bank capacity. When a message arrives, the number of octets in that message is compared to the number of credits in the bank. If the number of credits is greater than or equal to the number of octets, then the message is accepted for transmission and the number of credits in the bank is decremented by the number of octets. If the number of credits is less than the number of octets, then the message is delayed until enough credits are accumulated. This paper presents simulation results showing delay performance of the SS7 ISUP and TCAP message traffic with a range of correlated message traffic, and control parameters of the credit manager (i.e., credit generation rate and bank capacity) are determined that ensure the traffic entering the SS7 network is acceptable. The results show that control parameters can be set so that for any incoming traffic stream there is no detrimental impact on the SS7 ISUP and TCAP message delay, and the credit manager accepts a wide range of traffic patterns without causing significant delay.

  5. A methodology for time-frequency image processing applied to the classification of non-stationary multichannel signals using instantaneous frequency descriptors with application to newborn EEG signals

    NASA Astrophysics Data System (ADS)

    Boashash, Boualem; Boubchir, Larbi; Azemi, Ghasem

    2012-12-01

    This article presents a general methodology for processing non-stationary signals for the purpose of classification and localization. The methodology combines methods adapted from three complementary areas: time-frequency signal analysis, multichannel signal analysis and image processing. The latter three combine in a new methodology referred to as multichannel time-frequency image processing which is applied to the problem of classifying electroencephalogram (EEG) abnormalities in both adults and newborns. A combination of signal related features and image related features are used by merging key instantaneous frequency descriptors which characterize the signal non-stationarities. The results obtained show that, firstly, the features based on time-frequency image processing techniques such as image segmentation, improve the performance of EEG abnormalities detection in the classification systems based on multi-SVM and neural network classifiers. Secondly, these discriminating features are able to better detect the correlation between newborn EEG signals in a multichannel-based newborn EEG seizure detection for the purpose of localizing EEG abnormalities on the scalp.

  6. Long-Range Correlations in the Sequence of Human Heartbeats and Other Biological Signals

    NASA Astrophysics Data System (ADS)

    Teich, Malvin C.

    1998-03-01

    specificity for various salient measures, as a function of data length, is determined by the use of ROC analysis. A phase-space reconstruction based on generalized heart rate is used to obtain a putative attractor's capacity dimension. Though the dependence of this dimension on the embedding dimension is consistent with that of a low-dimensional dynamical system, surrogate-data analysis shows that identical behavior emerges from long-range temporal correlations in a stochastic process.^2 An integrate-and-fire model, comprising a fractal-Gaussian-noise kernel and Gaussian event-jittering,(S. Thurner, S. B. Lowen, M. C. Feurstein, C. Heneghan, H. G. Feichtinger, and M. C. Teich, Fractals) 5, No. 4 (1997). provides a realistic simulation of heartbeat sequences for both normal and heart-failure patients, over all time scales. These results could be of use in generating an artificial heartbeat that mimics the healthy heartbeat sequence for applications such as pacemakers. The presentation will be concluded with a brief discussion of the application of these methods to other unitary biological signals.

  7. Electrophysiological correlates of the BOLD signal for EEG-informed fMRI

    PubMed Central

    Murta, Teresa; Leite, Marco; Carmichael, David W; Figueiredo, Patrícia; Lemieux, Louis

    2015-01-01

    Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) are important tools in cognitive and clinical neuroscience. Combined EEG–fMRI has been shown to help to characterise brain networks involved in epileptic activity, as well as in different sensory, motor and cognitive functions. A good understanding of the electrophysiological correlates of the blood oxygen level-dependent (BOLD) signal is necessary to interpret fMRI maps, particularly when obtained in combination with EEG. We review the current understanding of electrophysiological–haemodynamic correlates, during different types of brain activity. We start by describing the basic mechanisms underlying EEG and BOLD signals and proceed by reviewing EEG-informed fMRI studies using fMRI to map specific EEG phenomena over the entire brain (EEG–fMRI mapping), or exploring a range of EEG-derived quantities to determine which best explain colocalised BOLD fluctuations (local EEG–fMRI coupling). While reviewing studies of different forms of brain activity (epileptic and nonepileptic spontaneous activity; cognitive, sensory and motor functions), a significant attention is given to epilepsy because the investigation of its haemodynamic correlates is the most common application of EEG-informed fMRI. Our review is focused on EEG-informed fMRI, an asymmetric approach of data integration. We give special attention to the invasiveness of electrophysiological measurements and the simultaneity of multimodal acquisitions because these methodological aspects determine the nature of the conclusions that can be drawn from EEG-informed fMRI studies. We emphasise the advantages of, and need for, simultaneous intracranial EEG–fMRI studies in humans, which recently became available and hold great potential to improve our understanding of the electrophysiological correlates of BOLD fluctuations. PMID:25277370

  8. Electrophysiological correlates of the BOLD signal for EEG-informed fMRI.

    PubMed

    Murta, Teresa; Leite, Marco; Carmichael, David W; Figueiredo, Patrícia; Lemieux, Louis

    2015-01-01

    Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) are important tools in cognitive and clinical neuroscience. Combined EEG-fMRI has been shown to help to characterise brain networks involved in epileptic activity, as well as in different sensory, motor and cognitive functions. A good understanding of the electrophysiological correlates of the blood oxygen level-dependent (BOLD) signal is necessary to interpret fMRI maps, particularly when obtained in combination with EEG. We review the current understanding of electrophysiological-haemodynamic correlates, during different types of brain activity. We start by describing the basic mechanisms underlying EEG and BOLD signals and proceed by reviewing EEG-informed fMRI studies using fMRI to map specific EEG phenomena over the entire brain (EEG-fMRI mapping), or exploring a range of EEG-derived quantities to determine which best explain colocalised BOLD fluctuations (local EEG-fMRI coupling). While reviewing studies of different forms of brain activity (epileptic and nonepileptic spontaneous activity; cognitive, sensory and motor functions), a significant attention is given to epilepsy because the investigation of its haemodynamic correlates is the most common application of EEG-informed fMRI. Our review is focused on EEG-informed fMRI, an asymmetric approach of data integration. We give special attention to the invasiveness of electrophysiological measurements and the simultaneity of multimodal acquisitions because these methodological aspects determine the nature of the conclusions that can be drawn from EEG-informed fMRI studies. We emphasise the advantages of, and need for, simultaneous intracranial EEG-fMRI studies in humans, which recently became available and hold great potential to improve our understanding of the electrophysiological correlates of BOLD fluctuations.

  9. Cognitive tasks during walking affect cerebral blood flow signal features in middle cerebral arteries and their correlation to gait characteristics.

    PubMed

    Gatouillat, Arthur; Bleton, Héloïse; VanSwearingen, Jessie; Perera, Subashan; Thompson, Scott; Smith, Traci; Sejdić, Ervin

    2015-09-26

    Gait is a complex process involving both cognitive and sensory ability and is strongly impacted by the environment. In this paper, we propose to study of the impact of a cognitive task during gait on the cerebral blood flow velocity, the blood flow signal features and the correlation of gait and blood flow features through a dual task methodology. Both cerebral blood flow velocity and gait characteristics of eleven participants with no history of brain or gait conditions were recorded using transcranial Doppler on mid-cerebral artery while on a treadmill. The cognitive task was induced by a backward counting starting from 10,000 with decrement of 7. Central blood flow velocity raw and envelope features were extracted in both time, frequency and time-scale domain; information-theoretic metrics were also extracted and statistical significances were inspected. A similar feature extraction was performed on the stride interval signal. Statistical differences between the cognitive and baseline trials, between the left and right mid-cerebral arteries signals and the impact of the antropometric variables where studied using linear mixed models. No statistical differences were found between the left and right mid-cerebral arteries flows or the baseline and cognitive state gait features, while statistical differences for specific features were measured between cognitive and baseline states. These statistical differences found between the baseline and cognitive states show that cognitive process has an impact on the cerebral activity during walking. The state was found to have an impact on the correlation between the gait and blood flow features.

  10. Tracking the dehydration process of raw honey by synchronous two-dimensional near infrared correlation spectroscopy

    NASA Astrophysics Data System (ADS)

    Chen, Guiyun; Sun, Xin; Huang, Yuping; Chen, Kunjie

    2014-11-01

    Though much attention is paid to honey quality assessment, few reports on characteristic of manually dehydrated honey have been found. The aim of this investigation is to track the dehydration process of raw honey using synchronous two-dimensional (2D) near infrared correlation spectroscopy. To minimize the impact of dehydration to honey quality, seventy-two honey samples from six different dehydration stages were obtained using drum wind drying method with temperature controlled at 40 °C. Their dynamic short-wave NIR spectra from 600 to 1100 nm were collected in the transmission mode from 10 to 50 °C with an increment of 5 °C and were analyzed using synchronous two-dimensional correlation method. Short-wave NIR spectral data has been exploited less than other NIR region for its weaker signal especially for water absorption's interference with useful information. The investigation enlarged the signal at this band using synchronous 2D correlation analysis, revealing the fingerprinting feature of rape honey and chaste honey during the artificial dehydration process. The results have shown that, with the help of 2D correlation analysis, this band can detect the variation of the second overtone of O-H and N-H groups vibration upon their H-bonds forming or collapsing resulted from the interactions between water and solute. The results have also shown that 2D-NIRS method is able to convert the tiny changes in honey constituents into the detectable fingerprinting difference, which provides a new method for assessing honey quality.

  11. Single sensor processing to obtain high resolution color component signals

    NASA Technical Reports Server (NTRS)

    Glenn, William E. (Inventor)

    2010-01-01

    A method for generating color video signals representative of color images of a scene includes the following steps: focusing light from the scene on an electronic image sensor via a filter having a tri-color filter pattern; producing, from outputs of the sensor, first and second relatively low resolution luminance signals; producing, from outputs of the sensor, a relatively high resolution luminance signal; producing, from a ratio of the relatively high resolution luminance signal to the first relatively low resolution luminance signal, a high band luminance component signal; producing, from outputs of the sensor, relatively low resolution color component signals; and combining each of the relatively low resolution color component signals with the high band luminance component signal to obtain relatively high resolution color component signals.

  12. Signal Processing Methods for Liquid Rocket Engine Combustion Stability Assessments

    NASA Technical Reports Server (NTRS)

    Kenny, R. Jeremy; Lee, Erik; Hulka, James R.; Casiano, Matthew

    2011-01-01

    The J2X Gas Generator engine design specifications include dynamic, spontaneous, and broadband combustion stability requirements. These requirements are verified empirically based high frequency chamber pressure measurements and analyses. Dynamic stability is determined with the dynamic pressure response due to an artificial perturbation of the combustion chamber pressure (bomb testing), and spontaneous and broadband stability are determined from the dynamic pressure responses during steady operation starting at specified power levels. J2X Workhorse Gas Generator testing included bomb tests with multiple hardware configurations and operating conditions, including a configuration used explicitly for engine verification test series. This work covers signal processing techniques developed at Marshall Space Flight Center (MSFC) to help assess engine design stability requirements. Dynamic stability assessments were performed following both the CPIA 655 guidelines and a MSFC in-house developed statistical-based approach. The statistical approach was developed to better verify when the dynamic pressure amplitudes corresponding to a particular frequency returned back to pre-bomb characteristics. This was accomplished by first determining the statistical characteristics of the pre-bomb dynamic levels. The pre-bomb statistical characterization provided 95% coverage bounds; these bounds were used as a quantitative measure to determine when the post-bomb signal returned to pre-bomb conditions. The time for post-bomb levels to acceptably return to pre-bomb levels was compared to the dominant frequency-dependent time recommended by CPIA 655. Results for multiple test configurations, including stable and unstable configurations, were reviewed. Spontaneous stability was assessed using two processes: 1) characterization of the ratio of the peak response amplitudes to the excited chamber acoustic mode amplitudes and 2) characterization of the variability of the peak response

  13. 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.

  14. Improved Statistical Signal Processing of Nonstationary Random Processes Using Time-Warping

    NASA Astrophysics Data System (ADS)

    Wisdom, Scott Thomas

    A common assumption used in statistical signal processing of nonstationary random signals is that the signals are locally stationary. Using this assumption, data is segmented into short analysis frames, and processing is performed using these short frames. Short frames limit the amount of data available, which in turn limits the performance of statistical estimators. In this thesis, we propose a novel method that promises improved performance for a variety of statistical signal processing algorithms. This method proposes to estimate certain time-varying parameters of nonstationary signals and then use this estimated information to perform a time-warping of the data that compensates for the time-varying parameters. Since the time-warped data is more stationary, longer analysis frames may be used, which improves the performance of statistical estimators. We first examine the spectral statistics of two particular types of nonstationary random processes that are useful for modeling ship propeller noise and voiced speech. We examine the effect of time-varying frequency content on these spectral statistics, and in addition show that the cross-frequency spectral statistics of these signals contain significant additional information that is not usually exploited using a stationary assumption. This information, combined with our proposed method, promises improvements for a wide variety of applications in the future. We then describe and test an implementation of our time-warping method, the fan-chirp transform. We apply our method to two applications, detection of ship noise in a passive sonar application and joint denoising and dereverberation of speech. Our method yields improved results for both applications compared to conventional methods.

  15. Optimal Signal Processing in Small Stochastic Biochemical Networks

    PubMed Central

    Ziv, Etay; Nemenman, Ilya; Wiggins, Chris H.

    2007-01-01

    We quantify the influence of the topology of a transcriptional regulatory network on its ability to process environmental signals. By posing the problem in terms of information theory, we do this without specifying the function performed by the network. Specifically, we study the maximum mutual information between the input (chemical) signal and the output (genetic) response attainable by the network in the context of an analytic model of particle number fluctuations. We perform this analysis for all biochemical circuits, including various feedback loops, that can be built out of 3 chemical species, each under the control of one regulator. We find that a generic network, constrained to low molecule numbers and reasonable response times, can transduce more information than a simple binary switch and, in fact, manages to achieve close to the optimal information transmission fidelity. These high-information solutions are robust to tenfold changes in most of the networks' biochemical parameters; moreover they are easier to achieve in networks containing cycles with an odd number of negative regulators (overall negative feedback) due to their decreased molecular noise (a result which we derive analytically). Finally, we demonstrate that a single circuit can support multiple high-information solutions. These findings suggest a potential resolution of the “cross-talk” phenomenon as well as the previously unexplained observation that transcription factors that undergo proteolysis are more likely to be auto-repressive. PMID:17957259

  16. Correlation study between contamination and signal degradation in single-mode APC connectors

    NASA Astrophysics Data System (ADS)

    Lytle, Steve; Brown, Matt; Berdinskikh, Tatiana; Wilson, Douglas H.; Fisher, David; Huang, Sun-Yuan; Hughes, Mike; Mitcheltree, Tom; Roche, Brian J.

    2009-06-01

    This paper summarizes the correlation study between contamination and scratches on singlemode APC connectors and signal degradation; leading to an Acceptance Criteria Matrix. The study is a continuation of International Electronics Manufacturing Initiative (iNEMI) research on development of cleanliness specification for singlemode angled physical contact (SM-APC) connectors. Twenty-five APC SC connectors on one-meter patch cords were used for this study. The Design of the Experiment (DoE) was a multi-step process that involved: (1) inspecting, cleaning and inspecting connectors being tested (devices under test, or DUTs) and launch connectors; (2) making multiple matings and dematings of each DUT, in a pristine state, with a reference connector, and recording Return Loss (RL) data after each cycle; (3) manually applying dust to the cleaned end-faces of the DUTs; then (4) mating contaminated DUTs with clean reference connectors at least five times, taking RL measurements after each mating and saving fiber end-face images for both connectors. It was shown that connectors with the contamination at the core (9um diameter) demonstrated a dramatic decrease in average RL of 14.2 dB. In comparison, the samples with contamination on the cladding and clear core demonstrated a negligible change in RL of 0.15 dB. For highly contaminated samples in the cladding layer, we found the changes of RL to be about 5-6 dB. Further investigation established that particle migration during successive matings also occurs on the ferrule within the contact zone (approximately <250 μm in diameter). Polishing scratches had no impact on RL of APC connectors. Based on the experimental data described in this paper, an inspection criteria matrix is proposed for SM-APC connectors including the zone definitions and number of allowable defects (contamination and scratches) for each zone. The recommendations on pass/fail criteria have been provided to the IEC (International Electrotechnical Committee

  17. Modeling and processing of laser Doppler reactive hyperaemia signals

    NASA Astrophysics Data System (ADS)

    Humeau, Anne; Saumet, Jean-Louis; L'Huiller, Jean-Pierre

    2003-07-01

    Laser Doppler flowmetry is a non-invasive method used in the medical domain to monitor the microvascular blood cell perfusion through tissue. Most commercial laser Doppler flowmeters use an algorithm calculating the first moment of the power spectral density to give the perfusion value. Many clinical applications measure the perfusion after a vascular provocation such as a vascular occlusion. The response obtained is then called reactive hyperaemia. Target pathologies include diabetes, hypertension and peripheral arterial occlusive diseases. In order to have a deeper knowledge on reactive hyperaemia acquired by the laser Doppler technique, the present work first proposes two models (one analytical and one numerical) of the observed phenomenon. Then, a study on the multiple scattering between photons and red blood cells occurring during reactive hyperaemia is carried out. Finally, a signal processing that improves the diagnosis of peripheral arterial occlusive diseases is presented.

  18. Neurological Tremor: Sensors, Signal Processing and Emerging Applications

    PubMed Central

    Grimaldi, Giuliana; Manto, Mario

    2010-01-01

    Neurological tremor is the most common movement disorder, affecting more than 4% of elderly people. Tremor is a non linear and non stationary phenomenon, which is increasingly recognized. The issue of selection of sensors is central in the characterization of tremor. This paper reviews the state-of-the-art instrumentation and methods of signal processing for tremor occurring in humans. We describe the advantages and disadvantages of the most commonly used sensors, as well as the emerging wearable sensors being developed to assess tremor instantaneously. We discuss the current limitations and the future applications such as the integration of tremor sensors in BCIs (brain-computer interfaces) and the need for sensor fusion approaches for wearable solutions. PMID:22205874

  19. Possible Signal for Critical Point in Hadronization Process

    NASA Astrophysics Data System (ADS)

    Rybczynski, M.; Wlodarczyk, Z.; Wilk, G.

    2004-02-01

    We argue that recent data on fluctuations observed in heavy ion collisions show non-monotonic behaviour as function of number of participants (or ''wounded nucleons'') NW. When interpreted in thermodynamical approach this result can be associated with a possible structure occurring in the corresponding equation of state (EoS). This in turn could be further interpreted as due to the occurrence of some characteristic points (like softest point or critical point) of EoS discussed in the literature and therefore be regarded as a possible signal of the QGP formation in such collisions. We show, however, that the actual situation is still far from being clear and calls for more investigations of fluctuation phenomena in multiparticle production processes to be performed.

  20. On adaptive robustness approach to Anti-Jam signal processing

    NASA Astrophysics Data System (ADS)

    Poberezhskiy, Y. S.; Poberezhskiy, G. Y.

    An effective approach to exploiting statistical differences between desired and jamming signals named adaptive robustness is proposed and analyzed in this paper. It combines conventional Bayesian, adaptive, and robust approaches that are complementary to each other. This combining strengthens the advantages and mitigates the drawbacks of the conventional approaches. Adaptive robustness is equally applicable to both jammers and their victim systems. The capabilities required for realization of adaptive robustness in jammers and victim systems are determined. The employment of a specific nonlinear robust algorithm for anti-jam (AJ) processing is described and analyzed. Its effectiveness in practical situations has been proven analytically and confirmed by simulation. Since adaptive robustness can be used by both sides in electronic warfare, it is more advantageous for the fastest and most intelligent side. Many results obtained and discussed in this paper are also applicable to commercial applications such as communications in unregulated or poorly regulated frequency ranges and systems with cognitive capabilities.

  1. Digital Signal Processing for the Event Horizon Telescope

    NASA Astrophysics Data System (ADS)

    Weintroub, Jonathan

    2015-08-01

    A broad international collaboration is building the Event Horizon Telescope (EHT). The aim is to test Einstein’s theory of General Relativity in one of the very few places it could break down: the strong gravity regime right at the edge of a black hole. The EHT is an earth-size VLBI array operating at the shortest radio wavelengths, that has achieved unprecedented angular resolution of a few tens of μarcseconds. For nearby super massive black holes (SMBH) this size scale is comparable to the Schwarzschild Radius, and emission in the immediate neighborhood of the event horizon can be directly observed. We give an introduction to the science behind the CASPER-enabled EHT, and outline technical developments, with emphasis on the secret sauce of high speed signal processing.

  2. Quantum signal processing-based visual cryptography with unexpanded shares

    NASA Astrophysics Data System (ADS)

    Das, Surya Sarathi; Sharma, Kaushik Das; Chandra, Jayanta K.; Bera, Jitendra Nath

    2015-09-01

    This paper proposes a visual cryptography scheme (VCS) based on quantum signal processing (QSP). VCS is an image encryption technique that is very simple in formulation and is secure. In (k,n)-VCS, a secret binary image is encoded into n share images and minimum k shares are needed to decrypt the secret image. The efforts to encrypt a grayscale image are few in number and the majority are related to grayscale to binary conversion. Thus, a generalized approach of encryption for all types of images, i.e., binary, gray, and color is needed. Here, a generic VCS is proposed based on QSP where all types of images can be encrypted without pixel expansion along with a smoothing technique to enhance the quality of the decrypted image. The proposed scheme is tested and compared for benchmark images, and the result shows the effectiveness of the scheme.

  3. REVIEW ARTICLE: Spectrophotometric applications of digital signal processing

    NASA Astrophysics Data System (ADS)

    Morawski, Roman Z.

    2006-09-01

    Spectrophotometry is more and more often the method of choice not only in analysis of (bio)chemical substances, but also in the identification of physical properties of various objects and their classification. The applications of spectrophotometry include such diversified tasks as monitoring of optical telecommunications links, assessment of eating quality of food, forensic classification of papers, biometric identification of individuals, detection of insect infestation of seeds and classification of textiles. In all those applications, large numbers of data, generated by spectrophotometers, are processed by various digital means in order to extract measurement information. The main objective of this paper is to review the state-of-the-art methodology for digital signal processing (DSP) when applied to data provided by spectrophotometric transducers and spectrophotometers. First, a general methodology of DSP applications in spectrophotometry, based on DSP-oriented models of spectrophotometric data, is outlined. Then, the most important classes of DSP methods for processing spectrophotometric data—the methods for DSP-aided calibration of spectrophotometric instrumentation, the methods for the estimation of spectra on the basis of spectrophotometric data, the methods for the estimation of spectrum-related measurands on the basis of spectrophotometric data—are presented. Finally, the methods for preprocessing and postprocessing of spectrophotometric data are overviewed. Throughout the review, the applications of DSP are illustrated with numerous examples related to broadly understood spectrophotometry.

  4. Digital signal processing techniques for coherent optical communication

    NASA Astrophysics Data System (ADS)

    Goldfarb, Gilad

    Coherent detection with subsequent digital signal processing (DSP) is developed, analyzed theoretically and numerically and experimentally demonstrated in various fiber-optic transmission scenarios. The use of DSP in conjunction with coherent detection unleashes the benefits of coherent detection which rely on the preservaton of full information of the incoming field. These benefits include high receiver sensitivity, the ability to achieve high spectral-efficiency and the use of advanced modulation formats. With the immense advancements in DSP speeds, many of the problems hindering the use of coherent detection in optical transmission systems have been eliminated. Most notably, DSP alleviates the need for hardware phase-locking and polarization tracking, which can now be achieved in the digital domain. The complexity previously associated with coherent detection is hence significantly diminished and coherent detection is once gain considered a feasible detection alternative. In this thesis, several aspects of coherent detection (with or without subsequent DSP) are addressed. Coherent detection is presented as a means to extend the dispersion limit of a duobinary signal using an analog decision-directed phase-lock loop. Analytical bit-error ratio estimation for quadrature phase-shift keying signals is derived. To validate the promise for high spectral efficiency, the orthogonal-wavelength-division multiplexing scheme is suggested. In this scheme the WDM channels are spaced at the symbol rate, thus achieving the spectral efficiency limit. Theory, simulation and experimental results demonstrate the feasibility of this approach. Infinite impulse response filtering is shown to be an efficient alternative to finite impulse response filtering for chromatic dispersion compensation. Theory, design considerations, simulation and experimental results relating to this topic are presented. Interaction between fiber dispersion and nonlinearity remains the last major challenge

  5. A nonlinear optoelectronic filter for electronic signal processing.

    PubMed

    Loh, William; Yegnanarayanan, Siva; Ram, Rajeev J; Juodawlkis, Paul W

    2014-01-09

    The conversion of electrical signals into modulated optical waves and back into electrical signals provides the capacity for low-loss radio-frequency (RF) signal transfer over optical fiber. Here, we show that the unique properties of this microwave-photonic link also enable the manipulation of RF signals beyond what is possible in conventional systems. We achieve these capabilities by realizing a novel nonlinear filter, which acts to suppress a stronger RF signal in the presence of a weaker signal independent of their separation in frequency. Using this filter, we demonstrate a relative suppression of 56 dB for a stronger signal having a 1-GHz center frequency, uncovering the presence of otherwise undetectable weaker signals located as close as 3.5 Hz away. The capabilities of the optoelectronic filter break the conventional limits of signal detection, opening up new possibilities for radar and communication systems, and for the field of precision frequency metrology.

  6. Spontaneous eye blinks during creative task correlate with divergent processing.

    PubMed

    Ueda, Yoshiyuki; Tominaga, Atsuko; Kajimura, Shogo; Nomura, Michio

    2016-07-01

    Creativity consists of divergent and convergent thinking, with both related to individual eye blinks at rest. To assess underlying mechanisms between eye blinks and traditional creativity tasks, we investigated the relationship between creativity performance and eye blinks at rest and during tasks. Participants performed an alternative uses and remote association task while eye blinks were recorded. Results showed that the relationship between eye blinks at rest and creativity performance was compatible with those of previous research. Interestingly, we found that the generation of ideas increased as a function of eye blink number during the alternative uses task. On the other hand, during the remote association task, accuracy was independent of eye blink number during the task, but response time increased with it. Moreover, eye blink changes in participants who responded quickly during the remote association task were different depending on their resting state eye blinks; that is, participants with many eye blinks during rest showed little increasing eye blinks and achieved solutions quickly. Positive correlations between eye blinks during creative tasks and yielding ideas on the alternative uses task and response time on the remote association task suggest that eye blinks during creativity tasks relate to divergent thinking processes such as conceptual reorganization.

  7. Optical hybrid analog-digital signal processing based on spike processing in neurons

    NASA Astrophysics Data System (ADS)

    Fok, Mable P.; Tian, Yue; Rosenbluth, David; Deng, Yanhua; Prucnal, Paul R.

    2011-09-01

    Spike processing is one kind of hybrid analog-digital signal processing, which has the efficiency of analog processing and the robustness to noise of digital processing. When instantiated with optics, a hybrid analog-digital processing primitive has the potential to be scalable, computationally powerful, and have high operation bandwidth. These devices open up a range of processing applications for which electronic processing is too slow. Our approach is based on a hybrid analog/digital computational primitive that elegantly implements the functionality of an integrate-and-fire neuron using a Ge-doped non-linear optical fiber and off-the-shelf semiconductor devices. In this paper, we introduce our photonic neuron architecture and demonstrate the feasibility of implementing simple photonic neuromorphic circuits, including the auditory localization algorithm of the barn owl, which is useful for LIDAR localization, and the crayfish tail-flip escape response.

  8. Quantifying process heterogeneity: Signal propagation in hydrological systems

    NASA Astrophysics Data System (ADS)

    Lischeid, G.; Merz, C.; Schindler, U.; Schulz, R.; Steidl, J.; Tauschke, R.

    2009-04-01

    Natural hydrological systems are characterized by heterogeneous structures. The typical length scale of the relevant structures is smaller than the resolution of area-covering methods that are available at the catchment-scale. On the other hand these structures are too large to be treated as random effects and are often related to hydrological behaviour in a non-linear way. Consequently, model results, risk assessments etc. are prone to substantial uncertainties. This is often addressed by random realizations of the structures based on given probability density functions and geostatistical properties, and then analysing the resulting effects on hydrological behaviour, e.g., discharge or groundwater table fluctuations, using process-based models. In this study an alternative approach was followed. Hydrological systems usually act as low-pass filters: An input signal (precipitation, groundwater recharge, tracer application, etc.) is damped and delayed during its passage through the system. This study aimed at characterizing the damping behaviour in a quantitative way. Large perturbations usually are transmitted at much higher velocities compared to small perturbations, thus hindering a spectrum analysis based approach. Instead, time series of soil water content, groundwater level and catchment runoff from the Uckermark region in North Germany were analysed using a principal component analysis. In all cases, the first component depicted the mean behaviour, and the second component explained a large fraction of the deviations from the mean behaviour. The loadings of the first two components could be used as an index of the mean damping behaviour for the given time period. Results of the soil water content data showed a linear increase of damping with depth at most sites. However, different sites differed substantially even for backfilled lysimeters that were considered to be homogeneous. There was no clear relationship between clay content and damping behaviour. The

  9. Correlation between light scattering signal and tissue reversibility in rat brain exposed to hypoxia

    NASA Astrophysics Data System (ADS)

    Kawauchi, Satoko; Sato, Shunichi; Uozumi, Yoichi; Nawashiro, Hiroshi; Ishihara, Miya; Kikuchi, Makoto

    2010-02-01

    Light scattering signal is a potential indicator of tissue viability in brain because cellular and subcellular structural integrity should be associated with cell viability in brain tissue. We previously performed multiwavelength diffuse reflectance measurement for a rat global ischemic brain model and observed a unique triphasic change in light scattering at a certain time after oxygen and glucose deprivation. This triphasic scattering change (TSC) was shown to precede cerebral ATP exhaustion, suggesting that loss of brain tissue viability can be predicted by detecting scattering signal. In the present study, we examined correlation between light scattering signal and tissue reversibility in rat brain in vivo. We performed transcranial diffuse reflectance measurement for rat brain; under spontaneous respiration, hypoxia was induced for the rat by nitrogen gas inhalation and reoxygenation was started at various time points. We observed a TSC, which started at 140 +/- 15 s after starting nitrogen gas inhalation (mean +/- SD, n=8). When reoxygenation was started before the TSC, all rats survived (n=7), while no rats survived when reoxygenation was started after the TSC (n=8). When reoxygenation was started during the TSC, rats survived probabilistically (n=31). Disability of motor function was not observed for the survived rats. These results indicate that TSC can be used as an indicator of loss of tissue reversibility in brains, providing useful information on the critical time zone for treatment to rescue the brain.

  10. From Bursts to Back-Projection: Signal Processing Techniques for Earth and Planetary Observing Radars

    NASA Technical Reports Server (NTRS)

    Rosen, Paul A.

    2012-01-01

    Discusses: (1) JPL Radar Overview and Historical Perspective (2) Signal Processing Needs in Earth and Planetary Radars (3) Examples of Current Systems and techniques (4) Future Perspectives in signal processing for radar missions

  11. Increasing signal processing sophistication in the calculation of the respiratory modulation of the photoplethysmogram (DPOP).

    PubMed

    Addison, Paul S; Wang, Rui; Uribe, Alberto A; Bergese, Sergio D

    2015-06-01

    DPOP (∆POP or Delta-POP) is a non-invasive parameter which measures the strength of respiratory modulations present in the pulse oximetry photoplethysmogram (pleth) waveform. It has been proposed as a non-invasive surrogate parameter for pulse pressure variation (PPV) used in the prediction of the response to volume expansion in hypovolemic patients. Many groups have reported on the DPOP parameter and its correlation with PPV using various semi-automated algorithmic implementations. The study reported here demonstrates the performance gains made by adding increasingly sophisticated signal processing components to a fully automated DPOP algorithm. A DPOP algorithm was coded and its performance systematically enhanced through a series of code module alterations and additions. Each algorithm iteration was tested on data from 20 mechanically ventilated OR patients. Correlation coefficients and ROC curve statistics were computed at each stage. For the purposes of the analysis we split the data into a manually selected 'stable' region subset of the data containing relatively noise free segments and a 'global' set incorporating the whole data record. Performance gains were measured in terms of correlation against PPV measurements in OR patients undergoing controlled mechanical ventilation. Through increasingly advanced pre-processing and post-processing enhancements to the algorithm, the correlation coefficient between DPOP and PPV improved from a baseline value of R = 0.347 to R = 0.852 for the stable data set, and, correspondingly, R = 0.225 to R = 0.728 for the more challenging global data set. Marked gains in algorithm performance are achievable for manually selected stable regions of the signals using relatively simple algorithm enhancements. Significant additional algorithm enhancements, including a correction for low perfusion values, were required before similar gains were realised for the more challenging global data set.

  12. Neural correlates of post-error slowing during a stop signal task: a functional magnetic resonance imaging study.

    PubMed

    Li, Chiang-shan Ray; Huang, Cong; Yan, Peisi; Paliwal, Prashni; Constable, Robert Todd; Sinha, Rajita

    2008-06-01

    The ability to detect errors and adjust behavior accordingly is essential for maneuvering in an uncertain environment. Errors are particularly prone to occur when multiple, conflicting responses are registered in a situation that requires flexible behavioral outputs; for instance, when a go signal requires a response and a stop signal requires inhibition of the response during a stop signal task (SST). Previous studies employing the SST have provided ample evidence indicating the importance of the medial cortical brain regions in conflict/error processing. Other studies have also related these regional activations to postconflict/error behavioral adjustment. However, very few studies have directly explored the neural correlates of postconflict/error behavioral adjustment. Here we employed an SST to elicit errors in approximately half of the stop trials despite constant behavioral adjustment of the observers. Using functional magnetic resonance imaging, we showed that prefrontal loci including the ventrolateral prefrontal cortex are involved in post-error slowing in reaction time. These results delineate the neural circuitry specifically involved in error-associated behavioral modifications.

  13. Correlation between signal input and output in PctA and PctB amino acid chemoreceptor of Pseudomonas aeruginosa.

    PubMed

    Reyes-Darias, José A; Yang, Yiling; Sourjik, Victor; Krell, Tino

    2015-05-01

    The PctA and PctB chemoreceptors of Pseudomonas aeruginosa mediate chemotaxis toward amino acids. A general feature of signal transduction processes is that a signal input is converted into an output. We have generated chimeras combining the Tar signaling domain with either the PctA or PctB ligand binding domain (LBD). Escherichia coli harboring either PctA-Tar or PctB-Tar mediated chemotaxis toward amino acids. The responses of both chimeras were determined using fluorescence resonance energy transfer, and the derived EC50 values are a measure of output. PctA-Tar and PctB-Tar responded to 19 and 11 L-amino acids respectively. The EC50 values of PctA-Tar responses differed by more than three orders of magnitude, whereas PctB-Tar responded preferentially to L-Gln. The comparison of amino acid binding constants and the corresponding EC50 values for both receptors revealed statistically significant correlations between inputs and outputs. PctA and PctB possess a double PDC (PhoQ-DcuS-CitA) LBD - a family of binding domain found in various other amino acid chemoreceptors. Similarly, various chemoreceptors share the preferential response to certain amino acids (e.g. L-Cys, L-Ser and L-Thr) that we observed for PctA. Defining the specific inputs and outputs of these chemoreceptors is an important step toward better understanding of their physiological role.

  14. Peta-Flop Real Time Radio Astronomy Signal Processing Instrumentation and the CASPER Collaboration

    NASA Astrophysics Data System (ADS)

    Werthimer, Dan

    2014-04-01

    I will briefly describe next generation radio telescopes, such as HERA and the Square Kilometer Array (SKA), which will require 1E15 to 1E17 operations per second of real time processing. I'll present some of the new architectures we've used to develop a variety of heterogeneous FPGA-GPU-CPU based signal processing systems for such telescopes, including spectrometers, correlators, and beam formers. I will also describe the CASPER collaboration, which has developed architectures, open source programming tools, libraries and reference designs that make it relatively easy to develop a variety of scalable, upgradeable, fault tolerant, low power, real time digital signal processing instrumentation. CASPER utilizes commercial 10Gbit and 40 Gbit ethernet switches to interconnect open source general purpose field programmable gate array (FPGA) boards with GPUs and software modules. CASPER collaborators at hundreds of universities, government labs and observatories have used these techniques to rapidly develop and deploy a variety of correlators, beamformers, spectrometers, pulsar/transient machines, and VLBI instrumentation. CASPER instrumentation is also utilized in physics, medicine, genomics and engineering. Open source source hardware, software, libraries, tools, tutorials, reference designs, information about workshops, and how to join the collaboration are available at http://casper.berkeley.edu

  15. Characterization of Pairwise Correlations from Multiple Quantum Correlated Beams Generated from Cascaded Four-Wave Mixing Processes

    PubMed Central

    Wang, Hailong; Cao, Leiming; Jing, Jietai

    2017-01-01

    We theoretically characterize the performance of the pairwise correlations (PCs) from multiple quantum correlated beams based on the cascaded four-wave mixing (FWM) processes. The presence of the PCs with quantum corre- lation in these systems can be verified by calculating the degree of intensity difference squeezing for any pair of all the output fields. The quantum correlation characteristics of all the PCs under different cascaded schemes are also discussed in detail and the repulsion effect between PCs in these cascaded FWM processes is theoretically predicted. Our results open the way for the classification and application of quantum states generated from the cascaded FWM processes. PMID:28071759

  16. Periodically correlated random processes: Application in early diagnostics of mechanical systems

    NASA Astrophysics Data System (ADS)

    Javorskyj, I.; Kravets, I.; Matsko, I.; Yuzefovych, R.

    2017-01-01

    The covariance and spectral characteristics of periodically correlated random processes (PCRP) are used to describe the state of rotary mechanical systems and in their fault detection. The methods for estimation of mean function, covariance function, instantaneous spectral density and their Fourier coefficients for a given class of non-stationary random processes on the basis of experimental data, namely: the synchronous averaging, component, least squares method and linear filtration methods are considered. The first and second order periodicity detection methods are used for vibration signals analysis. A method for mechanical system fault identification and classification based on a harmonic series representation is developed. Examples of fault detection in rolling/sliding bearings and gearboxes are given.

  17. Advanced Signal Processing for High Temperatures Health Monitoring of Condensed Water Height in Steam Pipes

    NASA Technical Reports Server (NTRS)

    Lih, Shyh-Shiuh; Bar-Cohen, Yoseph; Lee, Hyeong Jae; Takano, Nobuyuki; Bao, Xiaoqi

    2013-01-01

    An advanced signal processing methodology is being developed to monitor the height of condensed water thru the wall of a steel pipe while operating at temperatures as high as 250deg. Using existing techniques, previous study indicated that, when the water height is low or there is disturbance in the environment, the predicted water height may not be accurate. In recent years, the use of the autocorrelation and envelope techniques in the signal processing has been demonstrated to be a very useful tool for practical applications. In this paper, various signal processing techniques including the auto correlation, Hilbert transform, and the Shannon Energy Envelope methods were studied and implemented to determine the water height in the steam pipe. The results have shown that the developed method provides a good capability for monitoring the height in the regular conditions. An alternative solution for shallow water or no water conditions based on a developed hybrid method based on Hilbert transform (HT) with a high pass filter and using the optimized windowing technique is suggested. Further development of the reported methods would provide a powerful tool for the identification of the disturbances of water height inside the pipe.

  18. Multiple Source DF (Direction Finding) Signal Processing: An Experimental System,

    DTIC Science & Technology

    The MUltiple SIgnal Characterization ( MUSIC ) algorithm is an implementation of the Signal Subspace Approach to provide parameter estimates of...the signal subspace (obtained from the received data) and the array manifold (obtained via array calibration). The MUSIC algorithm has been

  19. Optimal Signal Processing of Frequency-Stepped CW Radar Data

    NASA Technical Reports Server (NTRS)

    Ybarra, Gary A.; Wu, Shawkang M.; Bilbro, Griff L.; Ardalan, Sasan H.; Hearn, Chase P.; Neece, Robert T.

    1995-01-01

    An optimal signal processing algorithm is derived for estimating the time delay and amplitude of each scatterer reflection using a frequency-stepped CW system. The channel is assumed to be composed of abrupt changes in the reflection coefficient profile. The optimization technique is intended to maximize the target range resolution achievable from any set of frequency-stepped CW radar measurements made in such an environment. The algorithm is composed of an iterative two-step procedure. First, the amplitudes of the echoes are optimized by solving an overdetermined least squares set of equations. Then, a nonlinear objective function is scanned in an organized fashion to find its global minimum. The result is a set of echo strengths and time delay estimates. Although this paper addresses the specific problem of resolving the time delay between the first two echoes, the derivation is general in the number of echoes. Performance of the optimization approach is illustrated using measured data obtained from an HP-X510 network analyzer. It is demonstrated that the optimization approach offers a significant resolution enhancement over the standard processing approach that employs an IFFT. Degradation in the performance of the algorithm due to suboptimal model order selection and the effects of additive white Gaussion noise are addressed.

  20. Optimal Signal Processing of Frequency-Stepped CW Radar Data

    NASA Technical Reports Server (NTRS)

    Ybarra, Gary A.; Wu, Shawkang M.; Bilbro, Griff L.; Ardalan, Sasan H.; Hearn, Chase P.; Neece, Robert T.

    1995-01-01

    An optimal signal processing algorithm is derived for estimating the time delay and amplitude of each scatterer reflection using a frequency-stepped CW system. The channel is assumed to be composed of abrupt changes in the reflection coefficient profile. The optimization technique is intended to maximize the target range resolution achievable from any set of frequency-stepped CW radar measurements made in such an environment. The algorithm is composed of an iterative two-step procedure. First, the amplitudes of the echoes are optimized by solving an overdetermined least squares set of equations. Then, a nonlinear objective function is scanned in an organized fashion to find its global minimum. The result is a set of echo strengths and time delay estimates. Although this paper addresses the specific problem of resolving the time delay between the two echoes, the derivation is general in the number of echoes. Performance of the optimization approach is illustrated using measured data obtained from an HP-851O network analyzer. It is demonstrated that the optimization approach offers a significant resolution enhancement over the standard processing approach that employs an IFFT. Degradation in the performance of the algorithm due to suboptimal model order selection and the effects of additive white Gaussion noise are addressed.