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Sample records for ground signal processing

  1. Work flow of signal processing data of ground penetrating radar case of rigid pavement measurements

    Energy Technology Data Exchange (ETDEWEB)

    Handayani, Gunawan [The Earth Physics and Complex Systems Research Group (Jl. Ganesa 10 Bandung Indonesia) gunawanhandayani@gmail.com (Indonesia)

    2015-04-16

    The signal processing of Ground Penetrating Radar (GPR) requires a certain work flow to obtain good results. Even though the Ground Penetrating Radar data looks similar with seismic reflection data, but the GPR data has particular signatures that the seismic reflection data does not have. This is something to do with coupling between antennae and the ground surface. Because of this, the GPR data should be treated differently from the seismic signal data processing work flow. Even though most of the processing steps still follow the same work flow of seismic reflection data such as: filtering, predictive deconvolution etc. This paper presents the work flow of GPR processing data on rigid pavement measurements. The processing steps start from raw data, de-Wow process, remove DC and continue with the standard process to get rid of noises i.e. filtering process. Some radargram particular features of rigid pavement along with pile foundations are presented.

  2. Work flow of signal processing data of ground penetrating radar case of rigid pavement measurements

    Science.gov (United States)

    Handayani, Gunawan

    2015-04-01

    The signal processing of Ground Penetrating Radar (GPR) requires a certain work flow to obtain good results. Even though the Ground Penetrating Radar data looks similar with seismic reflection data, but the GPR data has particular signatures that the seismic reflection data does not have. This is something to do with coupling between antennae and the ground surface. Because of this, the GPR data should be treated differently from the seismic signal data processing work flow. Even though most of the processing steps still follow the same work flow of seismic reflection data such as: filtering, predictive deconvolution etc. This paper presents the work flow of GPR processing data on rigid pavement measurements. The processing steps start from raw data, de-Wow process, remove DC and continue with the standard process to get rid of noises i.e. filtering process. Some radargram particular features of rigid pavement along with pile foundations are presented.

  3. Processing the ground vibration signal produced by debris flows: the methods of amplitude and impulses compared

    Science.gov (United States)

    Arattano, M.; Abancó, C.; Coviello, V.; Hürlimann, M.

    2014-12-01

    Ground vibration sensors have been increasingly used and tested, during the last few years, as devices to monitor debris flows and they have also been proposed as one of the more reliable devices for the design of debris flow warning systems. The need to process the output of ground vibration sensors, to diminish the amount of data to be recorded, is usually due to the reduced storing capabilities and the limited power supply, normally provided by solar panels, available in the high mountain environment. There are different methods that can be found in literature to process the ground vibration signal produced by debris flows. In this paper we will discuss the two most commonly employed: the method of impulses and the method of amplitude. These two methods of data processing are analyzed describing their origin and their use, presenting examples of applications and their main advantages and shortcomings. The two methods are then applied to process the ground vibration raw data produced by a debris flow occurred in the Rebaixader Torrent (Spanish Pyrenees) in 2012. The results of this work will provide means for decision to researchers and technicians who find themselves facing the task of designing a debris flow monitoring installation or a debris flow warning equipment based on the use of ground vibration detectors.

  4. Advanced signal processing method for ground penetrating radar feature detection and enhancement

    Science.gov (United States)

    Zhang, Yu; Venkatachalam, Anbu Selvam; Huston, Dryver; Xia, Tian

    2014-03-01

    This paper focuses on new signal processing algorithms customized for an air coupled Ultra-Wideband (UWB) Ground Penetrating Radar (GPR) system targeting highway pavements and bridge deck inspections. The GPR hardware consists of a high-voltage pulse generator, a high speed 8 GSps real time data acquisition unit, and a customized field-programmable gate array (FPGA) control element. In comparison to most existing GPR system with low survey speeds, this system can survey at normal highway speed (60 mph) with a high horizontal resolution of up to 10 scans per centimeter. Due to the complexity and uncertainty of subsurface media, the GPR signal processing is important but challenging. In this GPR system, an adaptive GPR signal processing algorithm using Curvelet Transform, 2D high pass filtering and exponential scaling is proposed to alleviate noise and clutter while the subsurface features are preserved and enhanced. First, Curvelet Transform is used to remove the environmental and systematic noises while maintain the range resolution of the B-Scan image. Then, mathematical models for cylinder-shaped object and clutter are built. A two-dimension (2D) filter based on these models removes clutter and enhances the hyperbola feature in a B-Scan image. Finally, an exponential scaling method is applied to compensate the signal attenuation in subsurface materials and to improve the desired signal feature. For performance test and validation, rebar detection experiments and subsurface feature inspection in laboratory and field configurations are performed.

  5. Signature of magmatic processes in ground deformation signals from Phlegraean Fields (Italy)

    Science.gov (United States)

    Bagagli, Matteo; Montagna, Chiara Paola; Longo, Antonella; Papale, Paolo

    2016-04-01

    Ground deformation signals such as dilatometric and tiltmetric ones, are nowadays well studied from the vulcanological community all over the world. These signals can be used to retrieve information on volcanoes state and to study the magma dynamics in their plumbing system. We compared synthetic signals in the Very Long Period (VLP, 10-2 - 10-1 Hz) and Ultra Long Period (ULP, 10-4 - 10-2 Hz) bands obtained from the simulation of magma mixing in shallow reservoirs ([3],[4]) with real data obtained from the dilatometers and tiltmeters network situated in the Phlegraean Fields near Naples (Italy), in order to define and constrain the relationships between them. Analyses of data from the October 2006 seismic swarm in the area show that the frequency spectrum of the synthetics is remarkably similar to the transient present in the real signals. In depth studies with accurated techniques for spectral analysis (i.e wavelet transform) and application of this method to other time windows have identified in the bandwidth around 10-4Hz (between 1h30m and 2h45m) peaks that are fairly stable and independent from the processing carried out on the full-band signal. These peaks could be the signature of ongoing convection at depth. It is well known that re-injection of juvenile magmas can reactivate the eruption dynamics ([1],[2]), thus being able to define mixing markers and detect them in the ground deformation signals is a relevant topic in order to understand the dynamics of active and quiescent vulcanoes and to eventually improve early-warning methods for impending eruptions. [1] Arienzo, I. et al. (2010). "The feeding system of Agnano-Monte Spina eruption (Campi Flegrei, Italy): dragging the past into present activity and future scenarios". In: Chemical Geology 270.1, pp. 135-147. [2] Bachmann, Olivier and George Bergantz (2008). "The magma reservoirs that feed supereruptions". In: Elements 4.1, pp. 17-21. [3] Longo, Antonella et al. (2012). "Magma convection and mixing

  6. Ground-penetrating radar signal processing for the detection of buried objects

    Science.gov (United States)

    Walters, Mitchell; Garcia, Ephrahim

    2011-06-01

    In this work the singular value decomposition (SVD) is used to analyze matrices of ground penetrating radar (GPR) data. The targets to be detected are Russian PMN antipersonnel landmines and improvised explosive devices constructed from 155mm artillery shells. Target responses are simulated with GPRmax 2D, a simulation package based on the Finite- Difference-Time-Domain method. First, the utility of the SVD for image enhancement and reconstruction is demonstrated. Then the singular values and singular vectors of the decomposed matrices are analyzed with the goal of finding properties that will aid in the development of automated underground detection algorithms.

  7. Signal Processing

    Science.gov (United States)

    1989-03-01

    34ESPIRIT Estimation of signal parameters via rotational imvariance techin+I,-- 1\\I111;1 Smith. A. Faradani "Local and ( Moba ! tomography" I’ Nitlerer and...Feb 1 - Jul 30 Friedman, Avner IMA Gader, Paul University of Wisconsin Jun 27 - Jul 24 Games , Richard MITRE Corp Jun 27 - Aug 5 Garvan, Francis U. of...Gader, Paul University of Wisconsin Jun 27 - Jul 24 Games , Richard MITRE Corp Jun 27 - Aug 5 Garvan, Francis U. of Wisconsin Jun 26 - Jul 31 Habsieger

  8. PALSAR ground data processing

    Science.gov (United States)

    Frick, Heinrich; Palsetia, Marzban; Carande, Richard; Curlander, James C.

    2002-02-01

    The upcoming launches of new satellites like ALOS, Envisat, Radarsat2 and ECHO will pose a significant challenge for many ground stations, namely to integrate new SAR processing software into their existing systems. Vexcel Corporation in Boulder, Colorado, has built a SAR processing system, named APEX -Suite, for spaceborne SAR satellites that can easily be expanded for the next generation of SAR satellites. APEX-Suite includes an auto-satellite-detecting Level 0 Processor that includes bit-error correction, data quality characterization, and as a unique feature, a sophisticated and very accurate Doppler centroid estimator. The Level 1 processing is divided into the strip mode processor FOCUST, based on the well-proven range-Doppler algorithm, and the SWATHT ScanSAR processor that uses the Chirp Z Trans-form algorithm. A high-accuracy ortho-rectification processor produces systematic and precision corrected Level 2 SAR image pro ducts. The PALSAR instrument is an L-band SAR with multiple fine and standard resolution beams in strip mode, and several wide-swath ScanSAR modes. We will address the adaptation process of Vexcel's APEX-Suite processing system for the PALSAR sensor and discuss image quality characteristics based on processed simulated point target phase history data.

  9. Spacelab Ground Processing

    Science.gov (United States)

    Scully, Edward J.; Gaskins, Roger B.

    1982-02-01

    Spacelab (SL) ground processing is active at the Kennedy Space Center (KSC). The palletized payload for the second Shuttle launch is staged and integrated with interface verification active. The SL Engineering Model is being assembled for subsequent test and checkout activities. After delivery of SL flight elements from Europe, prelaunch operations for the first SL flight start with receipt of the flight experiment packages and staging of the SL hardware. Experiment operations consist of integrating the various experiment elements into the SL racks, floors and pallets. Rack and floor assemblies with the experiments installed, are integrated into the flight module. Aft end-cone installation, pallet connections, and SL subsystems interface verifications are accomplished, and SL-Orbiter interfaces verified. The Spacelab cargo is then transferred to the Orbiter Processing Facility (OPF) in a controlled environment using a canister/transporter. After the SL is installed into the Orbiter payload bay, physical and functional integrity of all payload-to-Orbiter interfaces are verified and final close-out operations conducted. Spacelab payload activities at the launch pad are minimal with the payload bay doors remaining closed. Limited access is available to the module through the Spacelab Transfer Tunnel. After mission completion, the SL is removed from the Orbiter in the OPF and returned to the SL processing facility for experiment equipment removal and reconfiguration for the subsequent mission.

  10. Basic digital signal processing

    CERN Document Server

    Lockhart, Gordon B

    1985-01-01

    Basic Digital Signal Processing describes the principles of digital signal processing and experiments with BASIC programs involving the fast Fourier theorem (FFT). The book reviews the fundamentals of the BASIC program, continuous and discrete time signals including analog signals, Fourier analysis, discrete Fourier transform, signal energy, power. The text also explains digital signal processing involving digital filters, linear time-variant systems, discrete time unit impulse, discrete-time convolution, and the alternative structure for second order infinite impulse response (IIR) sections.

  11. Acoustic Signal Processing

    Science.gov (United States)

    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.

  12. Biomedical signal processing

    CERN Document Server

    Akay, Metin

    1994-01-01

    Sophisticated techniques for signal processing are now available to the biomedical specialist! Written in an easy-to-read, straightforward style, Biomedical Signal Processing presents techniques to eliminate background noise, enhance signal detection, and analyze computer data, making results easy to comprehend and apply. In addition to examining techniques for electrical signal analysis, filtering, and transforms, the author supplies an extensive appendix with several computer programs that demonstrate techniques presented in the text.

  13. Digital signal processing laboratory

    CERN Document Server

    Kumar, B Preetham

    2011-01-01

    INTRODUCTION TO DIGITAL SIGNAL PROCESSING Brief Theory of DSP ConceptsProblem SolvingComputer Laboratory: Introduction to MATLAB®/SIMULINK®Hardware Laboratory: Working with Oscilloscopes, Spectrum Analyzers, Signal SourcesDigital Signal Processors (DSPs)ReferencesDISCRETE-TIME LTI SIGNALS AND SYSTEMS Brief Theory of Discrete-Time Signals and SystemsProblem SolvingComputer Laboratory: Simulation of Continuous Time and Discrete-Time Signals and Systems ReferencesTIME AND FREQUENCY ANALYSIS OF COMMUNICATION SIGNALS Brief Theory of Discrete-Time Fourier Transform (DTFT), Discrete Fourier Transform

  14. Ultrahigh bandwidth signal processing

    DEFF Research Database (Denmark)

    Oxenløwe, Leif Katsuo

    2016-01-01

    Optical time lenses have proven to be very versatile for advanced optical signal processing. Based on a controlled interplay between dispersion and phase-modulation by e.g. four-wave mixing, the processing is phase-preserving, an hence useful for all types of data signals including coherent multi......-level modulation founats. This has enabled processing of phase-modulated spectrally efficient data signals, such as orthogonal frequency division multiplexed (OFDM) signa In that case, a spectral telescope system was used, using two time lenses with different focal lengths (chirp rates), yielding a spectral...... regeneratio These operations require a broad bandwidth nonlinear platform, and novel photonic integrated nonlinear platform like aluminum gallium arsenide nano-waveguides used for 1.28 Tbaud optical signal processing will be described....

  15. Acoustic MIMO signal processing

    CERN Document Server

    Huang, Yiteng; Chen, Jingdong

    2006-01-01

    A timely and important book addressing a variety of acoustic signal processing problems under multiple-input multiple-output (MIMO) scenarios. It uniquely investigates these problems within a unified framework offering a novel and penetrating analysis.

  16. Digital signal processing

    CERN Document Server

    O'Shea, Peter; Hussain, Zahir M

    2011-01-01

    In three parts, this book contributes to the advancement of engineering education and that serves as a general reference on digital signal processing. Part I presents the basics of analog and digital signals and systems in the time and frequency domain. It covers the core topics: convolution, transforms, filters, and random signal analysis. It also treats important applications including signal detection in noise, radar range estimation for airborne targets, binary communication systems, channel estimation, banking and financial applications, and audio effects production. Part II considers sel

  17. Digital signal processing: Handbook

    Science.gov (United States)

    Goldenberg, L. M.; Matiushkin, B. D.; Poliak, M. N.

    The fundamentals of the theory and design of systems and devices for the digital processing of signals are presented. Particular attention is given to algorithmic methods of synthesis and digital processing equipment in communication systems (e.g., selective digital filtering, spectral analysis, and variation of the signal discretization frequency). Programs for the computer-aided analysis of digital filters are described. Computational examples are presented, along with tables of transfer function coefficients for recursive and nonrecursive digital filters.

  18. Topological signal processing

    CERN Document Server

    Robinson, Michael

    2014-01-01

    Signal processing is the discipline of extracting information from collections of measurements. To be effective, the measurements must be organized and then filtered, detected, or transformed to expose the desired information.  Distortions caused by uncertainty, noise, and clutter degrade the performance of practical signal processing systems. In aggressively uncertain situations, the full truth about an underlying signal cannot be known.  This book develops the theory and practice of signal processing systems for these situations that extract useful, qualitative information using the mathematics of topology -- the study of spaces under continuous transformations.  Since the collection of continuous transformations is large and varied, tools which are topologically-motivated are automatically insensitive to substantial distortion. The target audience comprises practitioners as well as researchers, but the book may also be beneficial for graduate students.

  19. Ultrahigh bandwidth signal processing

    Science.gov (United States)

    Oxenløwe, Leif Katsuo

    2016-04-01

    Optical time lenses have proven to be very versatile for advanced optical signal processing. Based on a controlled interplay between dispersion and phase-modulation by e.g. four-wave mixing, the processing is phase-preserving, and hence useful for all types of data signals including coherent multi-level modulation formats. This has enabled processing of phase-modulated spectrally efficient data signals, such as orthogonal frequency division multiplexed (OFDM) signals. In that case, a spectral telescope system was used, using two time lenses with different focal lengths (chirp rates), yielding a spectral magnification of the OFDM signal. Utilising such telescopic arrangements, it has become possible to perform a number of interesting functionalities, which will be described in the presentation. This includes conversion from OFDM to Nyquist WDM, compression of WDM channels to a single Nyquist channel and WDM regeneration. These operations require a broad bandwidth nonlinear platform, and novel photonic integrated nonlinear platforms like aluminum gallium arsenide nano-waveguides used for 1.28 Tbaud optical signal processing will be described.

  20. VLSI signal processing technology

    CERN Document Server

    Swartzlander, Earl

    1994-01-01

    This book is the first in a set of forthcoming books focussed on state-of-the-art development in the VLSI Signal Processing area. It is a response to the tremendous research activities taking place in that field. These activities have been driven by two factors: the dramatic increase in demand for high speed signal processing, especially in consumer elec­ tronics, and the evolving microelectronic technologies. The available technology has always been one of the main factors in determining al­ gorithms, architectures, and design strategies to be followed. With every new technology, signal processing systems go through many changes in concepts, design methods, and implementation. The goal of this book is to introduce the reader to the main features of VLSI Signal Processing and the ongoing developments in this area. The focus of this book is on: • Current developments in Digital Signal Processing (DSP) pro­ cessors and architectures - several examples and case studies of existing DSP chips are discussed in...

  1. Genomic signal processing

    CERN Document Server

    Shmulevich, Ilya

    2007-01-01

    Genomic signal processing (GSP) can be defined as the analysis, processing, and use of genomic signals to gain biological knowledge, and the translation of that knowledge into systems-based applications that can be used to diagnose and treat genetic diseases. Situated at the crossroads of engineering, biology, mathematics, statistics, and computer science, GSP requires the development of both nonlinear dynamical models that adequately represent genomic regulation, and diagnostic and therapeutic tools based on these models. This book facilitates these developments by providing rigorous mathema

  2. RASSP signal processing architectures

    Science.gov (United States)

    Shirley, Fred; Bassett, Bob; Letellier, J. P.

    1995-06-01

    The rapid prototyping of application specific signal processors (RASSP) program is an ARPA/tri-service effort to dramatically improve the process by which complex digital systems, particularly embedded signal processors, are specified, designed, documented, manufactured, and supported. The domain of embedded signal processing was chosen because it is important to a variety of military and commercial applications as well as for the challenge it presents in terms of complexity and performance demands. The principal effort is being performed by two major contractors, Lockheed Sanders (Nashua, NH) and Martin Marietta (Camden, NJ). For both, improvements in methodology are to be exercised and refined through the performance of individual 'Demonstration' efforts. The Lockheed Sanders' Demonstration effort is to develop an infrared search and track (IRST) processor. In addition, both contractors' results are being measured by a series of externally administered (by Lincoln Labs) six-month Benchmark programs that measure process improvement as a function of time. The first two Benchmark programs are designing and implementing a synthetic aperture radar (SAR) processor. Our demonstration team is using commercially available VME modules from Mercury Computer to assemble a multiprocessor system scalable from one to hundreds of Intel i860 microprocessors. Custom modules for the sensor interface and display driver are also being developed. This system implements either proprietary or Navy owned algorithms to perform the compute-intensive IRST function in real time in an avionics environment. Our Benchmark team is designing custom modules using commercially available processor ship sets, communication submodules, and reconfigurable logic devices. One of the modules contains multiple vector processors optimized for fast Fourier transform processing. Another module is a fiberoptic interface that accepts high-rate input data from the sensors and provides video-rate output data to a

  3. Adaptive Signal Processing Testbed

    Science.gov (United States)

    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.

  4. Signal Processing of Random Physiological Signals

    CERN Document Server

    Lessard, Charles

    2006-01-01

    Signal Processing of Random Physiological Signals presents the most widely used techniques in signal and system analysis. Specifically, the book is concerned with methods of characterizing signals and systems. Author Charles Lessard provides students and researchers an understanding of the time and frequency domain processes which may be used to evaluate random physiological signals such as brainwave, sleep, respiratory sounds, heart valve sounds, electromyograms, and electro-oculograms.Another aim of the book is to have the students evaluate actual mammalian data without spending most or all

  5. Phonocardiography Signal Processing

    CERN Document Server

    Abbas, Abbas K

    2009-01-01

    The auscultation method is an important diagnostic indicator for hemodynamic anomalies. Heart sound classification and analysis play an important role in the auscultative diagnosis. The term phonocardiography refers to the tracing technique of heart sounds and the recording of cardiac acoustics vibration by means of a microphone-transducer. Therefore, understanding the nature and source of this signal is important to give us a tendency for developing a competent tool for further analysis and processing, in order to enhance and optimize cardiac clinical diagnostic approach. This book gives the

  6. Signal processing unit

    Energy Technology Data Exchange (ETDEWEB)

    Boswell, J.

    1983-01-01

    The architecture of the signal processing unit (SPU) comprises an ROM connected to a program bus, and an input-output bus connected to a data bus and register through a pipeline multiplier accumulator (pmac) and a pipeline arithmetic logic unit (palu), each associated with a random access memory (ram1,2). The system pulse frequency is from 20 mhz. The pmac is further detailed, and has a capability of 20 mega operations per second. There is also a block diagram for the palu, showing interconnections between the register block (rbl), separator for bus (bs), register (reg), shifter (sh) and combination unit. The first and second rams have formats 64*16 and 32*32 bits, respectively. Further data are a 5-v power supply and 2.5 micron n-channel silicon gate mos technology with about 50000 transistors.

  7. Signals and processing for random signal radars

    Science.gov (United States)

    Moore, G. S.

    1980-06-01

    Signals and associated processing techniques are developed which improve the performance, simplify the implementation, and are more amenable to adaptive operation for radars using the random signal concept. These goals are accomplished through the use of a signal set that is composed of a deterministic spreading function, a binary random or pseudo-random noise source, and a possibly random or pseudo-random pulsing sequence. Techniques are developed for determining the parameters of the spreading function that result in signals with desirable ambiguity functions and high effective power. These techniques are based on the use of window functions for sidelobe control and the theory of chirp waveforms for effective power enhancement.

  8. Machine intelligence and signal processing

    CERN Document Server

    Vatsa, Mayank; Majumdar, Angshul; Kumar, Ajay

    2016-01-01

    This book comprises chapters on key problems in machine learning and signal processing arenas. The contents of the book are a result of a 2014 Workshop on Machine Intelligence and Signal Processing held at the Indraprastha Institute of Information Technology. Traditionally, signal processing and machine learning were considered to be separate areas of research. However in recent times the two communities are getting closer. In a very abstract fashion, signal processing is the study of operator design. The contributions of signal processing had been to device operators for restoration, compression, etc. Applied Mathematicians were more interested in operator analysis. Nowadays signal processing research is gravitating towards operator learning – instead of designing operators based on heuristics (for example wavelets), the trend is to learn these operators (for example dictionary learning). And thus, the gap between signal processing and machine learning is fast converging. The 2014 Workshop on Machine Intel...

  9. Biomedical signal and image processing

    CERN Document Server

    Najarian, Kayvan

    2012-01-01

    INTRODUCTION TO DIGITAL SIGNAL AND IMAGE PROCESSINGSignals and Biomedical Signal ProcessingIntroduction and OverviewWhat is a ""Signal""?Analog, Discrete, and Digital SignalsProcessing and Transformation of SignalsSignal Processing for Feature ExtractionSome Characteristics of Digital ImagesSummaryProblemsFourier TransformIntroduction and OverviewOne-Dimensional Continuous Fourier TransformSampling and NYQUIST RateOne-Dimensional Discrete Fourier TransformTwo-Dimensional Discrete Fourier TransformFilter DesignSummaryProblemsImage Filtering, Enhancement, and RestorationIntroduction and Overview

  10. Multidimensional signal processing for ultrasonic signal classification

    Science.gov (United States)

    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.

  11. Chaotic signal processing: information aspects

    CERN Document Server

    Andreyev, Y V; Efremova, E V; Anagnostopoulos, A N

    2003-01-01

    One of the features of chaotic signals that make them different of other types of signals is their special information properties. In this paper, we investigate the effect of these properties on the procedures of chaotic signal processing. On examples of cleaning chaotic signals off noise, chaotic synchronization and separation of chaotic signals we demonstrate the existence of basic limits imposed by information theory on chaotic signal processing, independent of concrete algorithms. Relations of these limits with the Second law, Shannon theorems and Landauer principle are discussed.

  12. Introduction to digital signal processing

    CERN Document Server

    Kuc, Roman

    2008-01-01

    This book approaches digital Signal Processing and filter design in a Novel way, by presenting the relevant theory and then having the Student apply it by implementing signal processing routines on a computer. This mixture of theory and application has worked successfully. With this approach, the students receive a deeper and intuitive understanding of the theory, its applications and its limitations. This text also includes projects that require students to write Computer programs to accomplish signal processing projects.

  13. Software Defined Radio for processing GNSS signals

    OpenAIRE

    Martinez Gutierrez, Sara

    2014-01-01

    GPS satellites are fitted with atomic clocks, in which it relapses the main objective of this project, to recover some of their accuracy and stability on a ground based receiver. This project describes the fundamentals of GPS signals, the assembly of the installation implemented to process them in software and the corresponding experiments. In order to achieve the software processing, a USB DVB-T dongle is connected to an active antenna and to the computer. As mentioned, one of...

  14. Algorithm of sky-ground-wave signal separation in CDMA system

    Institute of Scientific and Technical Information of China (English)

    Zhang Jingjuan; Chen Shiru

    2008-01-01

    To solve the problem of the sky-wave interference in radio positioning system operating in CDMA mode, an algorithm of sky-ground-wave separation is provided. Based on the MLE (maximum likelihood estimate),and by estimating the amplitude and the phase of the sky-wave signal, the provided algorithm for separating sky-ground-wave is implemented. The mathematics model used for signal processing is established, and the possible solutions are provided. The structure and signal processing flow implementing the presented algorithm in the receiver are presented. A multi-channels signal searching idea is adopted, some of which process the sky-wave signal, and some of which process the ground-wave signal. Numerical analysis and simulation show that the proposed algorithm has higher accuracy, more rapid processing speed, and simpler implementation for the estimation of the sky-wave signal parameter, and can separate the sky-wave signal and ground-wave signal from the arrival combination signal effectively.

  15. Fundamentals of statistical signal processing

    CERN Document Server

    Kay, Steven M

    1993-01-01

    A unified presentation of parameter estimation for those involved in the design and implementation of statistical signal processing algorithms. Covers important approaches to obtaining an optimal estimator and analyzing its performance; and includes numerous examples as well as applications to real- world problems. MARKETS: For practicing engineers and scientists who design and analyze signal processing systems, i.e., to extract information from noisy signals — radar engineer, sonar engineer, geophysicist, oceanographer, biomedical engineer, communications engineer, economist, statistician, physicist, etc.

  16. Parallel Computers in Signal Processing

    Directory of Open Access Journals (Sweden)

    Narsingh Deo

    1985-07-01

    Full Text Available Signal processing often requires a great deal of raw computing power for which it is important to take a look at parallel computers. The paper reviews various types of parallel computer architectures from the viewpoint of signal and image processing.

  17. Advanced planning for ISS payload ground processing

    Science.gov (United States)

    Page, Kimberly A.

    2000-01-01

    Ground processing at John F. Kennedy Space Center (KSC) is the concluding phase of the payload/flight hardware development process and is the final opportunity to ensure safe and successful recognition of mission objectives. Planning for the ground processing of on-orbit flight hardware elements and payloads for the International Space Station is a responsibility taken seriously at KSC. Realizing that entering into this operational environment can be an enormous undertaking for a payload customer, KSC continually works to improve this process by instituting new/improved services for payload developer/owner, applying state-of-the-art technologies to the advanced planning process, and incorporating lessons learned for payload ground processing planning to ensure complete customer satisfaction. This paper will present an overview of the KSC advanced planning activities for ISS hardware/payload ground processing. It will focus on when and how KSC begins to interact with the payload developer/owner, how that interaction changes (and grows) throughout the planning process, and how KSC ensures that advanced planning is successfully implemented at the launch site. It will also briefly consider the type of advance planning conducted by the launch site that is transparent to the payload user but essential to the successful processing of the payload (i.e. resource allocation, executing documentation, etc.) .

  18. Digital Signal Processing applied to Physical Signals

    CERN Document Server

    Alberto, Diego; Musa, L

    2011-01-01

    It is well known that many of the scientific and technological discoveries of the XXI century will depend on the capability of processing and understanding a huge quantity of data. With the advent of the digital era, a fully digital and automated treatment can be designed and performed. From data mining to data compression, from signal elaboration to noise reduction, a processing is essential to manage and enhance features of interest after every data acquisition (DAQ) session. In the near future, science will go towards interdisciplinary research. In this work there will be given an example of the application of signal processing to different fields of Physics from nuclear particle detectors to biomedical examinations. In Chapter 1 a brief description of the collaborations that allowed this thesis is given, together with a list of the publications co-produced by the author in these three years. The most important notations, definitions and acronyms used in the work are also provided. In Chapter 2, the last r...

  19. Handbook of signal processing systems

    CERN Document Server

    Deprettere, Ed; Leupers, Rainer; Takala, Jarmo

    2013-01-01

    Handbook of Signal Processing Systems is organized in three parts. The first part motivates representative applications that drive and apply state-of-the art methods for design and implementation of signal processing systems; the second part discusses architectures for implementing these applications; the third part focuses on compilers and simulation tools, describes models of computation and their associated design tools and methodologies. This handbook is an essential tool for professionals in many fields and researchers of all levels.

  20. Microsystem for signal processing applications

    Science.gov (United States)

    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.

  1. Passive localization processing for tactical unattended ground sensors

    Energy Technology Data Exchange (ETDEWEB)

    Ng, L.C.; Breitfeller, E.F.

    1995-09-01

    This report summarizes our preliminary results of a development effort to assess the potential capability of a system of unattended ground sensors to detect, classify, and localize underground sources. This report also discusses the pertinent signal processing methodologies, demonstrates the approach with computer simulations, and validates the simulations with experimental data. Specific localization methods discussed include triangulation and measurement of time difference of arrival from multiple sensor arrays.

  2. Ground squirrels use an infrared signal to deter rattlesnake predation.

    Science.gov (United States)

    Rundus, Aaron S; Owings, Donald H; Joshi, Sanjay S; Chinn, Erin; Giannini, Nicolas

    2007-09-04

    The evolution of communicative signals involves a major hurdle; signals need to effectively stimulate the sensory systems of their targets. Therefore, sensory specializations of target animals are important sources of selection on signal structure. Here we report the discovery of an animal signal that uses a previously unknown communicative modality, infrared radiation or "radiant heat," which capitalizes on the infrared sensory capabilities of the signal's target. California ground squirrels (Spermophilus beecheyi) add an infrared component to their snake-directed tail-flagging signals when confronting infrared-sensitive rattlesnakes (Crotalus oreganus), but tail flag without augmenting infrared emission when confronting infrared-insensitive gopher snakes (Pituophis melanoleucus). Experimental playbacks with a biorobotic squirrel model reveal this signal's communicative function. When the infrared component was added to the tail flagging display of the robotic models, rattlesnakes exhibited a greater shift from predatory to defensive behavior than during control trials in which tail flagging included no infrared component. These findings provide exceptionally strong support for the hypothesis that the sensory systems of signal targets should, in general, channel the evolution of signal structure. Furthermore, the discovery of previously undescribed signaling modalities such as infrared radiation should encourage us to overcome our own human-centered sensory biases and more fully examine the form and diversity of signals in the repertoires of many animal species.

  3. Signal processing for remote sensing

    CERN Document Server

    Chen, CH

    2007-01-01

    Written by leaders in the field, Signal Processing for Remote Sensing explores the data acquisitions segment of remote sensing. Each chapter presents a major research result or the most up to date development of a topic. The book includes a chapter by Dr. Norden Huang, inventor of the Huang-Hilbert transform who, along with and Dr. Steven Long discusses the application of the transform to remote sensing problems. It also contains a chapter by Dr. Enders A. Robinson, who has made major contributions to seismic signal processing for over half a century, on the basic problem of constructing seism

  4. Signal processing for cognitive radios

    CERN Document Server

    Jayaweera, Sudharman K

    2014-01-01

    This book covers power electronics, in depth, by presenting the basic principles and application details, and it can be used both as a textbook and reference book.  Introduces the specific type of CR that has gained the most research attention in recent years: the CR for Dynamic Spectrum Access (DSA). Provides signal processing solutions to each task by relating the tasks to materials covered in Part II. Specialized chapters then discuss specific signal processing algorithms required for DSA and DSS cognitive radios  

  5. PSpice for digital signal processing

    CERN Document Server

    Tobin, Paul

    2007-01-01

    PSpice for Digital Signal Processing is the last in a series of five books using Cadence Orcad PSpice version 10.5 and introduces a very novel approach to learning digital signal processing (DSP). DSP is traditionally taught using Matlab/Simulink software but has some inherent weaknesses for students particularly at the introductory level. The 'plug in variables and play' nature of these software packages can lure the student into thinking they possess an understanding they don't actually have because these systems produce results quicklywithout revealing what is going on. However, it must be

  6. Innovative process rational choice grounding in organization

    OpenAIRE

    S.M. Illiashenko

    2015-01-01

    The aim of the article. The aim of the article is to investigate and scientifically to ground recommendations concerning choice of the rational structure and innovative process content, depending on innovative development potential in the organization and innovation radicalization degree, which provides to coordinate interconnection between SRCCW and innovations marketing at its stages for various innovative business types. The results of the analysis. The generalized scheme of organizati...

  7. Innovative process rational choice grounding in organization

    Directory of Open Access Journals (Sweden)

    S.M. Illiashenko

    2015-06-01

    Full Text Available The aim of the article. The aim of the article is to investigate and scientifically to ground recommendations concerning choice of the rational structure and innovative process content, depending on innovative development potential in the organization and innovation radicalization degree, which provides to coordinate interconnection between SRCCW and innovations marketing at its stages for various innovative business types. The results of the analysis. The generalized scheme of organization innovative activity is investigated. It characterizes interconnections between innovative process, innovative business and innovative strategies types. The peculiarities of the works conduct concerning innovative process distinguished types are confirmed by scheme: works essence, type (types of the innovative business, innovative strategy (strategies, which is realized. Recommendations concerning works conduct reasonability of the several stages in the innovative process for organizations, which have innovative business combined type, are suggested. Essence and content of SRRCW works and innovations marketing works are confirmed at the innovative and life cycle stages of the new product. Table of decisions is developed to choose innovative process variants, which are reasonably to realize by concrete organization, depending on subsystems constituents state of its innovative development potential and innovative product radicalization degree. The enlarged block-scheme of the algorithm to choose rational structure in the innovative process within one or every innovative projects, realized by organization, is investigated. The recommendations concerning estimation of the innovative processes possible simultaneous conduct with various or similar variants of the innovative process structures by formal procedures are developed. Conclusions and directions of further researches. Author’s studies together allow to increase validity and decrease risk to choose

  8. Wavelets and multiscale signal processing

    CERN Document Server

    Cohen, Albert

    1995-01-01

    Since their appearance in mid-1980s, wavelets and, more generally, multiscale methods have become powerful tools in mathematical analysis and in applications to numerical analysis and signal processing. This book is based on "Ondelettes et Traitement Numerique du Signal" by Albert Cohen. It has been translated from French by Robert D. Ryan and extensively updated by both Cohen and Ryan. It studies the existing relations between filter banks and wavelet decompositions and shows how these relations can be exploited in the context of digital signal processing. Throughout, the book concentrates on the fundamentals. It begins with a chapter on the concept of multiresolution analysis, which contains complete proofs of the basic results. The description of filter banks that are related to wavelet bases is elaborated in both the orthogonal case (Chapter 2), and in the biorthogonal case (Chapter 4). The regularity of wavelets, how this is related to the properties of the filters and the importance of regularity for t...

  9. Handbook of signal processing systems

    CERN Document Server

    Bhattacharyya, Shuvra S; Leupers, Rainer; Takala, Jarmo

    2010-01-01

    The Handbook is organized in four parts. The first part motivates representative applications that drive and apply state-of-the art methods for design and implementation of signal processing systems; the second part discusses architectures for implementing these applications; the third part focuses on compilers and simulation tools; and the fourth part describes models of computation and their associated design tools and methodologies.

  10. VLSI mixed signal processing system

    Science.gov (United States)

    Alvarez, A.; Premkumar, A. B.

    1993-01-01

    An economical and efficient VLSI implementation of a mixed signal processing system (MSP) is presented in this paper. The MSP concept is investigated and the functional blocks of the proposed MSP are described. The requirements of each of the blocks are discussed in detail. A sample application using active acoustic cancellation technique is described to demonstrate the power of the MSP approach.

  11. Signal Processing for Optical Networks

    Science.gov (United States)

    2007-11-02

    understanding and enhancing a number of important recent wavelet-based and DCT- based image coders. We show that Shapiro’s well-known EZW scheme, Said and...comparable to Shapiro’s EZW coder (J. M. Shapiro, "Embedded image coding using zerotrees of wavelet coefficients", IEEE Trans, on Signal Processing, v. 41

  12. CMOS Nonlinear Signal Processing Circuits

    OpenAIRE

    2010-01-01

    The chapter describes various nonlinear signal processing CMOS circuits, including a high reliable WTA/LTA, simple MED cell, and low-voltage arbitrary order extractor. We focus the discussion on CMOS analog circuit design with reliable, programmable capability, and low voltage operation. It is a practical problem when the multiple identical cells are required to match and realized within a single chip using a conventional process. Thus, the design of high-reliable circuit is indeed needed. Th...

  13. Acoustic signal processing toolbox for array processing

    Science.gov (United States)

    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.

  14. SAR processing using SHARC signal processing systems

    Science.gov (United States)

    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.

  15. Comparison of algorithms for finding the air-ground interface in ground penetrating radar signals

    Science.gov (United States)

    Wood, Joshua; Bolton, Jeremy; Casella, George; Collins, Leslie; Gader, Paul; Glenn, Taylor; Ho, Jeffery; Lee, Wen; Mueller, Richard; Smock, Brandon; Torrione, Peter; Watford, Ken; Wilson, Joseph

    2011-06-01

    In using GPR images for landmine detection it is often useful to identify the air-ground interface in the GPR signal for alignment purposes. A number of algorithms have been proposed to solve the air-ground interface detection problem, including some which use only A-scan data, and others which track the ground in B-scans or C-scans. Here we develop a framework for comparing these algorithms relative to one another and we examine the results. The evaluations are performed on data that have been categorized in terms of features that make the air-ground interface difficult to find or track. The data also have associated human selected ground locations, from multiple evaluators, that can be used for determining correctness. A distribution is placed over each of the human selected ground locations, with the sum of these distributions at the algorithm selected location used as a measure of its correctness. Algorithms are also evaluated in terms of how they affect the false alarm and true positive rates of mine detection algorithms that use ground aligned data.

  16. OPTIMAL SIGNAL PROCESSING METHODS IN GPR

    Directory of Open Access Journals (Sweden)

    Saeid Karamzadeh

    2014-01-01

    Full Text Available In the past three decades, a lot of various applications of Ground Penetrating Radar (GPR took place in real life. There are important challenges of this radar in civil applications and also in military applications. In this paper, the fundamentals of GPR systems will be covered and three important signal processing methods (Wavelet Transform, Matched Filter and Hilbert Huang will be compared to each other in order to get most accurate information about objects which are in subsurface or behind the wall.

  17. Ground Processing Affordability for Space Vehicles

    Science.gov (United States)

    Ingalls, John; Scott, Russell

    2011-01-01

    Launch vehicles and most of their payloads spend the majority of their time on the ground. The cost of ground operations is very high. So, why so often is so little attention given to ground processing during development? The current global space industry and economic environment are driving more need for efficiencies to save time and money. Affordability and sustainability are more important now than ever. We can not continue to treat space vehicles as mere science projects. More RLV's (Reusable Launch Vehicles) are being developed for the gains of reusability which are not available for ELV's (Expendable Launch Vehicles). More human-rated vehicles are being developed, with the retirement of the Space Shuttles, and for a new global space race, yet these cost more than the many unmanned vehicles of today. We can learn many lessons on affordability from RLV's. DFO (Design for Operations) considers ground operations during design, development, and manufacturing-before the first flight. This is often minimized for space vehicles, but is very important. Vehicles are designed for launch and mission operations. You will not be able to do it again if it is too slow or costly to get there. Many times, technology changes faster than space products such that what is launched includes outdated features, thus reducing competitiveness. Ground operations must be considered for the full product Lifecycle, from concept to retirement. Once manufactured, launch vehicles along with their payloads and launch systems require a long path of processing before launch. Initial assembly and testing always discover problems to address. A solid integration program is essential to minimize these impacts, as was seen in the Constellation Ares I-X test rocket. For RLV's, landing/recovery and post-flight turnaround activities are performed. Multi-use vehicles require reconfiguration. MRO (Maintenance, Repair, and Overhaul) must be well-planned--- even for the unplanned problems. Defect limits and

  18. Ground robotic measurement of aeolian processes

    Science.gov (United States)

    Qian, Feifei; Jerolmack, Douglas; Lancaster, Nicholas; Nikolich, George; Reverdy, Paul; Roberts, Sonia; Shipley, Thomas; Van Pelt, R. Scott; Zobeck, Ted M.; Koditschek, Daniel E.

    2017-08-01

    Models of aeolian processes rely on accurate measurements of the rates of sediment transport by wind, and careful evaluation of the environmental controls of these processes. Existing field approaches typically require intensive, event-based experiments involving dense arrays of instruments. These devices are often cumbersome and logistically difficult to set up and maintain, especially near steep or vegetated dune surfaces. Significant advances in instrumentation are needed to provide the datasets that are required to validate and improve mechanistic models of aeolian sediment transport. Recent advances in robotics show great promise for assisting and amplifying scientists' efforts to increase the spatial and temporal resolution of many environmental measurements governing sediment transport. The emergence of cheap, agile, human-scale robotic platforms endowed with increasingly sophisticated sensor and motor suites opens up the prospect of deploying programmable, reactive sensor payloads across complex terrain in the service of aeolian science. This paper surveys the need and assesses the opportunities and challenges for amassing novel, highly resolved spatiotemporal datasets for aeolian research using partially-automated ground mobility. We review the limitations of existing measurement approaches for aeolian processes, and discuss how they may be transformed by ground-based robotic platforms, using examples from our initial field experiments. We then review how the need to traverse challenging aeolian terrains and simultaneously make high-resolution measurements of critical variables requires enhanced robotic capability. Finally, we conclude with a look to the future, in which robotic platforms may operate with increasing autonomy in harsh conditions. Besides expanding the completeness of terrestrial datasets, bringing ground-based robots to the aeolian research community may lead to unexpected discoveries that generate new hypotheses to expand the science

  19. Low power digital signal processing

    DEFF Research Database (Denmark)

    Paker, Ozgun

    2003-01-01

    This thesis introduces a novel approach to programmable and low power platform design for audio signal processing, in particular hearing aids. The proposed programmable platform is a heterogeneous multiprocessor architecture consisting of small and simple instruction set processors called mini...... data addressing capabilities lead to the design of low power mini-cores. The algorithm suite also consisted of less demanding and/or irregular algorithms (LMS, compression) that required subsample rate signal processing justifying the use of a DSP/CPU-core. The thesis also contributes to the recent...... trend in the development of intellectual property based design methodologies. The actual mini-core designs are parameterized in word-size, memory-size, etc. and can be instantiated according to the needs of the application at hand. They are intended as low power programmable building blocks...

  20. Signal processing with free software practical experiments

    CERN Document Server

    Auger, François

    2014-01-01

    An ideal resource for students, industrial engineers, and researchers, Signal Processing with Free Software Practical Experiments presents practical experiments in signal processing using free software. The text introduces elementary signals through elementary waveform, signal storage files and elementary operations on signals and then presents the first tools to signal analysis such as temporal and frequency characteristics leading to Time-frequency analysis. Non-parametric spectral analysis is also discussed as well as signal processing through sampling, resampling, quantification, an

  1. Neural Network Communications Signal Processing

    Science.gov (United States)

    1994-08-01

    Technical Information Report for the Neural Network Communications Signal Processing Program, CDRL A003, 31 March 1993. Software Development Plan for...track changing jamming conditions to provide the decoder with the best log- likelihood ratio metrics at a given time. As part of our development plan we...Artificial Neural Networks (ICANN-91) Volume 2, June 24-28, 1991, pp. 1677-1680. Kohonen, Teuvo, Raivio, Kimmo, Simula, Oli, Venta , 011i, Henriksson

  2. Signal processing for smart cards

    Science.gov (United States)

    Quisquater, Jean-Jacques; Samyde, David

    2003-06-01

    In 1998, Paul Kocher showed that when a smart card computes cryptographic algorithms, for signatures or encryption, its consumption or its radiations leak information. The keys or the secrets hidden in the card can then be recovered using a differential measurement based on the intercorrelation function. A lot of silicon manufacturers use desynchronization countermeasures to defeat power analysis. In this article we detail a new resynchronization technic. This method can be used to facilitate the use of a neural network to do the code recognition. It becomes possible to reverse engineer a software code automatically. Using data and clock separation methods, we show how to optimize the synchronization using signal processing. Then we compare these methods with watermarking methods for 1D and 2D signal. The very last watermarking detection improvements can be applied to signal processing for smart cards with very few modifications. Bayesian processing is one of the best ways to do Differential Power Analysis, and it is possible to extract a PIN code from a smart card in very few samples. So this article shows the need to continue to set up effective countermeasures for cryptographic processors. Although the idea to use advanced signal processing operators has been commonly known for a long time, no publication explains that results can be obtained. The main idea of differential measurement is to use the cross-correlation of two random variables and to repeat consumption measurements on the processor to be analyzed. We use two processors clocked at the same external frequency and computing the same data. The applications of our design are numerous. Two measurements provide the inputs of a central operator. With the most accurate operator we can improve the signal noise ratio, re-synchronize the acquisition clock with the internal one, or remove jitter. The analysis based on consumption or electromagnetic measurements can be improved using our structure. At first sight

  3. Highly Parallel Modern Signal Processing.

    Science.gov (United States)

    1982-02-28

    SVD to Signal Processing (NOSC,USC) ----------------------------------- 11 Parallel Kalman Filter Algorithms (Stanford and ISI [25-27...speCtLrm d kvel,’ope d by u.s *converges to the 2- maqx i -um;- entropy s t-?ect ra I S i -ivate 8Syrn PLCticIIllY. N~rrently we have beg-un...Methods for Ppectral Estimat~ion and Array Processing I t may seem tOO amnbitLious tr. compare all currently popular high1- resol’Jtion spectra

  4. GSTAMIDS ground-penetrating radar: data processing algorithms

    Science.gov (United States)

    Sower, Gary D.; Kilgore, Roger; Roman, Jaime R.

    2001-10-01

    The Ground Standoff Mine Detection System is now in the Engineering, Manufacturing and Development (EMD) Block 0 phase for USA CECOM. This paper describes the data processing algorithms for the GPR that are used to extract the features used for anti-tank (AT) mine detection; those used for pre-processing the data re included herein to show the enhancement of the mine signals. A key feature of the processing is the acquisition of a clean radar return signal from undisturbed soil, which is then deconvolved from each data frame waveform. This soil signal is an estimate of the system impulse response function, save for the magnitude of the reflection coefficient of the soil, which is a scalar to first order. Deconvolution thus gives the impulse response function of the buried mines, a strong enhancement over their raw measured signals. A matched filter test statistic is generated to discriminate between mines and background. Discrimination algorithms using hidden Markov model processing are describe in a paper by PD Gader et al. These processes were developed in MATLAB using dat files acquired and stored from prototype GPR systems and then refined with data form production units. The MATLAB code is then converted into C code for use on the real-time processor on GSTAMIDS. The C code modules are run as dynamic library links in MATLAB for verification. The GPR sensor suite hardware and its physical incorporation into the GSTAMIDS sensor modules are described fully in a companion paper.

  5. Applied signal processing concepts, circuits, and systems

    CERN Document Server

    Hamdy, Nadder

    2008-01-01

    Introduction What are Signals? Signal parameters Why Signal processing? Analog vs. Digital Signal processing Practical Signal processing Systems Analog Signal Processing Amplitude Shaping Frequency Spectrum Shaping Phase Errors Correction Waveform Generation Analog Filter Design Describing Equations Design Procedures Filter Specifications Approximations to the Ideal Response Realization Practical RC-Filters Design Switched Capacitor Filter Realization Design examples Data Converters Introduction A typical DSP System Specifications of Data Converters Sampling Samp

  6. Acoustic vector sensor signal processing

    Institute of Scientific and Technical Information of China (English)

    SUN Guiqing; LI Qihu; ZHANG Bin

    2006-01-01

    Acoustic vector sensor simultaneously, colocately and directly measures orthogonal components of particle velocity as well as pressure at single point in acoustic field so that is possible to improve performance of traditional underwater acoustic measurement devices or detection systems and extends new ideas for solving practical underwater acoustic engineering problems. Although acoustic vector sensor history of appearing in underwater acoustic area is no long, but with huge and potential military demands, acoustic vector sensor has strong development trend in last decade, it is evolving into a one of important underwater acoustic technology. Under this background, we try to review recent progress in study on acoustic vector sensor signal processing, such as signal detection, DOA estimation, beamforming, and so on.

  7. Nuclear sensor signal processing circuit

    Science.gov (United States)

    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.

  8. a Universal De-Noising Algorithm for Ground-Based LIDAR Signal

    Science.gov (United States)

    Ma, Xin; Xiang, Chengzhi; Gong, Wei

    2016-06-01

    Ground-based lidar, working as an effective remote sensing tool, plays an irreplaceable role in the study of atmosphere, since it has the ability to provide the atmospheric vertical profile. However, the appearance of noise in a lidar signal is unavoidable, which leads to difficulties and complexities when searching for more information. Every de-noising method has its own characteristic but with a certain limitation, since the lidar signal will vary with the atmosphere changes. In this paper, a universal de-noising algorithm is proposed to enhance the SNR of a ground-based lidar signal, which is based on signal segmentation and reconstruction. The signal segmentation serving as the keystone of the algorithm, segments the lidar signal into three different parts, which are processed by different de-noising method according to their own characteristics. The signal reconstruction is a relatively simple procedure that is to splice the signal sections end to end. Finally, a series of simulation signal tests and real dual field-of-view lidar signal shows the feasibility of the universal de-noising algorithm.

  9. Fixed-point signal processing

    CERN Document Server

    Padgett, Wayne T

    2009-01-01

    This book is intended to fill the gap between the ""ideal precision"" digital signal processing (DSP) that is widely taught, and the limited precision implementation skills that are commonly required in fixed-point processors and field programmable gate arrays (FPGAs). These skills are often neglected at the university level, particularly for undergraduates. We have attempted to create a resource both for a DSP elective course and for the practicing engineer with a need to understand fixed-point implementation. Although we assume a background in DSP, Chapter 2 contains a review of basic theory

  10. Advanced Signal Analysis for Forensic Applications of Ground Penetrating Radar

    Energy Technology Data Exchange (ETDEWEB)

    Steven Koppenjan; Matthew Streeton; Hua Lee; Michael Lee; Sashi Ono

    2004-06-01

    Ground penetrating radar (GPR) systems have traditionally been used to image subsurface objects. The main focus of this paper is to evaluate an advanced signal analysis technique. Instead of compiling spatial data for the analysis, this technique conducts object recognition procedures based on spectral statistics. The identification feature of an object type is formed from the training vectors by a singular-value decomposition procedure. To illustrate its capability, this procedure is applied to experimental data and compared to the performance of the neural-network approach.

  11. Advanced digital signal processing and noise reduction

    CERN Document Server

    Vaseghi, Saeed V

    2008-01-01

    Digital signal processing plays a central role in the development of modern communication and information processing systems. The theory and application of signal processing is concerned with the identification, modelling and utilisation of patterns and structures in a signal process. The observation signals are often distorted, incomplete and noisy and therefore noise reduction, the removal of channel distortion, and replacement of lost samples are important parts of a signal processing system. The fourth edition of Advanced Digital Signal Processing and Noise Reduction updates an

  12. Research on mud pulse signal data processing in MWD

    Science.gov (United States)

    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.

  13. Optical time-lens signal processing

    DEFF Research Database (Denmark)

    Oxenløwe, Leif Katsuo; Galili, Michael; Mulvad, Hans Christian Hansen;

    2014-01-01

    This paper describes the use of optical time lenses for optical signal processing of advanced optical data signals. Examples given include 1.28 Tbaud Nyquist channel serial-to-parallel conversion and spectral magnification of OFDM signals.......This paper describes the use of optical time lenses for optical signal processing of advanced optical data signals. Examples given include 1.28 Tbaud Nyquist channel serial-to-parallel conversion and spectral magnification of OFDM signals....

  14. Digital signal processing using MATLAB

    CERN Document Server

    Schilling, Robert L

    2016-01-01

    Focus on the development, implementation, and application of modern DSP techniques with DIGITAL SIGNAL PROCESSING USING MATLAB(R), 3E. Written in an engaging, informal style, this edition immediately captures your attention and encourages you to explore each critical topic. Every chapter starts with a motivational section that highlights practical examples and challenges that you can solve using techniques covered in the chapter. Each chapter concludes with a detailed case study example, a chapter summary with learning outcomes, and practical homework problems cross-referenced to specific chapter sections for your convenience. DSP Companion software accompanies each book to enable further investigation. The DSP Companion software operates with MATLAB(R) and provides intriguing demonstrations as well as interactive explorations of analysis and design concepts.

  15. Fundamentals of adaptive signal processing

    CERN Document Server

    Uncini, Aurelio

    2015-01-01

    This book is an accessible guide to adaptive signal processing methods that equips the reader with advanced theoretical and practical tools for the study and development of circuit structures and provides robust algorithms relevant to a wide variety of application scenarios. Examples include multimodal and multimedia communications, the biological and biomedical fields, economic models, environmental sciences, acoustics, telecommunications, remote sensing, monitoring, and, in general, the modeling and prediction of complex physical phenomena. The reader will learn not only how to design and implement the algorithms but also how to evaluate their performance for specific applications utilizing the tools provided. While using a simple mathematical language, the employed approach is very rigorous. The text will be of value both for research purposes and for courses of study.

  16. Transformation of Ground Vibration Signal for Debris-Flow Monitoring and Detection in Alarm Systems

    Directory of Open Access Journals (Sweden)

    José Moya

    2012-04-01

    Full Text Available Debris flows are fast mass movements formed by a mix of water and solid materials, which occur in steep torrents, and are a source of high risks for human settlements. Geophones are widely used to detect the ground vibration induced by passing debris flows. However, the recording of geophone signals usually requires storing a huge amount of data, which leads to problems in storage capacity and power consumption. This paper presents a method to transform and simplify the signals measured by geophones. The key input parameter is the ground velocity threshold, which removes the seismic noise that is not related to debris flows. A signal conditioner was developed to implement the transformation and the ground velocity threshold was set by electrical resistors. The signal conditioner was installed at various European monitoring sites to test the method. Results show that data amount and power consumption can be greatly reduced without losing much information on the main features of the debris flows. However, the outcome stresses the importance of choosing a ground vibration threshold, which must be accurately calibrated. The transformation is also suitable to detect other rapid mass movements and to distinguish among different processes, which points to a possible implementation in alarm systems.

  17. Transformation of ground vibration signal for debris-flow monitoring and detection in alarm systems.

    Science.gov (United States)

    Abancó, Clàudia; Hürlimann, Marcel; Fritschi, Bruno; Graf, Christoph; Moya, José

    2012-01-01

    Debris flows are fast mass movements formed by a mix of water and solid materials, which occur in steep torrents, and are a source of high risks for human settlements. Geophones are widely used to detect the ground vibration induced by passing debris flows. However, the recording of geophone signals usually requires storing a huge amount of data, which leads to problems in storage capacity and power consumption. This paper presents a method to transform and simplify the signals measured by geophones. The key input parameter is the ground velocity threshold, which removes the seismic noise that is not related to debris flows. A signal conditioner was developed to implement the transformation and the ground velocity threshold was set by electrical resistors. The signal conditioner was installed at various European monitoring sites to test the method. Results show that data amount and power consumption can be greatly reduced without losing much information on the main features of the debris flows. However, the outcome stresses the importance of choosing a ground vibration threshold, which must be accurately calibrated. The transformation is also suitable to detect other rapid mass movements and to distinguish among different processes, which points to a possible implementation in alarm systems.

  18. Signal processing and analyzing works of art

    Science.gov (United States)

    Johnson, Don H.; Johnson, C. Richard, Jr.; Hendriks, Ella

    2010-08-01

    In examining paintings, art historians use a wide variety of physico-chemical methods to determine, for example, the paints, the ground (canvas primer) and any underdrawing the artist used. However, the art world has been little touched by signal processing algorithms. Our work develops algorithms to examine x-ray images of paintings, not to analyze the artist's brushstrokes but to characterize the weave of the canvas that supports the painting. The physics of radiography indicates that linear processing of the x-rays is most appropriate. Our spectral analysis algorithms have an accuracy superior to human spot-measurements and have the advantage that, through "short-space" Fourier analysis, they can be readily applied to entire x-rays. We have found that variations in the manufacturing process create a unique pattern of horizontal and vertical thread density variations in the bolts of canvas produced. In addition, we measure the thread angles, providing a way to determine the presence of cusping and to infer the location of the tacks used to stretch the canvas on a frame during the priming process. We have developed weave matching software that employs a new correlation measure to find paintings that share canvas weave characteristics. Using a corpus of over 290 paintings attributed to Vincent van Gogh, we have found several weave match cliques that we believe will refine the art historical record and provide more insight into the artist's creative processes.

  19. Support vector data description for detecting the air-ground interface in ground penetrating radar signals

    Science.gov (United States)

    Wood, Joshua; Wilson, Joseph

    2011-06-01

    In using GPR images for landmine detection it is often useful to identify the air-ground interface in the GRP signal for alignment purposes. A common simple technique for doing this is to assume that the highest return in an A-scan is from the reflection due to the ground and to use that as the location of the interface. However there are many situations, such as the presence of nose clutter or shallow sub-surface objects, that can cause the global maximum estimate to be incorrect. A Support Vector Data Description (SVDD) is a one-class classifier related to the SVM which encloses the class in a hyper-sphere as opposed to using a hyper-plane as a decision boundary. We apply SVDD to the problem of detection of the air-ground interface by treating each sample in an A-scan, with some number of leading and trailing samples, as a feature vector. Training is done using a set of feature vectors based on known interfaces and detection is done by creating feature vectors from each of the samples in an A-scan, applying the trained SVDD to them and selecting the one with the least distance from the center of the hyper-sphere. We compare this approach with the global maximum approach, examining both the performance on human truthed data and how each method affects false alarm and true positive rates when used as the alignment method in mine detection algorithms.

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

    Science.gov (United States)

    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.

  1. Development of an Ontology-Directed Signal Processing Toolbox

    Energy Technology Data Exchange (ETDEWEB)

    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

  2. Radar signal analysis and processing using Matlab

    CERN Document Server

    Mahafza, Bassem R

    2008-01-01

    Offering radar-related software for the analysis and design of radar waveform and signal processing, this book provides comprehensive coverage of radar signals and signal processing techniques and algorithms. It contains numerous graphical plots, common radar-related functions, table format outputs, and end-of-chapter problems. The complete set of MATLAB[registered] functions and routines are available for download online.

  3. A signal theoretic introduction to random processes

    CERN Document Server

    Howard, Roy M

    2015-01-01

    A fresh introduction to random processes utilizing signal theory By incorporating a signal theory basis, A Signal Theoretic Introduction to Random Processes presents a unique introduction to random processes with an emphasis on the important random phenomena encountered in the electronic and communications engineering field. The strong mathematical and signal theory basis provides clarity and precision in the statement of results. The book also features:  A coherent account of the mathematical fundamentals and signal theory that underpin the presented material Unique, in-depth coverage of

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

    Science.gov (United States)

    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.

  5. Efficient Underground Object Detection for Ground Penetrating Radar Signals

    Directory of Open Access Journals (Sweden)

    Ibrahim Mesecan

    2016-12-01

    Full Text Available Ground penetrating radar (GPR is one of the common sensor system for underground inspection. GPR emits electromagnetic waves which can pass through objects. The reflecting waves are recorded and digitised, and then, the B-scan images are formed. According to the properties of scanning object, GPR creates higher or lower intensity values on the object regions. Thus, these changes in signal represent the properties of scanning object. This paper proposes a 3-step method to detect and discriminate landmines: n-row average-subtraction (NRAS; Min-max normalisation; and image scaling. Proposed method has been tested using 3 common algorithms from the literature. According to the results, it has increased object detection ratio and positive object discrimination (POD significantly. For artificial neural networks (ANN, POD has increased from 77.4 per cent to 87.7 per cent. And, it has increased from 37.8 per cent to 80.2 per cent, for support vector machines (SVM.

  6. Improvements on Signal Processing for HF Radar

    Institute of Scientific and Technical Information of China (English)

    LIU Yongtan; SHEN Yiying

    2001-01-01

    In this paper improvements on signalprocessing are achieved to enhance the performancesof H-F radar system, being unobtainable by the con-ventional signal processing. Using the improved sig-nal processing both high range resolution and longcoherent integration time may be obtained for goodbenefit to the target resolution and weak signal de-tection. Modification to the unmatched correspon-dence between range delay samples and range resolu-tion ceils saves an additional accumulation loss in therange processing. Finally, comparisons between theimproved and the conventional signal processing aregiven by numerical simulation.

  7. Radar signal processing and its applications

    CERN Document Server

    Hummel, Robert; Stoica, Petre; Zelnio, Edmund

    2003-01-01

    Radar Signal Processing and Its Applications brings together in one place important contributions and up-to-date research results in this fast-moving area. In twelve selected chapters, it describes the latest advances in architectures, design methods, and applications of radar signal processing. The contributors to this work were selected from the leading researchers and practitioners in the field. This work, originally published as Volume 14, Numbers 1-3 of the journal, Multidimensional Systems and Signal Processing, will be valuable to anyone working or researching in the field of radar signal processing. It serves as an excellent reference, providing insight into some of the most challenging issues being examined today.

  8. Advanced Methods of Biomedical Signal Processing

    CERN Document Server

    Cerutti, Sergio

    2011-01-01

    This book grew out of the IEEE-EMBS Summer Schools on Biomedical Signal Processing, which have been held annually since 2002 to provide the participants state-of-the-art knowledge on emerging areas in biomedical engineering. Prominent experts in the areas of biomedical signal processing, biomedical data treatment, medicine, signal processing, system biology, and applied physiology introduce novel techniques and algorithms as well as their clinical or physiological applications. The book provides an overview of a compelling group of advanced biomedical signal processing techniques, such as mult

  9. Signals Intelligence - Processing - Analysis - Classification

    Science.gov (United States)

    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

  10. Mine detection using SF-GPR: A signal processing approach for resolution enhancement and clutter reduction

    DEFF Research Database (Denmark)

    Karlsen, Brian; Jakobsen, Kaj Bjarne; Larsen, Jan;

    2001-01-01

    Proper clutter reduction is essential for Ground Penetrating Radar data since low signal-to-clutter ratio prevent correct detection of mine objects. A signal processing approach for resolution enhancement and clutter reduction used on Stepped-Frequency Ground Penetrating Radar (SF-GPR) data is pr...

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

    Science.gov (United States)

    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.

  12. Optical Processing of High Dimensionality Signals

    DEFF Research Database (Denmark)

    Da Ros, Francesco

    signal processing, including wavelength conversion, optical phase conjugation (OPC), and signal regeneration. This project focuses precisely on the applications of OPAs for all-optical signal processing with a two-fold focus: on the one hand, processing the advanced modulation formats required......) waveguides, are investigated. The limits of parametric amplification for 16-quadrature amplitude modulation (QAM) signals are first characterized. The acquired knowledge is then applied to the design of a black-box OPC-device used to provide Kerr nonlinearity compensation for a 5-channel polarization......-division multiplexing (PDM) 16-QAM signal at 1.12 Tbps with significant improvements in received signal quality. Furthermore, the first demonstration of phase regeneration for binary phase-shift keying (BPSK) signals using the silicon platform is presented. The silicon-based OPA relies on a novel design where a reverse...

  13. Kennedy Space Center Orion Processing Team Planning for Ground Operations

    Science.gov (United States)

    Letchworth, Gary; Schlierf, Roland

    2011-01-01

    Topics in this presentation are: Constellation Ares I/Orion/Ground Ops Elements Orion Ground Operations Flow Orion Operations Planning Process and Toolset Overview, including: 1 Orion Concept of Operations by Phase 2 Ops Analysis Capabilities Overview 3 Operations Planning Evolution 4 Functional Flow Block Diagrams 5 Operations Timeline Development 6 Discrete Event Simulation (DES) Modeling 7 Ground Operations Planning Document Database (GOPDb) Using Operations Planning Tools for Operability Improvements includes: 1 Kaizen/Lean Events 2 Mockups 3 Human Factors Analysis

  14. Digital signal processing an experimental approach

    CERN Document Server

    Engelberg, Shlomo

    2008-01-01

    Digital Signal Processing is a mathematically rigorous but accessible treatment of digital signal processing that intertwines basic theoretical techniques with hands-on laboratory instruction. Divided into three parts, the book covers various aspects of the digital signal processing (DSP) ""problem."" It begins with the analysis of discrete-time signals and explains sampling and the use of the discrete and fast Fourier transforms. The second part of the book???covering digital to analog and analog to digital conversion???provides a practical interlude in the mathematical content before Part II

  15. Bistatic SAR: Signal Processing and Image Formation.

    Energy Technology Data Exchange (ETDEWEB)

    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.

  16. Digital signal processing for fiber nonlinearities [Invited

    DEFF Research Database (Denmark)

    Cartledge, John C.; Guiomar, Fernando P.; Kschischang, Frank R.

    2017-01-01

    This paper reviews digital signal processing techniques that compensate, mitigate, and exploit fiber nonlinearities in coherent optical fiber transmission systems......This paper reviews digital signal processing techniques that compensate, mitigate, and exploit fiber nonlinearities in coherent optical fiber transmission systems...

  17. Handbook of Signal Processing in Acoustics

    CERN Document Server

    Havelock, David; Vorländer, Michael

    2009-01-01

    The Handbook of Signal Processing in Acoustics presents signal processing as it is practiced in the field of acoustics. The Handbook is organized by areas of acoustics, with recognized leaders coordinating the self-contained chapters of each section. It brings together a wide range of perspectives from over 100 authors to reveal the interdisciplinary nature of signal processing in acoustics. Success in acoustic applications often requires juggling both the acoustic and the signal processing parameters of the problem. This handbook brings the key issues from both into perspective and is complementary to other reference material on the two subjects. It is a unique resource for experts and practitioners alike to find new ideas and techniques within the diversity of signal processing in acoustics.

  18. Advances in heuristic signal processing and applications

    CERN Document Server

    Chatterjee, Amitava; Siarry, Patrick

    2013-01-01

    There have been significant developments in the design and application of algorithms for both one-dimensional signal processing and multidimensional signal processing, namely image and video processing, with the recent focus changing from a step-by-step procedure of designing the algorithm first and following up with in-depth analysis and performance improvement to instead applying heuristic-based methods to solve signal-processing problems. In this book the contributing authors demonstrate both general-purpose algorithms and those aimed at solving specialized application problems, with a spec

  19. Ultrafast Nonlinear Signal Processing in Silicon Waveguides

    DEFF Research Database (Denmark)

    Oxenløwe, Leif Katsuo; Mulvad, Hans Christian Hansen; Hu, Hao;

    2012-01-01

    We describe recent demonstrations of exploiting highly nonlinear silicon waveguides for ultrafast optical signal processing. We describe wavelength conversion and serial-to-parallel conversion of 640 Gbit/s data signals and 1.28 Tbit/s demultiplexing and all-optical sampling.......We describe recent demonstrations of exploiting highly nonlinear silicon waveguides for ultrafast optical signal processing. We describe wavelength conversion and serial-to-parallel conversion of 640 Gbit/s data signals and 1.28 Tbit/s demultiplexing and all-optical sampling....

  20. Advanced Digital Signal Processing for Hybrid Lidar

    Science.gov (United States)

    2014-10-30

    Technical 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. 15. SUBJECT TERMS Hybrid Lidar - Radar 16...Award Number N000141110371 Title of Research Advanced Digital Signal Processing for Hybrid Lidar Principal Investigator William D. Jemison

  1. Signal processing methods for MFE plasma diagnostics

    Energy Technology Data Exchange (ETDEWEB)

    Candy, J.V.; Casper, T.; Kane, R.

    1985-02-01

    The application of various signal processing methods to extract energy storage information from plasma diamagnetism sensors occurring during physics experiments on the Tandom Mirror Experiment-Upgrade (TMX-U) is discussed. We show how these processing techniques can be used to decrease the uncertainty in the corresponding sensor measurements. The algorithms suggested are implemented using SIG, an interactive signal processing package developed at LLNL.

  2. RSFQ Baseband Digital Signal Processing

    Science.gov (United States)

    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.

  3. Signal and image processing in medical applications

    CERN Document Server

    Kumar, Amit; Rahim, B Abdul; Kumar, D Sravan

    2016-01-01

    This book highlights recent findings on and analyses conducted on signals and images in the area of medicine. The experimental investigations involve a variety of signals and images and their methodologies range from very basic to sophisticated methods. The book explains how signal and image processing methods can be used to detect and forecast abnormalities in an easy-to-follow manner, offering a valuable resource for researchers, engineers, physicians and bioinformatics researchers alike.

  4. Processing Music Signals Using Audio Decomposition Techniques

    OpenAIRE

    Driedger, Jonathan

    2016-01-01

    Music signals are complex. When musicians play together, their instruments' sounds superimpose and form a single complex sound mixture. Furthermore, even the sound of a single instrument may already comprise sound components of harmonic, percussive, noise-like, and transient nature, among others. The complexity of music signal processing tasks such as time-scale modifcation - the task of stretching or compressing the duration of a music signal - or music source separation - the...

  5. Pseudo random signal processing theory and application

    CERN Document Server

    Zepernick, Hans-Jurgen

    2013-01-01

    In recent years, pseudo random signal processing has proven to be a critical enabler of modern communication, information, security and measurement systems. The signal's pseudo random, noise-like properties make it vitally important as a tool for protecting against interference, alleviating multipath propagation and allowing the potential of sharing bandwidth with other users. Taking a practical approach to the topic, this text provides a comprehensive and systematic guide to understanding and using pseudo random signals. Covering theoretical principles, design methodologies and applications

  6. Surface Electromyography Signal Processing and Classification Techniques

    Directory of Open Access Journals (Sweden)

    Tae G. Chang

    2013-09-01

    Full Text Available 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.

  7. Surface Electromyography Signal Processing and Classification Techniques

    Science.gov (United States)

    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

  8. Electronic devices for analog signal processing

    CERN Document Server

    Rybin, Yu K

    2012-01-01

    Electronic Devices for Analog Signal Processing is intended for engineers and post graduates and considers electronic devices applied to process analog signals in instrument making, automation, measurements, and other branches of technology. They perform various transformations of electrical signals: scaling, integration, logarithming, etc. The need in their deeper study is caused, on the one hand, by the extension of the forms of the input signal and increasing accuracy and performance of such devices, and on the other hand, new devices constantly emerge and are already widely used in practice, but no information about them are written in books on electronics. The basic approach of presenting the material in Electronic Devices for Analog Signal Processing can be formulated as follows: the study with help from self-education. While divided into seven chapters, each chapter contains theoretical material, examples of practical problems, questions and tests. The most difficult questions are marked by a diamon...

  9. Surface electromyography signal processing and classification techniques.

    Science.gov (United States)

    Chowdhury, Rubana H; Reaz, Mamun B I; Ali, Mohd Alauddin Bin Mohd; Bakar, Ashrif A A; Chellappan, K; Chang, T G

    2013-09-17

    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.

  10. SignalPlant: an open signal processing software platform.

    Science.gov (United States)

    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.

  11. Grounding language processing on basic neurophysiological principles.

    Science.gov (United States)

    Friederici, Angela D; Singer, Wolf

    2015-06-01

    In animal models the neural basis of cognitive and executive processes has been studied extensively at various hierarchical levels from microcircuits to distributed functional networks. This work already provides compelling evidence that diverse cognitive functions are based on similar basic neuronal mechanisms. More recent data suggest that even cognitive functions realized only in human brains rely on these canonical neuronal mechanisms. Here we argue that language, like other cognitive functions, depends on distributed computations in specialized cortical areas forming large-scale dynamic networks and examine to what extent empirical results support this view.

  12. A special issue on photonic signal processing

    Institute of Scientific and Technical Information of China (English)

    Xinliang ZHANG; Jianping CHEN

    2011-01-01

    Photonic signal processing has been receiving increasing attention for about fifteen years.It would be enabling technology for next generation large capacity optical networks because it can avoid electronics bottleneck and decrease power consumption greatly.There are two main areas related to photonic signal processing.One topic is all-optical signal processing for digital bit sequence in optical network,such as all-optical wavelength conversion,alloptical logic operation,all-optical 3R regeneration,all-optical clock recovery,all-optical buffer,etc.The other topic is microwave photonic signal processing,such as microwave photonic filters,arbitrary waveform generation,RF signal generation,UWB signal generation,etc.However,there are still many problems to be solved before these functions could be used in optical networks.Researchers all over the world are concentrating on realizing photonic signal processing functions with some characteristics such as high operation speed and large bandwidth,flexible and multifunctional,potential integration.

  13. Multibeam swath bathymetry signal processing techniques

    Digital Repository Service at National Institute of Oceanography (India)

    Ranade, G.; Sudhakar, T.

    Mathematical advances and the advances in the real time signal processing techniques in the recent times, have considerably improved the state of art in the bathymetry systems. These improvements have helped in developing high resolution swath...

  14. Digital signal processing in communication systems

    CERN Document Server

    Frerking, Marvin E

    1994-01-01

    An engineer's introduction to concepts, algorithms, and advancements in Digital Signal Processing. This lucidly written resource makes extensive use of real-world examples as it covers all the important design and engineering references.

  15. Signal processing by the endosomal system.

    Science.gov (United States)

    Villaseñor, Roberto; Kalaidzidis, Yannis; Zerial, Marino

    2016-04-01

    Cells need to decode chemical or physical signals from their environment in order to make decisions on their fate. In the case of signalling receptors, ligand binding triggers a cascade of chemical reactions but also the internalization of the activated receptors in the endocytic pathway. Here, we highlight recent studies revealing a new role of the endosomal network in signal processing. The diversity of entry pathways and endosomal compartments is exploited to regulate the kinetics of receptor trafficking, and interactions with specific signalling adaptors and effectors. By governing the spatio-temporal distribution of signalling molecules, the endosomal system functions analogously to a digital-analogue computer that regulates the specificity and robustness of the signalling response.

  16. Signal and Image Processing with Sinlets

    CERN Document Server

    Davydov, Alexander Y

    2012-01-01

    This paper presents a new family of localized orthonormal bases - sinlets - which are well suited for both signal and image processing and analysis. One-dimensional sinlets are related to specific solutions of the time-dependent harmonic oscillator equation. By construction, each sinlet is differentiable infinitely many times and has a well-defined and smoothly-varied instantaneous frequency known in analytical form. For square-integrable transient signals with infinite support, one-dimensional sinlet basis provides an advantageous alternative to the Fourier transform by rendering accurate signal representation via a countable set of real-valued coefficients. The properties of sinlets make them suitable for analyzing many real-world signals whose frequency content changes with time including radar and sonar waveforms, music, speech, biological echolocation sounds, biomedical signals, seismic acoustic waves, and signals employed in wireless communication systems. One-dimensional sinlet bases can be used to con...

  17. Signal processing in noise waveform radar

    CERN Document Server

    Kulpa, Krzysztof

    2013-01-01

    This book is devoted to the emerging technology of noise waveform radar and its signal processing aspects. It is a new kind of radar, which use noise-like waveform to illuminate the target. The book includes an introduction to basic radar theory, starting from classical pulse radar, signal compression, and wave radar. The book then discusses the properties, difficulties and potential of noise radar systems, primarily for low-power and short-range civil applications. The contribution of modern signal processing techniques to making noise radar practical are emphasized, and application examples

  18. Digital signal processing techniques and applications in radar image processing

    CERN Document Server

    Wang, Bu-Chin

    2008-01-01

    A self-contained approach to DSP techniques and applications in radar imagingThe processing of radar images, in general, consists of three major fields: Digital Signal Processing (DSP); antenna and radar operation; and algorithms used to process the radar images. This book brings together material from these different areas to allow readers to gain a thorough understanding of how radar images are processed.The book is divided into three main parts and covers:* DSP principles and signal characteristics in both analog and digital domains, advanced signal sampling, and

  19. Sensing, Signal Processing, and Communication for WBANs

    Institute of Scientific and Technical Information of China (English)

    Seyyed Hamed Fouladi; Ral ChvezSantiago; Pl Ander Floor; Ilangko Balasingham; Tor ARamstad

    2014-01-01

    A wireless body area network (WBAN) enables real-time monitoring of physiological signals and helps with the early detection of life-threatening diseases. WBAN nodes can be located on, inside, or in close proximity to the body in order to detect vital signals. Measurements from sensors are processed and transmitted over wireless channels. Issues in sensing, signal processing, and com-munication have to be addressed before WBAN can be implemented. In this paper, we survey recent advances in research on sig-nal processing for the sensor measurements, and we describe aspects of communication based on IEEE 802.15.6. We also discuss state-of-the-art WBAN channel modeling in all the frequencies specified by IEEE 802.15.6 as well as the need for new channel models for new different frequencies.

  20. Liquid Argon TPC Signal Formation, Signal Processing and Hit Reconstruction

    Energy Technology Data Exchange (ETDEWEB)

    Baller, Bruce [Fermilab

    2017-03-11

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

  1. Simulation of non-stationary ground motion processes (II)

    Institute of Scientific and Technical Information of China (English)

    LIANG Jian-wen

    2005-01-01

    This paper proposes a method for simulation of non-stationary ground motion processes having the identical statistical feature, time-dependent power spectrum, with a given ground motion record, on the basis of review of simulation of non-stationary ground motion processes. The method has the following advantages: the sample processes are non-stationary both in amplitude and frequency, and both the amplitude and frequency non-stationarity depend on the target power spectrum; the power spectrum of any sample process does not necessarily accord with the target power spectrum, but statistically, it strictly accords with the target power spectrum. Finally, the method is verified by simulation of one acceleration record in Landers earthquake.

  2. Multivariate Analysis for the Processing of Signals

    Directory of Open Access Journals (Sweden)

    Beattie J.R.

    2014-01-01

    Full Text Available Real-world experiments are becoming increasingly more complex, needing techniques capable of tracking this complexity. Signal based measurements are often used to capture this complexity, where a signal is a record of a sample’s response to a parameter (e.g. time, displacement, voltage, wavelength that is varied over a range of values. In signals the responses at each value of the varied parameter are related to each other, depending on the composition or state sample being measured. Since signals contain multiple information points, they have rich information content but are generally complex to comprehend. Multivariate Analysis (MA has profoundly transformed their analysis by allowing gross simplification of the tangled web of variation. In addition MA has also provided the advantage of being much more robust to the influence of noise than univariate methods of analysis. In recent years, there has been a growing awareness that the nature of the multivariate methods allows exploitation of its benefits for purposes other than data analysis, such as pre-processing of signals with the aim of eliminating irrelevant variations prior to analysis of the signal of interest. It has been shown that exploiting multivariate data reduction in an appropriate way can allow high fidelity denoising (removal of irreproducible non-signals, consistent and reproducible noise-insensitive correction of baseline distortions (removal of reproducible non-signals, accurate elimination of interfering signals (removal of reproducible but unwanted signals and the standardisation of signal amplitude fluctuations. At present, the field is relatively small but the possibilities for much wider application are considerable. Where signal properties are suitable for MA (such as the signal being stationary along the x-axis, these signal based corrections have the potential to be highly reproducible, and highly adaptable and are applicable in situations where the data is noisy or

  3. Active control of shocks and sonic boom ground signal

    Science.gov (United States)

    Yagiz, Bedri

    The manipulation of a flow field to obtain a desired change is a much heightened subject. Active flow control has been the subject of the major research areas in fluid mechanics for the past two decades. It offers new solutions for mitigation of shock strength, sonic boom alleviation, drag minimization, reducing blade-vortex interaction noise in helicopters, stall control and the performance maximization of existing designs to meet the increasing requirements of the aircraft industries. Despite the wide variety of the potential applications of active flow control, the majority of studies have been performed at subsonic speeds. The active flow control cases were investigated in transonic speed in this study. Although the active flow control provides significant improvements, the sensibility of aerodynamic performance to design parameters makes it a nontrivial and expensive problem, so the designer has to optimize a number of different parameters. For the purpose of gaining understanding of the active flow control concepts, an automated optimization cycle process was generated. Also, the optimization cycle reduces cost and turnaround time. The mass flow coefficient, location, width and angle were chosen as design parameters to maximize the aerodynamic performance of an aircraft. As the main contribution of this study, a detailed parametric study and optimization process were presented. The second step is to appraise the practicability of weakening the shock wave and thereby reducing the wave drag in transonic flight regime using flow control devices such as two dimensional contour bump, individual jet actuator, and also the hybrid control which includes both control devices together, thereby gaining the desired improvements in aerodynamic performance of the air-vehicle. After this study, to improve the aerodynamic performance, the flow control and shape parameters are optimized separately, combined, and in a serial combination. The remarkable part of all these

  4. Intelligent Signal Processing for Detection System Optimization

    Energy Technology Data Exchange (ETDEWEB)

    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

    Energy Technology Data Exchange (ETDEWEB)

    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. Complexity of Receptor Tyrosine Kinase Signal Processing

    Science.gov (United States)

    Volinsky, Natalia; Kholodenko, Boris N.

    2013-01-01

    Our knowledge of molecular mechanisms of receptor tyrosine kinase (RTK) signaling advances with ever-increasing pace. Yet our understanding of how the spatiotemporal dynamics of RTK signaling control specific cellular outcomes has lagged behind. Systems-centered experimental and computational approaches can help reveal how overlapping networks of signal transducers downstream of RTKs orchestrate specific cell-fate decisions. We discuss how RTK network regulatory structures, which involve the immediate posttranslational and delayed transcriptional controls by multiple feed forward and feedback loops together with pathway cross talk, adapt cells to the combinatorial variety of external cues and conditions. This intricate network circuitry endows cells with emerging capabilities for RTK signal processing and decoding. We illustrate how mathematical modeling facilitates our understanding of RTK network behaviors by unraveling specific systems properties, including bistability, oscillations, excitable responses, and generation of intricate landscapes of signaling activities. PMID:23906711

  7. Improved Algorithms for Nanopore Signal Processing

    CERN Document Server

    Arjmandi, Nima; Lagae, Liesbet; Borghs, Gustaaf

    2012-01-01

    Nanopore resistive pulse techniques are based on analysis of current or voltage spikes in the recorded signal. These spikes result from translocation of nanometer sized analytes through a nanopore. The most important information that needs to be extracted is the duration, amplitude and number of the translocation spikes. The recorded signal is usually considerably noisy, with a huge baseline drift and hundreds of translocation spikes. Thus, incorporation of suitable signal processing algorithms is necessary for correct and fast detection of all the translocation spikes and to accurately measure their amplitude and duration. Generally, low-pass filtering is used for denoising, averaging is used for baseline detection, and thresholding is used for spike detection and measurement. Here we present novel algorithms and specifically developed software for nanopore signal processing that are significantly improving the accuracy of the nanopore measurements. It includes an improved method for baseline removing, an op...

  8. Sparse Signal Processing with Frame Theory

    CERN Document Server

    Mixon, Dustin G

    2012-01-01

    Many emerging applications involve sparse signals, and their processing is a subject of active research. We desire a large class of sensing matrices which allow the user to discern important properties of the measured sparse signal. Of particular interest are matrices with the restricted isometry property (RIP). RIP matrices are known to enable efficient and stable reconstruction of sufficiently sparse signals, but the deterministic construction of such matrices has proven very difficult. In this thesis, we discuss this matrix design problem in the context of a growing field of study known as frame theory. In the first two chapters, we build large families of equiangular tight frames and full spark frames, and we discuss their relationship to RIP matrices as well as their utility in other aspects of sparse signal processing. In Chapter 3, we pave the road to deterministic RIP matrices, evaluating various techniques to demonstrate RIP, and making interesting connections with graph theory and number theory. We ...

  9. Landmines Ground-Penetrating Radar Signal Enhancement by Digital Filtering

    OpenAIRE

    Potin, Delphine; Duflos, Emmanuel; Vanheeghe, Philippe

    2006-01-01

    Until now, humanitarian demining has been unable to provide a solution to the landmine removal problem. Furthermore, new low-cost methods have to be developed quickly. While much progress has been made with the introduction of new sensor types, other problems have been raised by these sensors. Ground-penetrating radars (GPRs) are key sensors for landmine detection as they are capable of detecting landmines with low metal contents. GPRs deliver so-called Bscan data, which are, roughly, vertica...

  10. Digital signal and image processing using MATLAB

    CERN Document Server

    Blanchet, Gérard

    2006-01-01

    This title provides the most important theoretical aspects of Image and Signal Processing (ISP) for both deterministic and random signals. The theory is supported by exercises and computer simulations relating to real applications.More than 200 programs and functions are provided in the MATLAB® language, with useful comments and guidance, to enable numerical experiments to be carried out, thus allowing readers to develop a deeper understanding of both the theoretical and practical aspects of this subject.

  11. Signal processing in cryogenic particle detection

    Energy Technology Data Exchange (ETDEWEB)

    Yuryev, Y.N. [Department of Physics and Astronomy, Seoul National University, Seoul (Korea, Republic of); Korea Research Institute of Standards and Science (KRISS), Daejeon (Korea, Republic of); Jang, Y.S. [Korea Research Institute of Standards and Science (KRISS), Daejeon (Korea, Republic of); Kim, S.K. [Department of Physics and Astronomy, Seoul National University, Seoul (Korea, Republic of); Lee, K.B.; Lee, M.K. [Korea Research Institute of Standards and Science (KRISS), Daejeon (Korea, Republic of); Lee, S.J. [Department of Physics and Astronomy, Seoul National University, Seoul (Korea, Republic of); Korea Research Institute of Standards and Science (KRISS), Daejeon (Korea, Republic of); Yoon, W.S. [Korea Research Institute of Standards and Science (KRISS), Daejeon (Korea, Republic of); Kim, Y.H., E-mail: yhkim@kriss.re.k [Korea Research Institute of Standards and Science (KRISS), Daejeon (Korea, Republic of)

    2011-04-11

    We describe a signal-processing program for a data acquisition system for cryogenic particle detectors. The program is based on an optimal-filtering method for high-resolution measurement of calorimetric signals with a significant amount of noise of unknown origin and non-stationary behavior. The program was applied to improve the energy resolution of the alpha particle spectrum of an {sup 241}Am source.

  12. Towards a repository for standardized medical image and signal case data annotated with ground truth.

    Science.gov (United States)

    Deserno, Thomas M; Welter, Petra; Horsch, Alexander

    2012-04-01

    Validation of medical signal and image processing systems requires quality-assured, representative and generally acknowledged databases accompanied by appropriate reference (ground truth) and clinical metadata, which are composed laboriously for each project and are not shared with the scientific community. In our vision, such data will be stored centrally in an open repository. We propose an architecture for a standardized case data and ground truth information repository supporting the evaluation and analysis of computer-aided diagnosis based on (a) the Reference Model for an Open Archival Information System (OAIS) provided by the NASA Consultative Committee for Space Data Systems (ISO 14721:2003), (b) the Dublin Core Metadata Initiative (DCMI) Element Set (ISO 15836:2009), (c) the Open Archive Initiative (OAI) Protocol for Metadata Harvesting, and (d) the Image Retrieval in Medical Applications (IRMA) framework. In our implementation, a portal bunches all of the functionalities that are needed for data submission and retrieval. The complete life cycle of the data (define, create, store, sustain, share, use, and improve) is managed. Sophisticated search tools make it easier to use the datasets, which may be merged from different providers. An integrated history record guarantees reproducibility. A standardized creation report is generated with a permanent digital object identifier. This creation report must be referenced by all of the data users. Peer-reviewed e-publishing of these reports will create a reputation for the data contributors and will form de-facto standards regarding image and signal datasets. Good practice guidelines for validation methodology complement the concept of the case repository. This procedure will increase the comparability of evaluation studies for medical signal and image processing methods and applications.

  13. Financial signal processing and machine learning

    CERN Document Server

    Kulkarni,Sanjeev R; Dmitry M. Malioutov

    2016-01-01

    The modern financial industry has been required to deal with large and diverse portfolios in a variety of asset classes often with limited market data available. Financial Signal Processing and Machine Learning unifies a number of recent advances made in signal processing and machine learning for the design and management of investment portfolios and financial engineering. This book bridges the gap between these disciplines, offering the latest information on key topics including characterizing statistical dependence and correlation in high dimensions, constructing effective and robust risk measures, and their use in portfolio optimization and rebalancing. The book focuses on signal processing approaches to model return, momentum, and mean reversion, addressing theoretical and implementation aspects. It highlights the connections between portfolio theory, sparse learning and compressed sensing, sparse eigen-portfolios, robust optimization, non-Gaussian data-driven risk measures, graphical models, causal analy...

  14. Nonlinear filtering for LIDAR signal processing

    Directory of Open Access Journals (Sweden)

    D. G. Lainiotis

    1996-01-01

    Full Text Available LIDAR (Laser Integrated Radar is an engineering problem of great practical importance in environmental monitoring sciences. Signal processing for LIDAR applications involves highly nonlinear models and consequently nonlinear filtering. Optimal nonlinear filters, however, are practically unrealizable. In this paper, the Lainiotis's multi-model partitioning methodology and the related approximate but effective nonlinear filtering algorithms are reviewed and applied to LIDAR signal processing. Extensive simulation and performance evaluation of the multi-model partitioning approach and its application to LIDAR signal processing shows that the nonlinear partitioning methods are very effective and significantly superior to the nonlinear extended Kalman filter (EKF, which has been the standard nonlinear filter in past engineering applications.

  15. Genomic Signal Processing: The Salient Issues

    Directory of Open Access Journals (Sweden)

    Shmulevich Ilya

    2004-01-01

    Full Text Available This paper considers key issues in the emerging field of genomic signal processing and its relationship to functional genomics. It focuses on some of the biological mechanisms driving the development of genomic signal processing, in addition to their manifestation in gene-expression-based classification and genetic network modeling. Certain problems are inherent. For instance, small-sample error estimation, variable selection, and model complexity are important issues for both phenotype classification and expression prediction used in network inference. A long-term goal is to develop intervention strategies to drive network behavior, which is briefly discussed. It is hoped that this nontechnical paper demonstrates that the field of signal processing has the potential to impact and help drive genomics research.

  16. Designer cell signal processing circuits for biotechnology.

    Science.gov (United States)

    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.

  17. Python for signal processing featuring IPython notebooks

    CERN Document Server

    Unpingco, José

    2013-01-01

    This book covers the fundamental concepts in signal processing illustrated with Python code and made available via IPython Notebooks, which are live, interactive, browser-based documents that allow one to change parameters, redraw plots, and tinker with the ideas presented in the text. Everything in the text is computable in this format and thereby invites readers to ""experiment and learn"" as they read. The book focuses on the core, fundamental principles of signal processing. The code corresponding to this book uses the core functionality of the scientific Python toolchain that should remai

  18. An introduction to digital signal processing

    CERN Document Server

    Karl, John H

    1989-01-01

    An Introduction to Digital Signal Processing is written for those who need to understand and use digital signal processing and yet do not wish to wade through a multi-semester course sequence. Using only calculus-level mathematics, this book progresses rapidly through the fundamentals to advanced topics such as iterative least squares design of IIR filters, inverse filters, power spectral estimation, and multidimensional applications--all in one concise volume.This book emphasizes both the fundamental principles and their modern computer implementation. It presents and demonstrates how si

  19. Signal Processing Methods Monitor Cranial Pressure

    Science.gov (United States)

    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.

  20. Estimation of source location and ground impedance using a hybrid multiple signal classification and Levenberg-Marquardt approach

    Science.gov (United States)

    Tam, Kai-Chung; Lau, Siu-Kit; Tang, Shiu-Keung

    2016-07-01

    A microphone array signal processing method for locating a stationary point source over a locally reactive ground and for estimating ground impedance is examined in detail in the present study. A non-linear least square approach using the Levenberg-Marquardt method is proposed to overcome the problem of unknown ground impedance. The multiple signal classification method (MUSIC) is used to give the initial estimation of the source location, while the technique of forward backward spatial smoothing is adopted as a pre-processer of the source localization to minimize the effects of source coherence. The accuracy and robustness of the proposed signal processing method are examined. Results show that source localization in the horizontal direction by MUSIC is satisfactory. However, source coherence reduces drastically the accuracy in estimating the source height. The further application of Levenberg-Marquardt method with the results from MUSIC as the initial inputs improves significantly the accuracy of source height estimation. The present proposed method provides effective and robust estimation of the ground surface impedance.

  1. Processing oscillatory signals by incoherent feedforward loops

    Science.gov (United States)

    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).

  2. Electrochemical noise minimization using digital signal processing

    Directory of Open Access Journals (Sweden)

    Claudia Smaniotto Barin

    2004-01-01

    Full Text Available This work discusses electrochemical noise in low amplitude signals and reviews the bibliography on signal iltering methods used to reduce noise interference. One of these methods, the Singular Spectrum Analysis (SSA, is described in detail and used to filter some signals in electrostatic deposition experiments. This study also compares results from other filtering techniques such as moving average, Stavitsky-Golay and Fourier and Wavelet, and discusses the advantages and disadvantages of transforms. Results have shown that the SSA method is efficient, of easy applicability, and extremely important for the understanding of electrodeposition characteristics. In the Introduction of this work, the origin of the signals is discussed, and the advantages, problems and the noise filtering techniques related to electrical deposition through microelectrodes are presented. In the Theory section, the SSA method is described, and the reasons for using it with noisy signals are presented. In the Materials and Methods section, the equipment and software used for collecting and processing the signals are described briefly. Finally, in the Results section, the signals reconstructed through SSA, as well as those found in other filtering techniques are presented.

  3. Wavelength-domain RF photonic signal processing

    Science.gov (United States)

    Gao, Lu

    This thesis presents a novel approach to RF-photonic signal processing applications based on wavelength-domain optical signal processing techniques using broadband light sources as the information carriers, such as femtosecond lasers and white light sources. The wavelength dimension of the broadband light sources adds an additional degree of freedom to conventional optical signal processing systems. Two novel wavelength-domain optical signal processing systems are presented and demonstrated in this thesis. The first wavelength-domain RF photonic signal processing system is a wavelength-compensated squint-free photonic multiple beam-forming system for wideband RF phased-array antennas. Such a photonic beam-forming system employs a new modulation scheme developed in this thesis, which uses traveling-wave tunable filters to modulate wideband RF signals onto broadband optical light sources in a frequency-mapped manner. The wavelength dimension of the broadband light sources provides an additional dimension in the wavelength-compensated Fourier beam-forming system for mapping the received RF frequencies to the linearly proportional optical frequencies, enabling true-time-delay beam forming, as well as other novel RF-photonic signal processing functions such as tunable filtering and frequency down conversion. A new slow-light mechanism, the SLUGGISH light, has also been discovered with an effective slow-light velocity of 86 m/s and a record time-bandwidth product of 20. Experimental demonstration of true-time-delay beam forming based on the SLUGGISH light effect has also been presented in this thesis. In the second wavelength-domain RF photonic signal processing system, the wavelength dimension increases the information carrying capacity by spectrally multiplexing multiple wavelength channels in a wavelength-division-multiplexing fiber-optic communication system. A novel ultrafast all-optical 3R (Re-amplification, Retiming, Re-shaping) wavelength converter based on

  4. Stimulus Contrast and Retinogeniculate Signal Processing.

    Science.gov (United States)

    Rathbun, Daniel L; Alitto, Henry J; Warland, David K; Usrey, W Martin

    2016-01-01

    Neuronal signals conveying luminance contrast play a key role in nearly all aspects of perception, including depth perception, texture discrimination, and motion perception. Although much is known about the retinal mechanisms responsible for encoding contrast information, relatively little is known about the relationship between stimulus contrast and the processing of neuronal signals between visual structures. Here, we describe simultaneous recordings from monosynaptically connected retinal ganglion cells and lateral geniculate nucleus (LGN) neurons in the cat to determine how stimulus contrast affects the communication of visual signals between the two structures. Our results indicate that: (1) LGN neurons typically reach their half-maximal response at lower contrasts than their individual retinal inputs and (2) LGN neurons exhibit greater contrast-dependent phase advance (CDPA) than their retinal inputs. Further analyses suggests that increased sensitivity relies on spatial convergence of multiple retinal inputs, while increased CDPA is achieved, in part, on temporal summation of arriving signals.

  5. Stimulus contrast and retinogeniculate signal processing

    Directory of Open Access Journals (Sweden)

    Daniel Llewellyn Rathbun

    2016-02-01

    Full Text Available Neuronal signals conveying luminance contrast play a key role in nearly all aspects of perception, including depth perception, texture discrimination, and motion perception. Although much is known about the retinal mechanisms responsible for encoding contrast information, relatively little is known about the relationship between stimulus contrast and the processing of neuronal signals between visual structures. Here we describe simultaneous recordings from monosynaptically connected retinal ganglion cells and lateral geniculate nucleus (LGN neurons in the cat to determine how stimulus contrast affects the communication of visual signals between the two structures. Our results indicate that 1 LGN neurons typically reach their half-maximal response at lower contrasts than their individual retinal inputs, and 2 LGN neurons exhibit greater contrast-dependent phase advance (CDPA than their retinal inputs. Further analyses suggests that increased sensitivity relies on spatial convergence of multiple retinal inputs, while increased CDPA is achieved, in part, on temporal summation of arriving signals.

  6. Digital signal processing techniques for on-board processing satellites

    Science.gov (United States)

    Kwan, Ching Chung

    1990-08-01

    In on-board processing satellite systems in which frequency division multiple access (FDMA)/signal channel per carrier (SCPC) access schemes are employed, transmultiplexers are required for the frequency demultiplexing of the SCPC signals. Digital techniques for the implementation of the transmultiplexer for such application were examined. The signal processing in the transmultiplexer operations involved many parameters which could be optimized in order to reduce the hardware complexity while satisfying the level of performance required of the system. An approach for the assessment of the relationship between the various parameters and the system performance was devised, which allowed hardware requirement of practical system specifications to be estimated. For systems involving signals of different bandwidths, a more flexible implementation of the transmultiplexer is required and two computationally efficient methods, the DFT convolution and analysis/synthesis filter bank, were investigated. These methods gave greater flexibility to the input frequency plan of the transmultiplexer, at the expense of increased computational requirements. Filters were then designed to exploit specific properties of the flexible transmultiplexer methods, resulting in considerable improvement in their efficiencies. Hardware implementation of the flexible transmultiplexer was considered and an efficient multiprocesser architecture in combination with parallel processing software algorithms for the signal processing operations were designed. Finally, an experimental model of the payload for a land-mobile satellite system proposal, T-SAT, was constructed using general-purpose digital signal processors and the merits of the on-board processing architecture were demonstrated.

  7. Liquid argon TPC signal formation, signal processing and reconstruction techniques

    Science.gov (United States)

    Baller, B.

    2017-07-01

    This document describes a reconstruction chain that was developed for the ArgoNeuT and MicroBooNE experiments at Fermilab. These experiments study accelerator neutrino interactions that occur in a Liquid Argon Time Projection Chamber. Reconstructing the properties of particles produced in these interactions benefits from the knowledge of the micro-physics processes that affect the creation and transport of ionization electrons to the readout system. A wire signal deconvolution technique was developed to convert wire signals to a standard form for hit reconstruction, to remove artifacts in the electronics chain and to remove coherent noise. A unique clustering algorithm reconstructs line-like trajectories and vertices in two dimensions which are then matched to create of 3D objects. These techniques and algorithms are available to all experiments that use the LArSoft suite of software.

  8. Ionospheric turbulence from ground-based and satellite VLF/LF transmitter signal observations for the Simushir earthquake (November 15, 2006

    Directory of Open Access Journals (Sweden)

    Pier Francesco Biagi

    2012-04-01

    Full Text Available

    Signals from very low frequency (VLF/ low frequency (LF transmitters recorded on the ground station at Petropavlovsk-Kamchatsky and on board the French DEMETER satellite were analyzed for the Simushir earthquake (M 8.3; November 15, 2006. The period of analysis was from October 1, 2006, to January 31, 2007. The ground and satellite data were processed by a method based on the difference between the real signal at night-time and the model signal. The model for the ground observations was the monthly averaged signal amplitudes and phases, as calculated for the quiet days of every month. For the satellite data, a two-dimensional model of the signal distribution over the selected area was constructed. Preseismic effects were found several days before the earthquake, in both the ground and satellite observations.

     

  9. Signal Processing for Digital Beamforming FMCW SAR

    Directory of Open Access Journals (Sweden)

    Qin Xin

    2014-01-01

    Full Text Available According to the limitations of single channel Frequency Modulation Continuous Wave (FMCW Synthetic Aperture Radar (SAR, Digital Beamforming (DBF technology is introduced to improve system performance. Combined with multiple receive apertures, DBF FMCW SAR can obtain high resolution in low pulse repetition frequency, which can increase the processing gain and decrease the sampling frequency. The received signal model of DBF FMCW SAR is derived. The continuous antenna motion which is the main characteristic of FMCW SAR received signal is taken into account in the whole signal processing. The detailed imaging diagram of DBF FMCW SAR is given. A reference system is also demonstrated in the paper by comparing with a single channel FMCW SAR. The validity of the presented diagram is demonstrated with a point target simulation results.

  10. CMOS circuits for analog signal processing

    NARCIS (Netherlands)

    Wallinga, Hans

    1988-01-01

    Design choices in CMOS analog signal processing circuits are presented. Special attention is focussed on continuous-time filter technologies. The basics of MOSFET-C continuous-time filters and CMOS Square Law Circuits are explained at the hand of a graphical MOST characteristics representation.

  11. Optimisation in signal and image processing

    CERN Document Server

    Siarry, Patrick

    2010-01-01

    This book describes the optimization methods most commonly encountered in signal and image processing: artificial evolution and Parisian approach; wavelets and fractals; information criteria; training and quadratic programming; Bayesian formalism; probabilistic modeling; Markovian approach; hidden Markov models; and metaheuristics (genetic algorithms, ant colony algorithms, cross-entropy, particle swarm optimization, estimation of distribution algorithms, and artificial immune systems).

  12. A Virtual Laboratory for Digital Signal Processing

    Science.gov (United States)

    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…

  13. Computer Aided Teaching of Digital Signal Processing.

    Science.gov (United States)

    Castro, Ian P.

    1990-01-01

    Describes a microcomputer-based software package developed at the University of Surrey for teaching digital signal processing to undergraduate science and engineering students. Menu-driven software capabilities are explained, including demonstration of qualitative concepts and experimentation with quantitative data, and examples are given of…

  14. Distributed radiofrequency signal processing using multicore fibers

    Science.gov (United States)

    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.

  15. Digital signal processing with Matlab examples

    CERN Document Server

    Giron-Sierra, Jose Maria

    2017-01-01

    This is the first volume in a trilogy on modern Signal Processing. The three books provide a concise exposition of signal processing topics, and a guide to support individual practical exploration based on MATLAB programs. This book includes MATLAB codes to illustrate each of the main steps of the theory, offering a self-contained guide suitable for independent study. The code is embedded in the text, helping readers to put into practice the ideas and methods discussed. The book is divided into three parts, the first of which introduces readers to periodic and non-periodic signals. The second part is devoted to filtering, which is an important and commonly used application. The third part addresses more advanced topics, including the analysis of real-world non-stationary signals and data, e.g. structural fatigue, earthquakes, electro-encephalograms, birdsong, etc. The book’s last chapter focuses on modulation, an example of the intentional use of non-stationary signals.

  16. Wavelet based methods for improved wind profiler signal processing

    Directory of Open Access Journals (Sweden)

    V. Lehmann

    Full Text Available In this paper, we apply wavelet thresholding for removing automatically ground and intermittent clutter (airplane echoes from wind profiler radar data. Using the concept of discrete multi-resolution analysis and non-parametric estimation theory, we develop wavelet domain thresholding rules, which allow us to identify the coefficients relevant for clutter and to suppress them in order to obtain filtered reconstructions.

    Key words. Meteorology and atmospheric dynamics (instruments and techniques – Radio science (remote sensing; signal processing

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

    Energy Technology Data Exchange (ETDEWEB)

    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.

  18. Feature Extraction and Classification of Echo Signal of Ground Penetrating Radar

    Institute of Scientific and Technical Information of China (English)

    ZHOU Hui-lin; TIAN Mao; CHEN Xiao-li

    2005-01-01

    Automatic feature extraction and classification algorithm of echo signal of ground penetrating radar is presented. Dyadic wavelet transform and the average energy of the wavelet coefficients are applied in this paper to decompose and extract feature of the echo signal. Then, the extracted feature vector is fed up to a feed-forward multi-layer perceptron classifier. Experimental results based on the measured GPR echo signals obtained from the Mei-shan railway are presented.

  19. Digital signal and image processing using Matlab

    CERN Document Server

    Blanchet , Gérard

    2015-01-01

    The most important theoretical aspects of Image and Signal Processing (ISP) for both deterministic and random signals, the theory being supported by exercises and computer simulations relating to real applications.   More than 200 programs and functions are provided in the MATLAB® language, with useful comments and guidance, to enable numerical experiments to be carried out, thus allowing readers to develop a deeper understanding of both the theoretical and practical aspects of this subject.  Following on from the first volume, this second installation takes a more practical stance, provi

  20. Digital signal and image processing using MATLAB

    CERN Document Server

    Blanchet , Gérard

    2014-01-01

    This fully revised and updated second edition presents the most important theoretical aspects of Image and Signal Processing (ISP) for both deterministic and random signals. The theory is supported by exercises and computer simulations relating to real applications. More than 200 programs and functions are provided in the MATLABÒ language, with useful comments and guidance, to enable numerical experiments to be carried out, thus allowing readers to develop a deeper understanding of both the theoretical and practical aspects of this subject. This fully revised new edition updates : - the

  1. Gossip Algorithms for Distributed Signal Processing

    CERN Document Server

    Dimakis, Alexandros G; Moura, Jose M F; Rabbat, Michael G; Scaglione, Anna

    2010-01-01

    Gossip algorithms are attractive for in-network processing in sensor networks because they do not require any specialized routing, there is no bottleneck or single point of failure, and they are robust to unreliable wireless network conditions. Recently, there has been a surge of activity in the computer science, control, signal processing, and information theory communities, developing faster and more robust gossip algorithms and deriving theoretical performance guarantees. This article presents an overview of recent work in the area. We describe convergence rate results, which are related to the number of transmitted messages and thus the amount of energy consumed in the network for gossiping. We discuss issues related to gossiping over wireless links, including the effects of quantization and noise, and we illustrate the use of gossip algorithms for canonical signal processing tasks including distributed estimation, source localization, and compression.

  2. Time synchronization and carrier frequency control of CAPS navigation signals generated on the ground

    Institute of Scientific and Technical Information of China (English)

    2009-01-01

    The Chinese Area Positioning System (CAPS) works without atomic clocks on the satellite, and the CAPS navigation signals transmitted on the ground may achieve the same effect as that with high-performance atomic clocks on the satellite. The primary means of achieving that effect is through the time synchronization and carrier frequency control of the CAPS navigation signals generated on the ground. In this paper the synchronization requirements of different time signals are analyzed by the formation of navigation signals, and the theories and methods of the time synchronization of the CAPS navigation signals generated on the ground are also introduced. According to the conditions of the high-precision satellite velocitymeasurement signal source, the carrier frequency and its chains of the navigation signals are constructed. CAPS velocity measurement is realized by the expected deviation of real time control to the carrier frequency, and the precision degree of this method is also analyzed. The experimental results show that the time synchronization precision of CAPS generating signals is about 0.3 ns and the precision of the velocity measurement signal source is about 4 cm/s. This proves that the theories and methods of the generating time synchronization and carrier frequency control are workable.

  3. Time synchronization and carrier frequency control of CAPS navigation signals generated on the ground

    Institute of Scientific and Technical Information of China (English)

    WU HaiTao; BIAN YuJing; LU XiaoChun; LI XiaoHui; WANG DanNi

    2009-01-01

    The Chinese Area Positioning System (CAPS) works without atomic clocks on the satellite,and the CAPS navigation signals transmitted on the ground may achieve the same effect as that with high-performance atomic clocks on the satellite.The primary means of achieving that effect is through the time synchronization and carrier frequency control of the CAPS navigation signals generated on the ground.In this paper the synchronization requirements of different time signals are analyzed by the formation of navigation signals,and the theories and methods of the time synchronization of the CAPS navigation signals generated on the ground are also introduced.According to the conditions of the high-precision satellite velocity-measurement signal source,the carrier frequency and its chains of the navigation signals are constructed.CAPS velocity measurement is realized by the expected deviation of real time control to the carrier frequency,end the precision degree of this method is also analyzed.The experimental results show that the time synchronization precision of CAPS generating signals is about 0.3 ns and the precision of the velocity measurement signal source is about 4 cm/s.This proves that the theories and methods of the generating time synchronization and carrier frequency control are workable.

  4. Detection capability of a pulsed Ground Penetrating Radar utilizing an oscilloscope and Radargram Fusion Approach for optimal signal quality

    Science.gov (United States)

    Seyfried, Daniel; Schoebel, Joerg

    2015-07-01

    In scientific research pulsed radars often employ a digital oscilloscope as sampling unit. The sensitivity of an oscilloscope is determined in general by means of the number of digits of its analog-to-digital converter and the selected full scale vertical setting, i.e., the maximal voltage range displayed. Furthermore oversampling or averaging of the input signal may increase the effective number of digits, hence the sensitivity. Especially for Ground Penetrating Radar applications high sensitivity of the radar system is demanded since reflection amplitudes of buried objects are strongly attenuated in ground. Hence, in order to achieve high detection capability this parameter is one of the most crucial ones. In this paper we analyze the detection capability of our pulsed radar system utilizing a Rohde & Schwarz RTO 1024 oscilloscope as sampling unit for Ground Penetrating Radar applications, such as detection of pipes and cables in the ground. Also effects of averaging and low-noise amplification of the received signal prior to sampling are investigated by means of an appropriate laboratory setup. To underline our findings we then present real-world radar measurements performed on our GPR test site, where we have buried pipes and cables of different types and materials in different depths. The results illustrate the requirement for proper choice of the settings of the oscilloscope for optimal data recording. However, as we show, displaying both strong signal contributions due to e.g., antenna cross-talk and direct ground bounce reflection as well as weak reflections from objects buried deeper in ground requires opposing trends for the oscilloscope's settings. We therefore present our Radargram Fusion Approach. By means of this approach multiple radargrams recorded in parallel, each with an individual optimized setting for a certain type of contribution, can be fused in an appropriate way in order to finally achieve a single radargram which displays all

  5. Advanced Signal Processing for Wireless Multimedia Communications

    Directory of Open Access Journals (Sweden)

    Xiaodong Wang

    2000-01-01

    Full Text Available There is at present a worldwide effort to develop next-generation wireless communication systems. It is envisioned that many of the future wireless systems will incorporate considerable signal-processing intelligence in order to provide advanced services such as multimedia transmission. In general, wireless channels can be very hostile media through which to communicate, due to substantial physical impediments, primarily radio-frequency interference and time-arying nature of the channel. The need of providing universal wireless access at high data-rate (which is the aim of many merging wireless applications presents a major technical challenge, and meeting this challenge necessitates the development of advanced signal processing techniques for multiple-access communications in non-stationary interference-rich environments. In this paper, we present some key advanced signal processing methodologies that have been developed in recent years for interference suppression in wireless networks. We will focus primarily on the problem of jointly suppressing multiple-access interference (MAI and intersymbol interference (ISI, which are the limiting sources of interference for the high data-rate wireless systems being proposed for many emerging application areas, such as wireless multimedia. We first present a signal subspace approach to blind joint suppression of MAI and ISI. We then discuss a powerful iterative technique for joint interference suppression and decoding, so-called Turbo multiuser detection, that is especially useful for wireless multimedia packet communications. We also discuss space-time processing methods that employ multiple antennas for interference rejection and signal enhancement. Finally, we touch briefly on the problems of suppressing narrowband interference and impulsive ambient noise, two other sources of radio-frequency interference present in wireless multimedia networks.

  6. An autonomous receiver/digital signal processor applied to ground-based and rocket-borne wave experiments

    Science.gov (United States)

    Dombrowski, M. P.; LaBelle, J.; McGaw, D. G.; Broughton, M. C.

    2016-07-01

    The programmable combined receiver/digital signal processor platform presented in this article is designed for digital downsampling and processing of general waveform inputs with a 66 MHz initial sampling rate and multi-input synchronized sampling. Systems based on this platform are capable of fully autonomous low-power operation, can be programmed to preprocess and filter the data for preselection and reduction, and may output to a diverse array of transmission or telemetry media. We describe three versions of this system, one for deployment on sounding rockets and two for ground-based applications. The rocket system was flown on the Correlation of High-Frequency and Auroral Roar Measurements (CHARM)-II mission launched from Poker Flat Research Range, Alaska, in 2010. It measured auroral "roar" signals at 2.60 MHz. The ground-based systems have been deployed at Sondrestrom, Greenland, and South Pole Station, Antarctica. The Greenland system synchronously samples signals from three spaced antennas providing direction finding of 0-5 MHz waves. It has successfully measured auroral signals and man-made broadcast signals. The South Pole system synchronously samples signals from two crossed antennas, providing polarization information. It has successfully measured the polarization of auroral kilometric radiation-like signals as well as auroral hiss. Further systems are in development for future rocket missions and for installation in Antarctic Automatic Geophysical Observatories.

  7. Signals, processes, and systems an interactive multimedia introduction to signal processing

    CERN Document Server

    Karrenberg, Ulrich

    2013-01-01

    This is a very new concept for learning Signal Processing, not only from the physically-based scientific fundamentals, but also from the didactic perspective, based on modern results of brain research. The textbook together with the DVD form a learning system that provides investigative studies and enables the reader to interactively visualize even complex processes. The unique didactic concept is built on visualizing signals and processes on the one hand, and on graphical programming of signal processing systems on the other. The concept has been designed especially for microelectronics, computer technology and communication. The book allows to develop, modify, and optimize useful applications using DasyLab - a professional and globally supported software for metrology and control engineering. With the 3rd edition, the software is also suitable for 64 bit systems running on Windows 7. Real signals can be acquired, processed and played on the sound card of your computer. The book provides more than 200 pre-pr...

  8. Masking interrupts figure-ground signals in V1

    NARCIS (Netherlands)

    Lamme, V.A.F.; Zipser, K.; Spekreijse, H.

    2002-01-01

    In a backward masking paradigm, a target stimulus is rapidly (<100 msec) followed by a second Stimulus. This typically results in a dramatic decrease in the visibility of the target stimulus. It has been shown that masking reduces responses in V1. It is not known, however, which process in V1 is aff

  9. Broadband Nonlinear Signal Processing in Silicon Nanowires

    DEFF Research Database (Denmark)

    Yvind, Kresten; Pu, Minhao; Hvam, Jørn Märcher;

    The fast non-linearity of silicon allows Tbit/s optical signal processing. By choosing suitable dimensions of silicon nanowires their dispersion can be tailored to ensure a high nonlinearity at power levels low enough to avoid significant two-photon abso We have fabricated low insertion and propa......The fast non-linearity of silicon allows Tbit/s optical signal processing. By choosing suitable dimensions of silicon nanowires their dispersion can be tailored to ensure a high nonlinearity at power levels low enough to avoid significant two-photon abso We have fabricated low insertion...... and propagation loss silicon nanowires and use them to demonstrate the broadband capabilities of silicon....

  10. Haptic teleoperation systems signal processing perspective

    CERN Document Server

    Lee, Jae-young

    2015-01-01

    This book examines the signal processing perspective in haptic teleoperation systems. This text covers the topics of prediction, estimation, architecture, data compression, and error correction that can be applied to haptic teleoperation systems. The authors begin with an overview of haptic teleoperation systems, then look at a Bayesian approach to haptic teleoperation systems. They move onto a discussion of haptic data compression, haptic data digitization and forward error correction.   ·         Presents haptic data prediction/estimation methods that compensate for unreliable networks   ·         Discusses haptic data compression that reduces haptic data size over limited network bandwidth and haptic data error correction that compensate for packet loss problem   ·         Provides signal processing techniques used with existing control architectures.

  11. Signal Detection for Pareto Renewal Processes.

    Science.gov (United States)

    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

  12. Simulation of non-stationary ground motion processes (I)

    Institute of Scientific and Technical Information of China (English)

    LIANG Jian-wen

    2005-01-01

    This paper presents a spectral representation method for simulation of non-stationary ground motion processes on the basis of Priestley's evolutionary spectral theory. Following this method, sample processes can be generated using a cosine series formula. It is shown that, these sample processes accurately reflect the prescribed characteristics of the evolutionary power spectral density function when the number of the terms in the cosine series is large enough; and the ensemble expected value and the ensemble autocorrelation function approach the corresponding target functions, respectively, as the sample size increases; and these sample processes are asymptotically normal as the number of the terms in the series tends to infinity. Finally, a few special cases of the formula are discussed, one of which is non-stationary white noise process, and other one is reduced to the formula for simulation of stationary stochastic processes.

  13. UMTRA Ground Water Project management action process document

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1996-03-01

    A critical U.S. Department of Energy (DOE) mission is to plan, implement, and complete DOE Environmental Restoration (ER) programs at facilities that were operated by or in support of the former Atomic Energy Commission (AEC). These facilities include the 24 inactive processing sites the Uranium Mill Tailings Radiation Control Act (UMTRCA) (42 USC Section 7901 et seq.) identified as Title I sites, which had operated from the late 1940s through the 1970s. In UMTRCA, Congress acknowledged the potentially harmful health effects associated with uranium mill tailings and directed the DOE to stabilize, dispose of, and control the tailings in a safe and environmentally sound manner. The UMTRA Surface Project deals with buildings, tailings, and contaminated soils at the processing sites and any associated vicinity properties (VP). Surface remediation at the processing sites will be completed in 1997 when the Naturita, Colorado, site is scheduled to be finished. The UMTRA Ground Water Project was authorized in an amendment to the UMTRCA (42 USC Section 7922(a)), when Congress directed DOE to comply with U.S. Environmental Protection Agency (EPA) ground water standards. The UMTRA Ground Water Project addresses any contamination derived from the milling operation that is determined to be present at levels above the EPA standards.

  14. Electric Signals on and under the Ground Surface Induced by Seismic Waves

    Directory of Open Access Journals (Sweden)

    Akihiro Takeuchi

    2012-01-01

    Full Text Available We constructed three observation sites in northeastern Japan (Honjo, Kyowa, and Sennan with condenser-type large plate electrodes (4 × 4 m2 as sensors supported 4 m above the ground and with pairs of reference electrodes buried vertically at 0.5 m and 2.5 m depth (with a ground velocity sensor at Sennan only. Electrical signals of an earthquake (M6.3 in northeastern Japan were detected simultaneously with seismic waves. Their waveforms were damped oscillations, with greatly differing signal amplitudes among sites. Good positive correlation was found between the amplitudes of signals detected by all electrodes. We propose a signal generation model: seismic acceleration vertically shook pore water in the topsoil, generating the vertical streaming potential between the upper unsaturated water zone and the lower saturated water zone. Maximum electric earth potential difference was observed when one electrode was in the saturated water zone, and the other was within the unsaturated water zone, but not when the electrodes were in the saturated water zone. The streaming potential formed a charge on the ground surface, generating a vertical atmospheric electric field. The large plate electrode detected electric signals related to electric potential differences between the electrode and the ground surface.

  15. Contemporary Challenges for a Social Signal processing

    Directory of Open Access Journals (Sweden)

    Dr.T.KishoreKumar

    2012-12-01

    Full Text Available This paper provides a short overview of Social Signal Processing. The exploration of how we react to the world and interact with it and each other remains one of the greatest scientific challenges. Latest research trends in cognitive sciences argue that our common view of intelligence is too narrow, ignoring a crucial range of abilities that matter immensely for how people do in life. This range of abilities is called social intelligence and includes the ability to express and recognize social signals produced during social interactions like agreement, politeness, empathy, friendliness, conflict, etc., coupled with the ability to manage them in order to get along well with others while winning their cooperation. Social Signal Processing (SSP is the new research domain that aims at understanding and modeling social interactions (human-science goals, and at providing computers with similar abilities in human-computer interaction scenarios (technological goals. SSP is in its infancy and the journey towards artificial social intelligence and socially-aware computing is still long, the paper outlines its future perspectives and some of its most promising applications.

  16. Ground Motions Induced by Precipitation and Fluvial Processes: An Example from Taiwan

    Science.gov (United States)

    Yang, Chu-Fang; Chi, Wu-Cheng; Lai, Ying-Ju

    2016-04-01

    Ground motions can be induced by weather-related processes. Analyzing such signals might help quantify those natural processes. Here, we used continuous seismic, meteorological and stream data to analyze broadband ground motions during heavy precipitation events in Taiwan. We detected long period seismic signals in drainage basins during two meteorological cases: Typhoon Morakot in 2009 and East Asian rainy season in 2012. The amplitudes of the seismic waveform correlate well with the amount of the precipitation and the derivative of water level and discharge in a nearby river. We proposed that these seismic signals were induced by ground tilt induced by the loading from the increased water volume in the nearby river. Furthermore, we used the seismic data to estimate and quantify the strength of precipitation during such events. The seismically derived precipitation correlates well with the observed meteorological data. It shows that the long period seismic data may be used to monitor rainfall in real-time. Next, we will try to test our tilt hypothesis using other independent datasets.

  17. Integrated Circuits for Analog Signal Processing

    CERN Document Server

    2013-01-01

      This book presents theory, design methods and novel applications for integrated circuits for analog signal processing.  The discussion covers a wide variety of active devices, active elements and amplifiers, working in voltage mode, current mode and mixed mode.  This includes voltage operational amplifiers, current operational amplifiers, operational transconductance amplifiers, operational transresistance amplifiers, current conveyors, current differencing transconductance amplifiers, etc.  Design methods and challenges posed by nanometer technology are discussed and applications described, including signal amplification, filtering, data acquisition systems such as neural recording, sensor conditioning such as biomedical implants, actuator conditioning, noise generators, oscillators, mixers, etc.   Presents analysis and synthesis methods to generate all circuit topologies from which the designer can select the best one for the desired application; Includes design guidelines for active devices/elements...

  18. Efficient audio signal processing for embedded systems

    Science.gov (United States)

    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

  19. The early ELF signals of the gigantic jets captured by the Taiwan ground observation network

    Science.gov (United States)

    Chen, A. B. C.; Huang, P. H.; Su, H. T.; Hsu, R. R.

    2015-12-01

    The in-cloud ignition process of gigantic jets and blue jets receives attentions and discussions in the past years. The polarity and the position of their breakdown were proposed by Krehbiel et al. [2008] but no concrete observational evidence to support it directly. ELF spectrogram is a good tool to explore the electric activities, but traditional spectrograms are generated by a Fourier transform which obtain the frequency information through an integration operation. However the integration greatly limits the lowest frequency revealed by spectrogram and buries the important transient features. In this study, we applied a new but widely-used method, the Hilbert-Huang transform (HHT), to explore the spectrogram. Instead of the integration, HHT obtains the frequency information by differentiating on the phase angle, and become a powerful tool to reveal the fast frequency variation associated with transient luminous events. More than 100 transient luminous events including 25 gigantic jets observed by Taiwan ground optical observation network were analyzed. The results indicate that approximately 70% of gigantic jets can identify a rapid frequency variation in the interval of 300-600 milliseconds before main surge discharge, and this early feature can not find a clear corresponding amplitude variation in its sferic. Since this early signal can not be identified from the traditional Fourier spectrogram, but clear in-cloud lightning was registered correspondingly by the ground optical observation. In contrast to gigantic jets, this feature of early frequency change can be seen only in less than 30% of sprites and elves. These observational evidences are able to provide new constraints on the early discharge process of gigantic jets in clouds.

  20. Seismic signal processing on heterogeneous supercomputers

    Science.gov (United States)

    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

  1. Fourier transforms in radar and signal processing

    CERN Document Server

    Brandwood, David

    2011-01-01

    Fourier transforms are used widely, and are of particular value in the analysis of single functions and combinations of functions found in radar and signal processing. Still, many problems that could have been tackled by using Fourier transforms may have gone unsolved because they require integration that is difficult and tedious. This newly revised and expanded edition of a classic Artech House book provides you with an up-to-date, coordinated system for performing Fourier transforms on a wide variety of functions. Along numerous updates throughout the book, the Second Edition includes a crit

  2. Power systems signal processing for smart grids

    CERN Document Server

    Ribeiro, Paulo Fernando; Ribeiro, Paulo Márcio; Cerqueira, Augusto Santiago

    2013-01-01

    With special relation to smart grids, this book provides clear and comprehensive explanation of how Digital Signal Processing (DSP) and Computational Intelligence (CI) techniques can be applied to solve problems in the power system. Its unique coverage bridges the gap between DSP, electrical power and energy engineering systems, showing many different techniques applied to typical and expected system conditions with practical power system examples. Surveying all recent advances on DSP for power systems, this book enables engineers and researchers to understand the current state of the art a

  3. Digital signal processing for radioactive decay studies

    Energy Technology Data Exchange (ETDEWEB)

    Miller, D.; Madurga, M.; Paulauskas, S. V. [Department of Physics and Astronomy, University of Tennessee, Knoxville, TN 37996 (United States); Ackermann, D.; Heinz, S.; Hessberger, F. P.; Hofmann, S. [GSI Helmholtzzentrum fuer Schwerionenforschung, D-64220, Darmstadt (Germany); Grzywacz, R. [Department of Physics and Astronomy, University of Tennessee, Knoxville, TN 37996 (United States); Physics Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831 (United States); Miernik, K.; Rykaczewski, K. [Physics Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831 (United States); Tan, H. [XIA LLC, Hayward, CA 94544 (United States)

    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. Principal Component Analysis in ECG Signal Processing

    Directory of Open Access Journals (Sweden)

    Andreas Bollmann

    2007-01-01

    Full Text Available This paper reviews the current status of principal component analysis in the area of ECG signal processing. The fundamentals of PCA are briefly described and the relationship between PCA and Karhunen-Loève transform is explained. Aspects on PCA related to data with temporal and spatial correlations are considered as adaptive estimation of principal components is. Several ECG applications are reviewed where PCA techniques have been successfully employed, including data compression, ST-T segment analysis for the detection of myocardial ischemia and abnormalities in ventricular repolarization, extraction of atrial fibrillatory waves for detailed characterization of atrial fibrillation, and analysis of body surface potential maps.

  5. Three-dimensional image signals: processing methods

    Science.gov (United States)

    Schiopu, Paul; Manea, Adrian; Craciun, Anca-Ileana; Craciun, Alexandru

    2010-11-01

    Over the years extensive studies have been carried out to apply coherent optics methods in real-time processing, communications and transmission image. This is especially true when a large amount of information needs to be processed, e.g., in high-resolution imaging. The recent progress in data-processing networks and communication systems has considerably increased the capacity of information exchange. We describe the results of literature investigation research of processing methods for the signals of the three-dimensional images. All commercially available 3D technologies today are based on stereoscopic viewing. 3D technology was once the exclusive domain of skilled computer-graphics developers with high-end machines and software. The images capture from the advanced 3D digital camera can be displayed onto screen of the 3D digital viewer with/ without special glasses. For this is needed considerable processing power and memory to create and render the complex mix of colors, textures, and virtual lighting and perspective necessary to make figures appear three-dimensional. Also, using a standard digital camera and a technique called phase-shift interferometry we can capture "digital holograms." These are holograms that can be stored on computer and transmitted over conventional networks. We present some research methods to process "digital holograms" for the Internet transmission and results.

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

    Science.gov (United States)

    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. An Excel Workbook for Identifying Redox Processes in Ground Water

    Science.gov (United States)

    Jurgens, Bryant C.; McMahon, Peter B.; Chapelle, Francis H.; Eberts, Sandra M.

    2009-01-01

    The reduction/oxidation (redox) condition of ground water affects the concentration, transport, and fate of many anthropogenic and natural contaminants. The redox state of a ground-water sample is defined by the dominant type of reduction/oxidation reaction, or redox process, occurring in the sample, as inferred from water-quality data. However, because of the difficulty in defining and applying a systematic redox framework to samples from diverse hydrogeologic settings, many regional water-quality investigations do not attempt to determine the predominant redox process in ground water. Recently, McMahon and Chapelle (2008) devised a redox framework that was applied to a large number of samples from 15 principal aquifer systems in the United States to examine the effect of redox processes on water quality. This framework was expanded by Chapelle and others (in press) to use measured sulfide data to differentiate between iron(III)- and sulfate-reducing conditions. These investigations showed that a systematic approach to characterize redox conditions in ground water could be applied to datasets from diverse hydrogeologic settings using water-quality data routinely collected in regional water-quality investigations. This report describes the Microsoft Excel workbook, RedoxAssignment_McMahon&Chapelle.xls, that assigns the predominant redox process to samples using the framework created by McMahon and Chapelle (2008) and expanded by Chapelle and others (in press). Assignment of redox conditions is based on concentrations of dissolved oxygen (O2), nitrate (NO3-), manganese (Mn2+), iron (Fe2+), sulfate (SO42-), and sulfide (sum of dihydrogen sulfide [aqueous H2S], hydrogen sulfide [HS-], and sulfide [S2-]). The logical arguments for assigning the predominant redox process to each sample are performed by a program written in Microsoft Visual Basic for Applications (VBA). The program is called from buttons on the main worksheet. The number of samples that can be analyzed

  8. Design of experiments in Biomedical Signal Processing Course.

    Science.gov (United States)

    Li, Ling; Li, Bin

    2008-01-01

    Biomedical Signal Processing is one of the most important major subjects in Biomedical Engineering. The contents of Biomedical Signal Processing include the theories of digital signal processing, the knowledge of different biomedical signals, physiology and the ability of computer programming. Based on our past five years teaching experiences, in order to let students master the signal processing algorithm well, we found that the design of experiments following algorithm was very important. In this paper we presented the ideas and aims in designing the experiments. The results showed that our methods facilitated the study of abstractive signal processing algorithms and made understanding of biomedical signals in a simple way.

  9. Writer Identification Using Inexpensive Signal Processing Techniques

    CERN Document Server

    Mokhov, Serguei A; Suen, Ching Y

    2009-01-01

    We propose to use novel and classical audio and text signal-processing and otherwise techniques for "inexpensive" fast writer identification tasks of scanned hand-written documents "visually". The "inexpensive" refers to the efficiency of the identification process in terms of CPU cycles while preserving decent accuracy for preliminary identification. This is a comparative study of multiple algorithm combinations in a pattern recognition pipeline implemented in Java around an open-source Modular Audio Recognition Framework (MARF) that can do a lot more beyond audio. We present our preliminary experimental findings in such an identification task. We simulate "visual" identification by "looking" at the hand-written document as a whole rather than trying to extract fine-grained features out of it prior classification.

  10. Digital Signal Processing in the GRETINA Spectrometer

    Science.gov (United States)

    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.

  11. Parallel Processing with Digital Signal Processing Hardware and Software

    Science.gov (United States)

    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.

  12. Active voltammetric microsensors with neural signal processing.

    Energy Technology Data Exchange (ETDEWEB)

    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

  13. Statistical Signal Processing in Humanitarian Mine Clerance Systems

    DEFF Research Database (Denmark)

    Karlsen, Brian; Sørensen, Helge Bjarup Dissing; Larsen, Jan;

    2002-01-01

    Denne artikel beskriver kortfattet metoder og resultater relateret til clutterreduktion (clutter: uønskede reflekterede signaler) i jordradar- (eng. ground penetrating radar, GPR) signaler vha. statistiske signalbehandlingsmetoder baseret på Independent Component Analysis (ICA). Formålet ved denn...

  14. Random noise de-noising and direct wave eliminating based on SVD method for ground penetrating radar signals

    Science.gov (United States)

    Liu, Cai; Song, Chao; Lu, Qi

    2017-09-01

    In this paper, we present a method using singular value decomposition (SVD) which aims at eliminating the random noise and direct wave from ground penetrating radar (GPR) signals. To demonstrate the validity and high efficiency of the SVD method in eliminating random noise, we compare the SVD de-noising method with wavelet threshold de-noising method and bandpass filtering method on both noisy synthetic data and field data. After that, we compare the SVD method with the mean trace deleting in eliminating direct wave on synthetic data and field data. We set general and quantitative criteria on choosing singular values to carry out the random noise de-noising and direct wave eliminating process. We find that by choosing appropriate singular values, SVD method can eliminate the random noise and direct wave in the GPR data validly and efficiently to improve the signal-to-noise ratio (SNR) of the GPR profiles and make effective reflection signals clearer.

  15. Nonlinear biochemical signal processing via noise propagation.

    Science.gov (United States)

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

    2013-10-14

    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.

  16. Intelligent sensor networks the integration of sensor networks, signal processing and machine learning

    CERN Document Server

    Hu, Fei

    2012-01-01

    Although governments worldwide have invested significantly in intelligent sensor network research and applications, few books cover intelligent sensor networks from a machine learning and signal processing perspective. Filling this void, Intelligent Sensor Networks: The Integration of Sensor Networks, Signal Processing and Machine Learning focuses on the close integration of sensing, networking, and smart signal processing via machine learning. Based on the world-class research of award-winning authors, the book provides a firm grounding in the fundamentals of intelligent sensor networks, incl

  17. Silicon Photonics for Signal Processing of Tbit/s Serial Data Signals

    DEFF Research Database (Denmark)

    Oxenløwe, Leif Katsuo; Ji, Hua; Galili, Michael

    2012-01-01

    In this paper, we describe our recent work on signal processing of terabit per second optical serial data signals using pure silicon waveguides. We employ nonlinear optical signal processing in nanoengineered silicon waveguides to perform demultiplexing and optical waveform sampling of 1.28-Tbit....../s data signals as well as wavelength conversion of up to 320-Gbit/s data signals. We demonstrate that the silicon waveguides are equally useful for amplitude and phase-modulated data signals....

  18. Signal Processing for Improved Wireless Receiver Performance

    DEFF Research Database (Denmark)

    Christensen, Lars P.B.

    2007-01-01

    This thesis is concerned with signal processing for improving the performance of wireless communication receivers for well-established cellular networks such as the GSM/EDGE and WCDMA/HSPA systems. The goal of doing so, is to improve the end-user experience and/or provide a higher system capacity...... in connection with parameter estimation. Next, a realistic framework for interference whitening is presented, allowing flexibility in the selection of whether interference is accounted for via a discrete or a Gaussian distribution. The approximate method of sphere detection and decoding is outlined and various...... suggestions for improvements are presented. In addition, methods for using generalized BP to perform approximate joint detection and decoding in systems with convolutional codes are outlined. One such method is a natural generalization of the traditional Turbo principle and a generalized Turbo principle can...

  19. Quantum optical signal processing in diamond

    CERN Document Server

    Fisher, Kent A G; Maclean, Jean-Phillipe W; Bustard, Philip J; Resch, Kevin J; Sussman, Benjamin J

    2015-01-01

    Controlling the properties of single photons is essential for a wide array of emerging optical quantum technologies spanning quantum sensing, quantum computing, and quantum communications. Essential components for these technologies include single photon sources, quantum memories, waveguides, and detectors. The ideal spectral operating parameters (wavelength and bandwidth) of these components are rarely similar; thus, frequency conversion and spectral control are key enabling steps for component hybridization. Here we perform signal processing of single photons by coherently manipulating their spectra via a modified quantum memory. We store 723.5 nm photons, with 4.1 nm bandwidth, in a room-temperature diamond crystal; upon retrieval we demonstrate centre frequency tunability over 4.2 times the input bandwidth, and bandwidth modulation between 0.5 to 1.9 times the input bandwidth. Our results demonstrate the potential for diamond, and Raman memories in general, to be an integrated platform for photon storage ...

  20. A New Approach to Adaptive Signal Processing

    Directory of Open Access Journals (Sweden)

    Muhammad Ali Raza Anjum

    2015-04-01

    Full Text Available A unified linear algebraic approach to adaptive signal processing (ASP is presented. Starting from just Ax=b, key ASP algorithms are derived in a simple, systematic, and integrated manner without requiring any background knowledge to the field.  Algorithms covered are Steepest Descent, LMS, Normalized LMS, Kaczmarz, Affine Projection, RLS, Kalman filter, and MMSE/Least Square Wiener filters. By following this approach, readers will discover a synthesis; they will learn that one and only one equation is involved in all these algorithms. They will also learn that this one equation forms the basis of more advanced algorithms like reduced rank adaptive filters, extended Kalman filter, particle filters, multigrid methods, preconditioning methods, Krylov subspace methods and conjugate gradients. This will enable them to enter many sophisticated realms of modern research and development. Eventually, this one equation will not only become their passport to ASP but also to many highly specialized areas of computational science and engineering.

  1. Ultrasound perfusion signal processing for tumor detection

    Science.gov (United States)

    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.

  2. Mathematical SETI Statistics, Signal Processing, Space Missions

    CERN Document Server

    Maccone, Claudio

    2012-01-01

    This book introduces the Statistical Drake Equation where, from a simple product of seven positive numbers, the Drake Equation is turned into the product of seven positive random variables. The mathematical consequences of this transformation are demonstrated and it is proven that the new random variable N for the number of communicating civilizations in the Galaxy must follow the lognormal probability distribution when the number of factors in the Drake equation is allowed to increase at will. Mathematical SETI also studies the proposed FOCAL (Fast Outgoing Cyclopean Astronomical Lens) space mission to the nearest Sun Focal Sphere at 550 AU and describes its consequences for future interstellar precursor missions and truly interstellar missions. In addition the author shows how SETI signal processing may be dramatically improved by use of the Karhunen-Loève Transform (KLT) rather than Fast Fourier Transform (FFT). Finally, he describes the efforts made to persuade the United Nations to make the central part...

  3. Decreasing costs of ground data processing system development using a software product line

    Science.gov (United States)

    Chaffin, Brian

    2005-01-01

    In this paper, I describe software product lines and why a Ground Data Processing System should use one. I also describe how to develop a software product line, using examples from an imaginary Ground Data Processing System.

  4. Reduction of Static Power with Minimized Ground Bounce Noise Using Sleep Signal Slew Rate Modulation In 45nm Technology

    Directory of Open Access Journals (Sweden)

    M. Naga Pramod Reddy

    2014-06-01

    Full Text Available In MTCMOS Integrated Circuit design there exists a significant trade-off between static power consumption and technology scaling. In Modern circuits increase in power dissipation is significant due to combination of higher clock speeds, greater functional integration and smaller process geometries resulting in dominant static power consumption component. This is a big challenge for the circuit designer. However, the designers do have few methods like sleep transistor approach, sleepy stack approach to reduce this static power consumption. However all of these methods do have their own drawbacks. In order to achieve lower static power consumptions one has to sacrifice area and circuit performance metrics. In this paper we propose a new enhancement to available static power reduction techniques by modulating the sleep signal slew rate. We have designed the basic CMOS circuits in MTCMOS to achieve significant reduction in Static power consumption. For Sleep signal slew rate modulation we have proposed a modulator called triple phase sleep signal slew rate modulator. By using this Triple Phase Sleep signal modulator(TPS we can control the noise at ground distribution network (ground bounce noise produced during sleep to active state transition. By using TPS we can decrease the reactivation time to a recognizable extent, along with reduced power (static and dynamic dissipation.

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

    Science.gov (United States)

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

    2013-01-01

    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. PMID:23349292

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

    Science.gov (United States)

    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. Diversity of optical signal processing led by optical signal form conversion

    Energy Technology Data Exchange (ETDEWEB)

    Konishi, Tsuyoshi, E-mail: konishi@mls.eng.osaka-u.ac.j [Osaka University, 2-1 Yamadaoka, Suita Osaka 565-0871 (Japan)

    2010-02-01

    This paper reviews opportunities of optical signal form conversion as typified by time-space conversion in optical signal processing. Several examples of typical ultra-fast optical signal processing using optical signal form conversion are described and their applications are introduced in respect to photonic networks, ultra-fast measurement, and so on.

  8. Second International Conference on Communications, Signal Processing, and Systems

    CERN Document Server

    Mu, Jiasong; Wang, Wei; Liang, Qilian; Pi, Yiming

    2014-01-01

    The Proceedings of The Second International Conference on Communications, Signal Processing, and Systems provides the state-of-art developments of Communications, Signal Processing, and Systems. The conference covered such topics as wireless communications, networks, systems, signal processing for communications. This book is a collection of contributions coming out of The Second International Conference on Communications, Signal Processing, and Systems (CSPS) held September 2013 in Tianjin, China.

  9. Ka-band bistatic ground-based SAR using noise signals

    Science.gov (United States)

    Lukin, K.; Mogyla, A.; Vyplavin, P.; Palamarchuk, V.; Zemlyaniy, O.; Tarasenko, V.; Zaets, N.; Skretsanov, V.; Shubniy, A.; Glamazdin, V.; Natarov, M.; Nechayev, O.

    2008-01-01

    Currently, one of the actual problems is remote monitoring of technical state of large objects. Different methods can be used for that purpose. The most promising of them relies on application of ground based synthetic aperture radars (SAR) and differential interferometry. We have designed and tested Ground Based Noise Waveform SAR based on noise radar technology [1] and synthetic aperture antennas [2]. It enabled to build an instrument for precise all-weather monitoring of large objects in real-time. We describe main performance of ground-based interferometric SAR which uses continuous Ka-band noise waveform as a probe signal. Besides, results of laboratory trials and evaluation of its main performance are presented as well.

  10. IEEE International Workshop on Machine Learning for Signal Processing: Preface

    DEFF Research Database (Denmark)

    Tao, Jianhua

    The 21st IEEE International Workshop on Machine Learning for Signal Processing will be held in Beijing, China, on September 18–21, 2011. The workshop series is the major annual technical event of the IEEE Signal Processing Society's Technical Committee on Machine Learning for Signal Processing...

  11. 3rd International Conference on Communications, Signal Processing, and Systems

    CERN Document Server

    Liang, Qilian; Wang, Wei; Zhang, Baoju; Pi, Yiming

    2015-01-01

    The Proceedings of The Third International Conference on Communications, Signal Processing, and Systems provides the state-of-art developments of communications, signal processing, and systems. This book is a collection of contributions from the conference and covers such topics as wireless communications, networks, systems, and signal processing for communications. The conference was held July 2014 in Hohhot, Inner Mongolia, China.

  12. IEEE International Workshop on Machine Learning for Signal Processing: Preface

    DEFF Research Database (Denmark)

    Tao, Jianhua

    The 21st IEEE International Workshop on Machine Learning for Signal Processing will be held in Beijing, China, on September 18–21, 2011. The workshop series is the major annual technical event of the IEEE Signal Processing Society's Technical Committee on Machine Learning for Signal Processing...

  13. Assertiveness process of Iranian nurse leaders: a grounded theory study.

    Science.gov (United States)

    Mahmoudirad, Gholamhossein; Ahmadi, Fazlollah; Vanaki, Zohreh; Hajizadeh, Ebrahim

    2009-06-01

    The purpose of this study was to explore the assertiveness process in Iranian nursing leaders. A qualitative design based on the grounded theory approach was used to collect and analyze the assertiveness experiences of 12 nurse managers working in four hospitals in Iran. Purposeful and theoretical sampling methods were employed for the data collection and selection of the participants, and semistructured interviews were held. During the data analysis, 17 categories emerged and these were categorized into three themes: "task generation", "assertiveness behavior", and "executive agents". From the participants' experiences, assertiveness theory emerged as being fundamental to the development of a schematic model describing nursing leadership behaviors. From another aspect, religious beliefs also played a fundamental role in Iranian nursing leadership assertiveness. It was concluded that bringing a change in the current support from top managers and improving self-learning are required in order to enhance the assertiveness of the nursing leaders in Iran.

  14. Variations of VLF/LF signals observed on the ground and satellite during a seismic activity in Japan region in May–June 2008

    Directory of Open Access Journals (Sweden)

    A. Rozhnoi

    2010-03-01

    Full Text Available Signals of two Japanese transmitters (22.2 kHz and 40 kHz recorded on the ground VLF/LF station in Petropavlovsk-Kamchatsky and on board the DEMETER French satellite have been analyzed during a seismic activity in Japan in May–June 2008. The period of analysis was from 18 April to 27 June. During this time two rather large earthquakes occurred in the north part of Honshu Island – 7 May (M=6.8 and 13 June (M=6.9. The ground and satellite data were processed by a method based on the difference between the real signal in nighttime and the model one. For ground observations a clear decrease in both signals has been found several days before the first earthquake. For the second earthquake anomalies were detected only in JJI signal. The epicenters of earthquakes were in reliable reception zone of 40 kHz signal on board the DEMETER. Signal enhancement above the seismic active region and significant signal intensity depletion in the magnetically conjugate area has been found for satellite observation before the first earthquake. Anomalies in satellite data coincide in time with those in the ground-based observation.

  15. Sensor Signal Processing for Ultrasonic Sensors Using Delta-Sigma Modulated Single-Bit Digital Signal

    Science.gov (United States)

    Hirata, S.; Kurosawa, M. K.; Katagiri, T.

    Ultrasonic distance measurement is based on determining the time of flight of ultrasonic wave. The pulse compression technique that obtains the cross-correlation function between the received signal and the reference signal is used to improve the resolution of distance measurement. The cross-correlation method requires high-cost digital signal processing. This paper presents a cross-correlation method using a delta-sigma modulated single-bit digital signal. Sensor signal processing composed of the cross-correlation between two single-bit signals and a post-moving average filter is proposed and enables reducing the cost of digital signal processing.

  16. Neutron coincidence counting with digital signal processing

    Energy Technology Data Exchange (ETDEWEB)

    Bagi, Janos [Institute of Isotopes (IKI)-Budapest (Hungary); Dechamp, Luc; Dransart, Pascal; Dzbikowicz, Zdzislaw [European Commission, Joint Research Centre, IPSC-Ispra, VA (Italy); Dufour, Jean-Luc [Institut de Radioprotection et Surete Nucleaire-Fontenay-aux-Roses (France); Holzleitner, Ludwig [European Commission, Joint Research Centre, IPSC-Ispra (Italy); Huszti, Joseph [Institute of Isotopes (IKI)-Budapest (Hungary); Looman, Marc [Consulenze Tecniche-Cocquio Trevisago (Italy); Marin Ferrer, Montserrat [European Commission, Joint Research Centre, IPSC-Ispra (Italy); Lambert, Thierry [Institut de Radioprotection et Surete Nucleaire-Fontenay-aux-Roses (France); Peerani, Paolo [European Commission, Joint Research Centre, IPSC-Ispra (Italy)], E-mail: paolo.peerani@jrc.it; Rackham, Jamie [VT Nuclear Services-Sellafield, Seascale (United Kingdom); Swinhoe, Martyn; Tobin, Steve [N-1, Safeguards Science and Technology Group, LANL-Los Alamos, NM (United States); Weber, Anne-Laure [Institut de Radioprotection et Surete Nucleaire-Fontenay-aux-Roses (France); Wilson, Mark [VT Nuclear Services-Sellafield, Seascale (United Kingdom)

    2009-09-11

    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

  17. Ground moving target signal model and power calculation in forward scattering micro radar

    Institute of Scientific and Technical Information of China (English)

    LONG Teng; HU Cheng; MIKHAIL Cherniakov

    2009-01-01

    Forward scattering micro radar is used for situation awareness;its operational range is relatively short because of the battery power and local horizon,the free space propagation model is not appropriate.The ground moving targets,such as humans,cars and tanks,have only comparable size with the transmitted signal wavelength;the point target model and the linear change of observation angle are not applicable.In this paper,the signal model of ground moving target is developed based on the case of forward scattering micro radar,considering the two-ray propagation model and area target model,and nonlinear change of observation angle as well as high order phase error.Furthermore,the analytical form of the received power from moving target has been obtained.Using the simulated forward scattering radar cross section,the received power of theoretical calculation is near to that of measured data.In addition,the simulated signal model of ground moving target is perfectly matched with the experimented data.All these results show the correctness of analytical calculation completely.

  18. Coherent signal processing in optical coherence tomography

    Science.gov (United States)

    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

  19. Dynamic range control of audio signals by digital signal processing

    Science.gov (United States)

    Gilchrist, N. H. C.

    It is often necessary to reduce the dynamic range of musical programs, particularly those comprising orchestral and choral music, for them to be received satisfactorily by listeners to conventional FM and AM broadcasts. With the arrival of DAB (Digital Audio Broadcasting) a much wider dynamic range will become available for radio broadcasting, although some listeners may prefer to have a signal with a reduced dynamic range. This report describes a digital processor developed by the BBC to control the dynamic range of musical programs in a manner similar to that of a trained Studio Manager. It may be used prior to transmission in conventional broadcasting, replacing limiters or other compression equipment. In DAB, it offers the possibility of providing a dynamic range control signal to be sent to the receiver via an ancillary data channel, simultaneously with the uncompressed audio, giving the listener the option of the full dynamic range or a reduced dynamic range.

  20. A Hydrogen Containment Process For Nuclear Thermal Engine Ground Testing

    Science.gov (United States)

    Wang, Ten-See; Stewart, Eric; Canabal, Francisco

    2016-01-01

    A hydrogen containment process was proposed for ground testing of a nuclear thermal engine. The hydrogen exhaust from the engine is contained in two unit operations: an oxygen-rich burner and a tubular heat exchanger. The burner burns off the majority of the hydrogen, and the remaining hydrogen is removed in the tubular heat exchanger through the species recombination mechanism. A multi-dimensional, pressure-based multiphase computational fluid dynamics methodology was used to conceptually sizing the oxygen-rich burner, while a one-dimensional thermal analysis methodology was used to conceptually sizing the heat exchanger. Subsequently, a steady-state operation of the entire hydrogen containment process, from pressure vessel, through nozzle, diffuser, burner and heat exchanger, was simulated numerically, with the afore-mentioned computational fluid dynamics methodology. The computational results show that 99% of hydrogen reduction is achieved at the end of the burner, and the rest of the hydrogen is removed to a trivial level in the heat exchanger. The computed flammability at the exit of the heat exchanger is less than the lower flammability limit, confirming the hydrogen containment capability of the proposed process.

  1. Data processing and visualisation in the Rosetta Science Ground Segment

    Science.gov (United States)

    Geiger, Bernhard

    2016-09-01

    Rosetta is the first space mission to rendezvous with a comet. The spacecraft encountered its target 67P/Churyumov-Gerasimenko in 2014 and currently escorts the comet through a complete activity cycle during perihelion passage. The Rosetta Science Ground Segment (RSGS) is in charge of planning and coordinating the observations carried out by the scientific instruments on board the Rosetta spacecraft. We describe the data processing system implemented at the RSGS in order to support data analysis and science operations planning. The system automatically retrieves and processes telemetry data in near real-time. The generated products include spacecraft and instrument housekeeping parameters, scientific data for some instruments, and derived quantities. Based on spacecraft and comet trajectory information a series of geometric variables are calculated in order to assess the conditions for scheduling the observations of the scientific instruments and analyse the respective measurements obtained. Images acquired by the Rosetta Navigation Camera are processed and distributed in near real-time to the instrument team community. A quicklook web-page displaying the images allows the RSGS team to monitor the state of the comet and the correct acquisition and downlink of the images. Consolidated datasets are later delivered to the long-term archive.

  2. The Process of Patient's Privacy: A Grounded Theory

    Directory of Open Access Journals (Sweden)

    Heidari

    2011-12-01

    Full Text Available Introduction: Ethics, customs, and divine and human values in all scientific and non-academic issues are accepted among all human societies in different eras. The purpose of this study was to understand the experiences of nursing professionals about the patient's privacy. Methods: 21 participants were selected by theoretical sampling which was guided by emerging categories. All participants were interviewed individually. Subjects were interviewed in a private setting and transcription was done after each interview. In-depth interviews and semi-structured questions were used for data collection. Corbin and Strauss’ Ground theory methodology was applied in order to explain the process of patient's privacy. Data analysis was an ongoing process which was started during data collection. Data analysis method included a three-step coding process including open coding, axial and selective coding through repeated line by line reading of transcripts. Results: Four central categories were identified from transcripts' constant comparative analysis: weakness of system, actors with serious effort, trying to maintain privacy and tension creation. Conclusion: Familiarity with how nurses deal with patient’s privacy can improve professional development, client satisfaction and observation of their rights. Nurses with sensitivity to patient’s privacy can manage their expectations respectfully.

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

    Energy Technology Data Exchange (ETDEWEB)

    Xu Chi; Guo Dongming; Jin Zhuji; Kang Renke, E-mail: xuchi_dut@163.com [Key Laboratory for Precision and Non-Traditional Machining Technology of Ministry of Education, Dalian University of Technology, Dalian 116024 (China)

    2010-12-15

    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. (semiconductor technology)

  4. Development of DC-TOP Signal Processing System

    Energy Technology Data Exchange (ETDEWEB)

    Nam, Uk Won [Korea Astronomy and Space Science Institute, Daejeon (Korea, Republic of)

    2010-08-15

    The PSD panel of the DC-TOF consists of 32 PSD(Position Sensitive Detector) and its signal processing part. Each signal processing part can communicate with Data Acquisition PC with TCP/IP protocol. By such a way, total 352 PSD(l1 paneD can be used in DC-TOF. In panel, 1 DSP, 8 PML and 64 PAM are installed as signal processing part, and control neutron detecting signal from 32 PSDs

  5. A Process Model of the Signal Duration Phenomenon of Vigilance

    Science.gov (United States)

    2014-10-01

    A Process Model of the Signal Duration Phenomenon of Vigilance Daniel Gartenberg1, Bella Veksler2, Glenn Gunzelmann2, J. Gregory Trafton3...REPORT TYPE 3. DATES COVERED 00-00-2014 to 00-00-2014 4. TITLE AND SUBTITLE A Process Model of the Signal Duration Phenomenon of Vigilance 5a...with shorter signal durations (see Figure 1). There is currently no process model that explains the signal duration effect found in vigilance

  6. Clay content evaluation in soils through GPR signal processing

    Science.gov (United States)

    Tosti, Fabio; Patriarca, Claudio; Slob, Evert; Benedetto, Andrea; Lambot, Sébastien

    2013-10-01

    The mechanical behavior of soils is partly affected by their clay content, which arises some important issues in many fields of employment, such as civil and environmental engineering, geology, and agriculture. This work focuses on pavement engineering, although the method applies to other fields of interest. Clay content in bearing courses of road pavement frequently causes damages and defects (e.g., cracks, deformations, and ruts). Therefore, the road safety and operability decreases, directly affecting the increase of expected accidents. In this study, different ground-penetrating radar (GPR) methods and techniques were used to non-destructively investigate the clay content in sub-asphalt compacted soils. Experimental layout provided the use of typical road materials, employed for road bearing courses construction. Three types of soils classified by the American Association of State Highway and Transportation Officials (AASHTO) as A1, A2, and A3 were used and adequately compacted in electrically and hydraulically isolated test boxes. Percentages of bentonite clay were gradually added, ranging from 2% to 25% by weight. Analyses were carried out for each clay content using two different GPR instruments. A pulse radar with ground-coupled antennae at 500 MHz centre frequency and a vector network analyzer spanning the 1-3 GHz frequency range were used. Signals were processed in both time and frequency domains, and the consistency of results was validated by the Rayleigh scattering method, the full-waveform inversion, and the signal picking techniques. Promising results were obtained for the detection of clay content affecting the bearing capacity of sub-asphalt layers.

  7. Optimal Hamiltonian Simulation by Quantum Signal Processing

    Science.gov (United States)

    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.

  8. RNS Applications in Digital Signal Processing

    DEFF Research Database (Denmark)

    Cardarilli, Gian Carlo; Nannarelli, Alberto; Re, Marco

    2017-01-01

    In the past decades, the Residue Number System (RNS) has been adopted in DSP as an alternative to the traditional two’s complement number system (TCS) because of the high speed of the obtained architectures and the savings in area and power dissipation. However, with the shrinking of device featu......-offs, and we identify some trends for implementing DSP on ASIC and FPGA platforms.......In the past decades, the Residue Number System (RNS) has been adopted in DSP as an alternative to the traditional two’s complement number system (TCS) because of the high speed of the obtained architectures and the savings in area and power dissipation. However, with the shrinking of device...... features and the advent of powerful design tools, the advantages offered by RNS are diminishing.In this chapter, we analyze the state-of-the-art RNS implementation for a number of common Digital Signal Processing (DSP) applications, we compare performance with respect to the TCS and consider trade...

  9. Microwave photonic delay line signal processing.

    Science.gov (United States)

    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.

  10. Signal Processing Model for Radiation Transport

    Energy Technology Data Exchange (ETDEWEB)

    Chambers, D H

    2008-07-28

    This note describes the design of a simplified gamma ray transport model for use in designing a sequential Bayesian signal processor for low-count detection and classification. It uses a simple one-dimensional geometry to describe the emitting source, shield effects, and detector (see Fig. 1). At present, only Compton scattering and photoelectric absorption are implemented for the shield and the detector. Other effects may be incorporated in the future by revising the expressions for the probabilities of escape and absorption. Pair production would require a redesign of the simulator to incorporate photon correlation effects. The initial design incorporates the physical effects that were present in the previous event mode sequence simulator created by Alan Meyer. The main difference is that this simulator transports the rate distributions instead of single photons. Event mode sequences and other time-dependent photon flux sequences are assumed to be marked Poisson processes that are entirely described by their rate distributions. Individual realizations can be constructed from the rate distribution using a random Poisson point sequence generator.

  11. Software for calculations of surge processes in ground conductors and grounded objects

    Directory of Open Access Journals (Sweden)

    Kuklin D.V.

    2015-03-01

    Full Text Available Software for calculations related to propagation of electromagnetic waves in high-voltage objects (transmission towers and their grounding, substation grounding has been described in the paper. Using the software the oblique thin wire simulation method proposed by Guiffaut et al. (2012 has been verified for conductive medium

  12. Block floating-point notation for signal processes

    Energy Technology Data Exchange (ETDEWEB)

    Simpson, J.E.

    1981-03-01

    The development and application of a notation for use with block floating-point (BFP) mathematical operations in real-time signal processes is described. The notation has been extensively used in developing perimeter security signal processors such as the Magnetic Intrusion Line Sensor (MILES) Adaptive Digital Processor (MADP) and its forerunner, the Signal Processing Development Unit (SSPDU).

  13. Automatization techniques for processing biomedical signals using machine learning methods

    OpenAIRE

    Artés Rodríguez, Antonio

    2008-01-01

    The Signal Processing Group (Department of Signal Theory and Communications, University Carlos III, Madrid, Spain) offers the expertise of its members in the automatic processing of biomedical signals. The main advantages in this technology are the decreased cost, the time saved and the increased reliability of the results. Technical cooperation for the research and development with internal and external funding is sought.

  14. Knee joint vibroarthrographic signal processing and analysis

    CERN Document Server

    Wu, Yunfeng

    2015-01-01

    This book presents the cutting-edge technologies of knee joint vibroarthrographic signal analysis for the screening and detection of knee joint injuries. It describes a number of effective computer-aided methods for analysis of the nonlinear and nonstationary biomedical signals generated by complex physiological mechanics. This book also introduces several popular machine learning and pattern recognition algorithms for biomedical signal classifications. The book is well-suited for all researchers looking to better understand knee joint biomechanics and the advanced technology for vibration arthrometry. Dr. Yunfeng Wu is an Associate Professor at the School of Information Science and Technology, Xiamen University, Xiamen, Fujian, China.

  15. Wavelet Transform Signal Processing Applied to Ultrasonics.

    Science.gov (United States)

    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

  16. Electrical measurement, signal processing, and displays

    CERN Document Server

    Webster, John G

    2003-01-01

    ELECTROMAGNETIC VARIABLES MEASUREMENTVoltage MeasurementCurrent Measurement Power Measurement Power Factor Measurement Phase Measurement Energy Measurement Electrical Conductivity and Resistivity Charge Measurement Capacitance and Capacitance Measurements Permittivity Measurement Electric Field Strength Magnetic Field Measurement Permeability and Hysteresis MeasurementInductance Measurement Immittance MeasurementQ Factor Measurement Distortion Measurement Noise Measurement.Microwave Measurement SIGNAL PROCESSINGAmplifiers and Signal ConditionersModulation Filters Spectrum Analysis and Correlat

  17. An Overview of the JPSS Ground Project Algorithm Integration Process

    Science.gov (United States)

    Vicente, G. A.; Williams, R.; Dorman, T. J.; Williamson, R. C.; Shaw, F. J.; Thomas, W. M.; Hung, L.; Griffin, A.; Meade, P.; Steadley, R. S.; Cember, R. P.

    2015-12-01

    The smooth transition, implementation and operationalization of scientific software's from the National Oceanic and Atmospheric Administration (NOAA) development teams to the Join Polar Satellite System (JPSS) Ground Segment requires a variety of experiences and expertise. This task has been accomplished by a dedicated group of scientist and engineers working in close collaboration with the NOAA Satellite and Information Services (NESDIS) Center for Satellite Applications and Research (STAR) science teams for the JPSS/Suomi-NPOES Preparatory Project (S-NPP) Advanced Technology Microwave Sounder (ATMS), Cross-track Infrared Sounder (CrIS), Visible Infrared Imaging Radiometer Suite (VIIRS) and Ozone Mapping and Profiler Suite (OMPS) instruments. The presentation purpose is to describe the JPSS project process for algorithm implementation from the very early delivering stages by the science teams to the full operationalization into the Interface Processing Segment (IDPS), the processing system that provides Environmental Data Records (EDR's) to NOAA. Special focus is given to the NASA Data Products Engineering and Services (DPES) Algorithm Integration Team (AIT) functional and regression test activities. In the functional testing phase, the AIT uses one or a few specific chunks of data (granules) selected by the NOAA STAR Calibration and Validation (cal/val) Teams to demonstrate that a small change in the code performs properly and does not disrupt the rest of the algorithm chain. In the regression testing phase, the modified code is placed into to the Government Resources for Algorithm Verification, Integration, Test and Evaluation (GRAVITE) Algorithm Development Area (ADA), a simulated and smaller version of the operational IDPS. Baseline files are swapped out, not edited and the whole code package runs in one full orbit of Science Data Records (SDR's) using Calibration Look Up Tables (Cal LUT's) for the time of the orbit. The purpose of the regression test is to

  18. Neural Networks for Signal Processing and Control

    Science.gov (United States)

    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.

  19. Single Phase-to-Ground Fault Line Identification and Section Location Method for Non-Effectively Grounded Distribution Systems Based on Signal Injection

    Institute of Scientific and Technical Information of China (English)

    PAN Zhencun; WANG Chengshan; CONG Wei; ZHANG Fan

    2008-01-01

    A diagnostic signal current trace detecting based single phase-to-ground fault line identifica- tion and section location method for non-effectively grounded distribution systems is presented in thisi oaper. A special diagnostic signal current is injected into the fault distribution system, and then it is de- tected at the outlet terminals to identify the fault line and at the sectionalizing or branching point along the fault line to locate the fault section. The method has been put into application in actual distribution network and field experience shows that it can identify the fault line and locate the fault section correctly and effectively.

  20. Proceedings of IEEE Machine Learning for Signal Processing Workshop XV

    DEFF Research Database (Denmark)

    Larsen, Jan

    These proceedings contains refereed papers presented at the Fifteenth IEEE Workshop on Machine Learning for Signal Processing (MLSP’2005), held in Mystic, Connecticut, USA, September 28-30, 2005. This is a continuation of the IEEE Workshops on Neural Networks for Signal Processing (NNSP) organized...... by the NNSP Technical Committee of the IEEE Signal Processing Society. The name of the Technical Committee, hence of the Workshop, was changed to Machine Learning for Signal Processing in September 2003 to better reflect the areas represented by the Technical Committee. The conference is organized...... by the Machine Learning for Signal Processing Technical Committee with sponsorship of the IEEE Signal Processing Society. Following the practice started two years ago, the bound volume of the proceedings is going to be published by IEEE following the Workshop, and we are pleased to offer to conference attendees...

  1. Proceedings of IEEE Machine Learning for Signal Processing Workshop XV

    DEFF Research Database (Denmark)

    Larsen, Jan

    These proceedings contains refereed papers presented at the Fifteenth IEEE Workshop on Machine Learning for Signal Processing (MLSP’2005), held in Mystic, Connecticut, USA, September 28-30, 2005. This is a continuation of the IEEE Workshops on Neural Networks for Signal Processing (NNSP) organized...... by the NNSP Technical Committee of the IEEE Signal Processing Society. The name of the Technical Committee, hence of the Workshop, was changed to Machine Learning for Signal Processing in September 2003 to better reflect the areas represented by the Technical Committee. The conference is organized...... by the Machine Learning for Signal Processing Technical Committee with sponsorship of the IEEE Signal Processing Society. Following the practice started two years ago, the bound volume of the proceedings is going to be published by IEEE following the Workshop, and we are pleased to offer to conference attendees...

  2. Energy-Efficient Optical Signal Processing Using Optical Time Lenses

    DEFF Research Database (Denmark)

    Oxenløwe, Leif Katsuo; Galili, Michael; Mulvad, Hans Christian Hansen;

    2015-01-01

    This chapter describes advanced functionalities for optical signal processing using optical time lenses. A special focus is devoted to functionalities that allow for energy-savings. In particular, we find that optical signal processing, where the processing is broadband and capable of handling ma...

  3. Optical Wavelet Signals Processing and Multiplexing

    Science.gov (United States)

    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.

  4. Optimizing signal and image processing applications using Intel libraries

    Science.gov (United States)

    Landré, Jérôme; Truchetet, Frédéric

    2007-01-01

    This paper presents optimized signal and image processing libraries from Intel Corporation. Intel Performance Primitives (IPP) is a low-level signal and image processing library developed by Intel Corporation to optimize code on Intel processors. Open Computer Vision library (OpenCV) is a high-level library dedicated to computer vision tasks. This article describes the use of both libraries to build flexible and efficient signal and image processing applications.

  5. Robust Signal Processing in Living Cells

    Science.gov (United States)

    Steuer, Ralf; Waldherr, Steffen; Sourjik, Victor; Kollmann, Markus

    2011-01-01

    Cellular signaling networks have evolved an astonishing ability to function reliably and with high fidelity in uncertain environments. A crucial prerequisite for the high precision exhibited by many signaling circuits is their ability to keep the concentrations of active signaling compounds within tightly defined bounds, despite strong stochastic fluctuations in copy numbers and other detrimental influences. Based on a simple mathematical formalism, we identify topological organizing principles that facilitate such robust control of intracellular concentrations in the face of multifarious perturbations. Our framework allows us to judge whether a multiple-input-multiple-output reaction network is robust against large perturbations of network parameters and enables the predictive design of perfectly robust synthetic network architectures. Utilizing the Escherichia coli chemotaxis pathway as a hallmark example, we provide experimental evidence that our framework indeed allows us to unravel the topological organization of robust signaling. We demonstrate that the specific organization of the pathway allows the system to maintain global concentration robustness of the diffusible response regulator CheY with respect to several dominant perturbations. Our framework provides a counterpoint to the hypothesis that cellular function relies on an extensive machinery to fine-tune or control intracellular parameters. Rather, we suggest that for a large class of perturbations, there exists an appropriate topology that renders the network output invariant to the respective perturbations. PMID:22215991

  6. Ground characterization and roof mapping:Online sensor signal-based change detection

    Institute of Scientific and Technical Information of China (English)

    Bahrampour Soheil; Rostami Jamal; Ray Asok; Naeimipour Ali; Collins Craig

    2015-01-01

    Measurement while drilling systems are becoming an important part of excavation operations for rock characterization and ground support design that require reliable information on rock strength and loca-tion&frequency of joints or voids. This paper focuses on improving rock characterization algorithms for instrumented roof-bolter systems. For this purpose, an improved void detection algorithm is proposed, where the underlying theory is built upon the concept of mean change detection based on the feed pressure signals. In addition, the application of acoustic sensing for void detection is examined and it is shown that the variance of the filtered acoustic signal is correlated to the strength of the material being drilled. The proposed algorithm has been validated on the data collected from full-scale drilling tests in various concrete and rock samples at the J. H. Fletcher facility.

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

    Science.gov (United States)

    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.

  8. All-optical signal processing data communication and storage applications

    CERN Document Server

    Eggleton, Benjamin

    2015-01-01

    This book provides a comprehensive review of the state-of-the art of optical signal processing technologies and devices. It presents breakthrough solutions for enabling a pervasive use of optics in data communication and signal storage applications. It presents presents optical signal processing as solution to overcome the capacity crunch in communication networks. The book content ranges from the development of innovative materials and devices, such as graphene and slow light structures, to the use of nonlinear optics for secure quantum information processing and overcoming the classical Shannon limit on channel capacity and microwave signal processing. Although it holds the promise for a substantial speed improvement, today’s communication infrastructure optics remains largely confined to the signal transport layer, as it lags behind electronics as far as signal processing is concerned. This situation will change in the near future as the tremendous growth of data traffic requires energy efficient and ful...

  9. Low sampling frequency processing for ultra-wideband signals

    Science.gov (United States)

    Wan, Yonglun; Si, Qiang; Lu, Youxin; Wang, Hong; Wang, Xuegang

    2005-11-01

    Ultra-wideband (UWB) signals are widely used in radar, navigation and satellite communications. It is rather difficult to process UWB signals. In this paper we adopt dechirp pulse compression method to process the received UWB linear frequency modulated (LFM) signals. UWB signals are converted into signals with frequency components that are proportional to the relative range between the target and the reference target. It means to select low-speed analog-to-digital converters (ADC) for sampling UWB signals. The simulation results show that LFM signal with 600MHz center frequency, 200MHz bandwidth and 30usec pulse width can be processed under 70MHz sampling frequency by means of the method.

  10. Signal Conditioning An Introduction to Continuous Wave Communication and Signal Processing

    CERN Document Server

    Das, Apurba

    2012-01-01

    "Signal Conditioning” is a comprehensive introduction to electronic signal processing. The book presents the mathematical basics including the implications of various transformed domain representations in signal synthesis and analysis in an understandable and lucid fashion and illustrates the theory through many applications and examples from communication systems. The ease to learn is supported by well-chosen exercises which give readers the flavor of the subject. Supplementary electronic materials available on http://extras.springer.com including MATLAB codes illuminating applications in the domain of one dimensional electrical signal processing, image processing and speech processing. The book is an introduction for students with a basic understanding in engineering or natural sciences.

  11. Robust digital processing of speech signals

    CERN Document Server

    Kovacevic, Branko; Veinović, Mladen; Marković, Milan

    2017-01-01

    This book focuses on speech signal phenomena, presenting a robustification of the usual speech generation models with regard to the presumed types of excitation signals, which is equivalent to the introduction of a class of nonlinear models and the corresponding criterion functions for parameter estimation. Compared to the general class of nonlinear models, such as various neural networks, these models possess good properties of controlled complexity, the option of working in “online” mode, as well as a low information volume for efficient speech encoding and transmission. Providing comprehensive insights, the book is based on the authors’ research, which has already been published, supplemented by additional texts discussing general considerations of speech modeling, linear predictive analysis and robust parameter estimation.

  12. SIGNAL PROCESSING UTILIZING RADIO FREQUENCY PHOTONICS

    Science.gov (United States)

    2017-09-07

    OEO version above, a master laser is used to lock the phase of a slave laser. The two laser outputs are then beat at a photodiode, generating an RF...and stability are just some examples of these advantages. All of the above functions can be accomplished by photonics. An example of an RF oscillator...of LO and RF sidebands. The LO and RF sidebands will be detected at the photodiode to an IF signal. The photonic downconverter does have the advantage

  13. Signal processing for distributed readout using TESs

    Science.gov (United States)

    Smith, Stephen J.; Whitford, Chris H.; Fraser, George W.

    2006-04-01

    We describe optimal filtering algorithms for determining energy and position resolution in position-sensitive Transition Edge Sensor (TES) Distributed Read-Out Imaging Devices (DROIDs). Improved algorithms, developed using a small-signal finite-element model, are based on least-squares minimisation of the total noise power in the correlated dual TES DROID. Through numerical simulations we show that significant improvements in energy and position resolution are theoretically possible over existing methods.

  14. Signal processing for distributed readout using TESs

    Energy Technology Data Exchange (ETDEWEB)

    Smith, Stephen J. [Department of Physics and Astronomy, Space Research Centre, University of Leicester, Michael Atiyah Building, University Road, Leicester, LE1 7RH (United Kingdom)]. E-mail: sts@star.le.ac.uk; Whitford, Chris H. [Department of Physics and Astronomy, Space Research Centre, University of Leicester, Michael Atiyah Building, University Road, Leicester, LE1 7RH (United Kingdom); Fraser, George W. [Department of Physics and Astronomy, Space Research Centre, University of Leicester, Michael Atiyah Building, University Road, Leicester, LE1 7RH (United Kingdom)

    2006-04-15

    We describe optimal filtering algorithms for determining energy and position resolution in position-sensitive Transition Edge Sensor (TES) Distributed Read-Out Imaging Devices (DROIDs). Improved algorithms, developed using a small-signal finite-element model, are based on least-squares minimisation of the total noise power in the correlated dual TES DROID. Through numerical simulations we show that significant improvements in energy and position resolution are theoretically possible over existing methods.

  15. Control and signal processing by transcriptional interference

    OpenAIRE

    2009-01-01

    A transcriptional activator can suppress gene expression by interfering with transcription initiated by another activator. Transcriptional interference has been increasingly recognized as a regulatory mechanism of gene expression. The signals received by the two antagonistically acting activators are combined by the polymerase trafficking along the DNA. We have designed a dual-control genetic system in yeast to explore this antagonism systematically. Antagonism by an upstream activator bears ...

  16. Artificial intelligence applied to process signal analysis

    Science.gov (United States)

    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.

  17. Artificial intelligence applied to process signal analysis

    Science.gov (United States)

    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.

  18. Control and signal processing by transcriptional interference

    Science.gov (United States)

    Buetti-Dinh, Antoine; Ungricht, Rosemarie; Kelemen, János Z; Shetty, Chetak; Ratna, Prasuna; Becskei, Attila

    2009-01-01

    A transcriptional activator can suppress gene expression by interfering with transcription initiated by another activator. Transcriptional interference has been increasingly recognized as a regulatory mechanism of gene expression. The signals received by the two antagonistically acting activators are combined by the polymerase trafficking along the DNA. We have designed a dual-control genetic system in yeast to explore this antagonism systematically. Antagonism by an upstream activator bears the hallmarks of competitive inhibition, whereas a downstream activator inhibits gene expression non-competitively. When gene expression is induced weakly, the antagonistic activator can have a positive effect and can even trigger paradoxical activation. Equilibrium and non-equilibrium models of transcription shed light on the mechanism by which interference converts signals, and reveals that self-antagonism of activators imitates the behavior of feed-forward loops. Indeed, a synthetic circuit generates a bell-shaped response, so that the induction of expression is limited to a narrow range of the input signal. The identification of conserved regulatory principles of interference will help to predict the transcriptional response of genes in their genomic context. PMID:19690569

  19. Adaptive Genetic Algorithm for Sensor Coarse Signal Processing

    Directory of Open Access Journals (Sweden)

    Xuan Huang

    2014-03-01

    Full Text Available As with the development of computer technology and informatization, network technique, sensor technique and communication technology become three necessary components of information industry. As the core technique of sensor application, signal processing mainly determines the sensor performances. For this reason, study on signal processing mode is very important to sensors and the application of sensor network. In this paper, we introduce a new sensor coarse signal processing mode based on adaptive genetic algorithm. This algorithm selects crossover, mutation probability adaptively and compensates multiple operators commutatively to optimize the search process, so that we can obtain the global optimum solution. Based on the proposed algorithm, using auto-correlative characteristic parameter extraction method, it achieves smaller test error in sensor coarse signal processing mode of processing interference signal. We evaluate the proposed approach on a set of data. The experimental results show that, the proposed approach is able to improve the performance in different experimental setting

  20. Proceedings of the IEEE Machine Learning for Signal Processing XVII

    DEFF Research Database (Denmark)

    , and two papers from the winners of the Data Analysis Competition. The program included papers in the following areas: genomic signal processing, pattern recognition and classification, image and video processing, blind signal processing, models, learning algorithms, and applications of machine learning......The seventeenth of a series of workshops sponsored by the IEEE Signal Processing Society and organized by the Machine Learning for Signal Processing Technical Committee (MLSP-TC). The field of machine learning has matured considerably in both methodology and real-world application domains and has....... The program featured a Special Session on Genomic Signal Processing, chaired by Prof. Man-Wai Mak from Hong Kong Polytechnic University, Hong Kong. The session included four refereed papers by leading experts in the field. We also continued the tradition of the Data Analysis Competition thanks to the efforts...

  1. Fractional Order Signal Processing Introductory Concepts and Applications

    CERN Document Server

    Das, Saptarshi

    2012-01-01

    The book tries to briefly introduce the diverse literatures in the field of fractional order signal processing which is becoming an emerging topic among an interdisciplinary community of researchers. This book is aimed at postgraduate and beginning level research scholars who would like to work in the field of Fractional Order Signal processing (FOSP). The readers should have preliminary knowledge about basic signal processing techniques. Prerequisite knowledge of fractional calculus is not essential and is exposited at relevant places in connection to the appropriate signal processing topics. Basic signal processing techniques like filtering, estimation, system identification, etc. in the light of fractional order calculus are presented along with relevant application areas. The readers can easily extend these concepts to varied disciplines like image or speech processing, pattern recognition, time series forecasting, financial data analysis and modeling, traffic modeling in communication channels, optics, b...

  2. A new formulation to compute self-potential signals associated with ground water flow

    Directory of Open Access Journals (Sweden)

    A. Bolève

    2007-06-01

    Full Text Available The classical formulation of the coupled hydroelectrical flow in porous media is based on a linear formulation of two coupled constitutive equations for the electrical current density and the seepage velocity of the water phase and obeying Onsager's reciprocity. This formulation shows that the streaming current density is controlled by the gradient of the fluid pressure of the water phase and a streaming current coupling coefficient that depends on the so-called zeta potential. Recently a new formulation has been introduced in which the streaming current density is directly connected to the seepage velocity of the water phase and to the excess of electrical charge per unit pore volume in the porous material. The advantages of this formulation are numerous. First this new formulation is more intuitive not only in terms of constitutive equation for the generalized Ohm's law but also in specifying boundary conditions for the influence of the flow field upon the streaming potential. With the new formulation, the streaming potential coupling coefficient shows a decrease of its magnitude with permeability in agreement with published results. The new formulation is also easily extendable to non-viscous laminar flow problems (high Reynolds number ground water flow in cracks for example and to unsaturated conditions with applications to the vadose zone. We demonstrate here that this formulation is suitable to model self-potential signals in the field. We investigate infiltration of water from an agricultural ditch, vertical infiltration of water into a sinkhole, and preferential horizontal flow of ground water in a paleochannel. For the three cases reported in the present study, a good match is obtained between the finite element simulations performed with the finite element code Comsol Multiphysics 3.3 and field observations. Finally, this formulation seems also very promising for the inversion of the geometry of ground water flow from the

  3. Streamlining digital signal processing a tricks of the trade guidebook

    CERN Document Server

    2012-01-01

    Streamlining Digital Signal Processing, Second Edition, presents recent advances in DSP that simplify or increase the computational speed of common signal processing operations and provides practical, real-world tips and tricks not covered in conventional DSP textbooks. It offers new implementations of digital filter design, spectrum analysis, signal generation, high-speed function approximation, and various other DSP functions. It provides:Great tips, tricks of the trade, secrets, practical shortcuts, and clever engineering solutions from seasoned signal processing professionalsAn assortment.

  4. Neural Dynamics of Feedforward and Feedback Processing in Figure-Ground Segregation

    Directory of Open Access Journals (Sweden)

    Oliver W. Layton

    2014-09-01

    Full Text Available Determining whether a region belongs to the interior or exterior of a shape (figure-ground segregation is a core competency of the primate brain, yet the underlying mechanisms are not well understood. Many models assume that figure-ground segregation occurs by assembling progressively more complex representations through feedforward connections, with feedback playing only a modulatory role. We present a dynamical model of figure-ground segregation in the primate ventral stream wherein feedback plays a crucial role in disambiguating a figure’s interior and exterior. We introduce a processing strategy whereby jitter in RF center locations and variation in RF sizes is exploited to enhance and suppress neural activity inside and outside of figures, respectively. Feedforward projections emanate from units that model cells in V4 known to respond to the curvature of boundary contours (curved contour cells, and feedback projections from units predicted to exist in IT that strategically group neurons with different RF sizes and RF center locations (teardrop cells. Neurons (convex cells that preferentially respond when centered on a figure dynamically balance feedforward (bottom-up information and feedback from higher visual areas. The activation is enhanced when an interior portion of a figure is in the RF via feedback from units that detect closure in the boundary contours of a figure. Our model produces maximal activity along the medial axis of well-known figures with and without concavities, and inside algorithmically generated shapes. Our results suggest that the dynamic balancing of feedforward signals with the specific feedback mechanisms proposed by the model is crucial for figure-ground segregation.

  5. Application of Mellin Transform in Wideband Underwater Acoustic Signal Processing

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    According to the features of the wideband underwater acoustic signals, an algorithm for the wideband ambiguity function is put forward based on Mellin transform. The wideband acoustic signal processing using the fast Mellin transform is also explored. The theoretical analysis and simulation results show that the algorithm has not only high computation efficiency but also good concentration in wideband ambiguity domain. It suits for the wideband underwater acoustic signal processing.

  6. [Research progress of adventitious respiratory sound signal processing].

    Science.gov (United States)

    Li, Zhenzhen; Wu, Xiaoming

    2013-10-01

    Adventitious respiratory sound signal processing has been an important researching topic in the field of computerized respiratory sound analysis system. In recent years, new progress has been achieved in adventitious respiratory sound signal analysis due to the applications of techniques of non-stationary random signal processing. Algorithm progress of adventitious respiratory sound detections is discussed in detail in this paper. Then the state of art of adventitious respiratory sound analysis is reviewed, and development directions of next phase are pointed out.

  7. Semiconductor quantum dot amplifiers for optical signal processing

    DEFF Research Database (Denmark)

    Berg, Tommy Winther; Uskov, A. V.; Bischoff, Svend

    2001-01-01

    The dynamics of quantum dot semiconductor amplifiers are investigated theoretically with respect to the potential for ultrafast signal processing. The high-speed signal processing capacity of these devices is found to be limited by the wetting layer dynamics in case of electrical pumping, while...

  8. Signal sampling techniques for data acquisition in process control

    NARCIS (Netherlands)

    Laan, Marten Derk van der

    1995-01-01

    In computing sytems employed for data acquisition and process control, communication with the controlled processes is mainly taking place via analog signal lines. In this situation, the quality of data acquired by A/D-converters and the generation of analog control signals by D/A-converters is of

  9. Semiconductor quantum dot amplifiers for optical signal processing

    DEFF Research Database (Denmark)

    Berg, Tommy Winther; Uskov, A. V.; Bischoff, Svend

    2001-01-01

    The dynamics of quantum dot semiconductor amplifiers are investigated theoretically with respect to the potential for ultrafast signal processing. The high-speed signal processing capacity of these devices is found to be limited by the wetting layer dynamics in case of electrical pumping, while...

  10. Signal sampling techniques for data acquisition in process control

    OpenAIRE

    Laan, Marten Derk van der

    1995-01-01

    In computing sytems employed for data acquisition and process control, communication with the controlled processes is mainly taking place via analog signal lines. In this situation, the quality of data acquired by A/D-converters and the generation of analog control signals by D/A-converters is of major importance for the overall performance of a system. ... Zie: Summary

  11. Signal sampling techniques for data acquisition in process control

    NARCIS (Netherlands)

    Laan, Marten Derk van der

    1995-01-01

    In computing sytems employed for data acquisition and process control, communication with the controlled processes is mainly taking place via analog signal lines. In this situation, the quality of data acquired by A/D-converters and the generation of analog control signals by D/A-converters is of ma

  12. Proceedings of the IEEE Machine Learning for Signal Processing XVII

    DEFF Research Database (Denmark)

    The seventeenth of a series of workshops sponsored by the IEEE Signal Processing Society and organized by the Machine Learning for Signal Processing Technical Committee (MLSP-TC). The field of machine learning has matured considerably in both methodology and real-world application domains and has...

  13. Quaternion Fourier transforms for signal and image processing

    CERN Document Server

    Ell, Todd A; Sangwine, Stephen J

    2014-01-01

    Based on updates to signal and image processing technology made in the last two decades, this text examines the most recent research results pertaining to Quaternion Fourier Transforms. QFT is a central component of processing color images and complex valued signals. The book's attention to mathematical concepts, imaging applications, and Matlab compatibility render it an irreplaceable resource for students, scientists, researchers, and engineers.

  14. Signal processing for on-chip space division multiplexing

    DEFF Research Database (Denmark)

    Peucheret, Christophe; Ding, Yunhong; Xu, Jing;

    2015-01-01

    Our recent results on the demonstration of on-chip mode-division multiplexing are reviewed, with special emphasis on nonlinear all-optical signal processing. Mode-selective parametric processes are demonstrated in a silicon-on-insulator waveguide.......Our recent results on the demonstration of on-chip mode-division multiplexing are reviewed, with special emphasis on nonlinear all-optical signal processing. Mode-selective parametric processes are demonstrated in a silicon-on-insulator waveguide....

  15. Innovative signal processing for Johnson Noise thermometry

    Energy Technology Data Exchange (ETDEWEB)

    Ezell, N. Dianne Bull [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Britton, Jr, Charles L. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Roberts, Michael [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

    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.

  16. Signal Processing in Large Systems: a New Paradigm

    CERN Document Server

    Couillet, Romain

    2011-01-01

    For a long time, signal processing applications, and most particularly detection and parameter estimation methods, have relied on the limiting behaviour of test statistics and estimators, as the number n of observations of a population grows large comparatively to the population size N, i.e. n>>N. Modern technological and societal advances now demand the study of sometimes extremely large populations, while simultaneously requiring fast signal processing due to accelerated system dynamics; this results in not-so-large practical ratios n/N, sometimes even smaller than one. A disruptive change in classical signal processing methods has therefore been initiated in the past ten years, mostly spurred by the field of large dimensional random matrix theory. The early literature in random matrix theory for signal processing applications is however scarce and highly technical. This tutorial proposes an accessible methodological introduction to the modern tools of random matrix theory and to the signal processing metho...

  17. Signal Processing and Electronic Noise in LZ

    CERN Document Server

    Khaitan, Dev Ashish

    2015-01-01

    The electronics of the LUX-ZEPLIN (LZ) experiment, the 10-tonne dark matter detector to be installed at the Sanford Underground Research Facility (SURF), consists of low-noise dual-gain amplifiers and a 100-MHz, 14-bit data acquisition system for the TPC PMTs. Pre-prototypes of the analog amplifiers and the 32-channel digitizers were tested extensively with simulated pulses that are similar to the prompt scintillation light and the electroluminescence signals expected in LZ. These studies are used to characterize the noise and to measure the linearity of the system. By increasing the amplitude of the test signals, the effect of saturating the amplifier and the digitizers was studied. The RMS ADC noise of the digitizer channels was measured to be 1.19 $\\pm$ 0.01 ADCC. When a high-energy channel of the amplifier is connected to the digitizer, the measured noise remained virtually unchanged, while the noise added by a low-energy channel was estimated to be 0.38 $\\pm$ 0.02 ADCC (46 $\\pm$ 2$\\mu$V). A test facility...

  18. Signal processing and electronic noise in LZ

    Science.gov (United States)

    Khaitan, D.

    2016-03-01

    The electronics of the LUX-ZEPLIN (LZ) experiment, the 10-tonne dark matter detector to be installed at the Sanford Underground Research Facility (SURF), consists of low-noise dual-gain amplifiers and a 100-MHz, 14-bit data acquisition system for the TPC PMTs. Pre-prototypes of the analog amplifiers and the 32-channel digitizers were tested extensively with simulated pulses that are similar to the prompt scintillation light and the electroluminescence signals expected in LZ. These studies are used to characterize the noise and to measure the linearity of the system. By increasing the amplitude of the test signals, the effect of saturating the amplifier and the digitizers was studied. The RMS ADC noise of the digitizer channels was measured to be 1.19± 0.01 ADCC. When a high-energy channel of the amplifier is connected to the digitizer, the measured noise remained virtually unchanged, while the noise added by a low-energy channel was estimated to be 0.38 ± 0.02 ADCC (46 ± 2 μV). A test facility is under construction to study saturation, mitigate noise and measure the performance of the LZ electronics and data acquisition chain.

  19. Is complex signal processing for bone conduction hearing aids useful?

    Science.gov (United States)

    Kompis, Martin; Kurz, Anja; Pfiffner, Flurin; Senn, Pascal; Arnold, Andreas; Caversaccio, Marco

    2014-05-01

    To establish whether complex signal processing is beneficial for users of bone anchored hearing aids. Review and analysis of two studies from our own group, each comparing a speech processor with basic digital signal processing (either Baha Divino or Baha Intenso) and a processor with complex digital signal processing (either Baha BP100 or Baha BP110 power). The main differences between basic and complex signal processing are the number of audiologist accessible frequency channels and the availability and complexity of the directional multi-microphone noise reduction and loudness compression systems. Both studies show a small, statistically non-significant improvement of speech understanding in quiet with the complex digital signal processing. The average improvement for speech in noise is +0.9 dB, if speech and noise are emitted both from the front of the listener. If noise is emitted from the rear and speech from the front of the listener, the advantage of the devices with complex digital signal processing as opposed to those with basic signal processing increases, on average, to +3.2 dB (range +2.3 … +5.1 dB, p ≤ 0.0032). Complex digital signal processing does indeed improve speech understanding, especially in noise coming from the rear. This finding has been supported by another study, which has been published recently by a different research group. When compared to basic digital signal processing, complex digital signal processing can increase speech understanding of users of bone anchored hearing aids. The benefit is most significant for speech understanding in noise.

  20. The signal selection and processing method for polarization measurement radar

    Institute of Scientific and Technical Information of China (English)

    CHANG YuLiang; WANG XueSong; LI YongZhen; XIAO ShunPing

    2009-01-01

    Based on the ambiguity function, a novel signal processing method for the polarization measurement radar is developed. One advantage of this method is that the two orthogonal polarized signals do not have to be perpendicular to each other, which is required by traditional methods. The error due to the correlation of the two transmitting signals in the traditional method, can be reduced by this new approach. A concept called ambiguity function matrix (AFM) is introduced based on this method. AFM is a promising tool for the signal selection and design in the polarization scattering matrix measurement. The waveforms of the polarimetric radar are categorized and analyzed based on AFM in this paper. The signal processing flow of this method is explained. And the polarization scattering matrix measurement performance is testified by simulation. Furthermore, this signal processing method can be used in the inter-pulse interval measurement technique as well as in the instantaneous measurement technique.

  1. Earthquake early warning system using real-time signal processing

    Energy Technology Data Exchange (ETDEWEB)

    Leach, R.R. Jr.; Dowla, F.U.

    1996-02-01

    An earthquake warning system has been developed to provide a time series profile from which vital parameters such as the time until strong shaking begins, the intensity of the shaking, and the duration of the shaking, can be derived. Interaction of different types of ground motion and changes in the elastic properties of geological media throughout the propagation path result in a highly nonlinear function. We use neural networks to model these nonlinearities and develop learning techniques for the analysis of temporal precursors occurring in the emerging earthquake seismic signal. The warning system is designed to analyze the first-arrival from the three components of an earthquake signal and instantaneously provide a profile of impending ground motion, in as little as 0.3 sec after first ground motion is felt at the sensors. For each new data sample, at a rate of 25 samples per second, the complete profile of the earthquake is updated. The profile consists of a magnitude-related estimate as well as an estimate of the envelope of the complete earthquake signal. The envelope provides estimates of damage parameters, such as time until peak ground acceleration (PGA) and duration. The neural network based system is trained using seismogram data from more than 400 earthquakes recorded in southern California. The system has been implemented in hardware using silicon accelerometers and a standard microprocessor. The proposed warning units can be used for site-specific applications, distributed networks, or to enhance existing distributed networks. By producing accurate, and informative warnings, the system has the potential to significantly minimize the hazards of catastrophic ground motion. Detailed system design and performance issues, including error measurement in a simple warning scenario are discussed in detail.

  2. Quantum Dot Devices for Optical Signal Processing

    DEFF Research Database (Denmark)

    Chen, Yaohui

    . Additional to the static linear amplication properties, we focus on exploring the gain dynamics on the time scale ranging from sub-picosecond to nanosecond. In terms of optical signals that have been investigated, one is the simple sinusoidally modulated optical carrier with a typical modulation frequency...... range of 1-100 gigahertz. Our simulations reveal the role of ultrafast intradot carrier dynamics in enhancing modulation bandwidth of quantum dot semiconductor optical ampliers. Moreover, the corresponding coherent gain response also provides rich dispersion contents over a broad bandwidth. One...... important implementation is recently boosted by the research in slow light. The idea is to migrate such dynamical gain knowledge for the investigation of microwave phase shifter based on semiconductor optical waveguide. Our study reveals that phase shifting based on the conventional semiconductor optical...

  3. Time reversal signal processing for communication.

    Energy Technology Data Exchange (ETDEWEB)

    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.

  4. Neuromorphic opto-electronic integrated circuits for optical signal processing

    Science.gov (United States)

    Romeira, B.; Javaloyes, J.; Balle, S.; Piro, O.; Avó, R.; Figueiredo, J. M. L.

    2014-08-01

    The ability to produce narrow optical pulses has been extensively investigated in laser systems with promising applications in photonics such as clock recovery, pulse reshaping, and recently in photonics artificial neural networks using spiking signal processing. Here, we investigate a neuromorphic opto-electronic integrated circuit (NOEIC) comprising a semiconductor laser driven by a resonant tunneling diode (RTD) photo-detector operating at telecommunication (1550 nm) wavelengths capable of excitable spiking signal generation in response to optical and electrical control signals. The RTD-NOEIC mimics biologically inspired neuronal phenomena and possesses high-speed response and potential for monolithic integration for optical signal processing applications.

  5. Signal Acquisition and Processing Method Using Sector SSPA

    Institute of Scientific and Technical Information of China (English)

    WU Kai-hua; HUANG Zuo-hua; YAN Kuang

    2005-01-01

    Self scanning photodiode array (SSPA) is a kind of solid state imaging sensor. The signal processing method using a special sector SSPA was investigated. Based on the principle and characteristics of SSPA, a signal acquisition and processing method controlled by computer was introduced. The amplification of weak signal, the matching of time sequence, the fast peak holding with low leakage, the high speed A/D conversion and nonlinear correction were discussed. This method can acquire the peak signal of every ring of sector SSPA with high accuracy and in real time. It can be used to detect the distribution of space light energy.

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

    Energy Technology Data Exchange (ETDEWEB)

    Clairet, F.; Bottereau, C. [CEA, IRFM, F-13108 Saint-Paul-lez-Durance (France); Ricaud, B. [CEA, IRFM, F-13108 Saint-Paul-lez-Durance (France); CPT UMR 6207, Campus de Luminy, case 907, F-13288 Marseille (France); Briolle, F. [CPT UMR 6207, Campus de Luminy, case 907, F-13288 Marseille (France); CReA, BA 701, F-13306 Salon de Provence (France); Heuraux, S. [IJL-P2M, UMR-CNRS 7198, Universite Henri Poincare, F-54506 Vandoeuvre (France)

    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. Introduction to ground penetrating radar inverse scattering and data processing

    CERN Document Server

    Persico, Raffaele

    2014-01-01

    This book presents a comprehensive treatment of ground penetrating radar using both forward and inverse scattering mathematical techniques. Use of field data instead of laboratory data enables readers to envision real-life underground imaging; a full color insert further clarifies understanding. Along with considering the practical problem of achieving interpretable underground images, this book also features significant coverage of the problem's mathematical background. This twofold approach provides a resource that will appeal both to application oriented geologists and testing specialists,

  8. Versatile architectures for onboard payload signal processing

    NARCIS (Netherlands)

    Walters, Karel Hubertus Gerardus

    2013-01-01

    This thesis presents a hardware fused-multiply-add floating point unit, called Sabrewing, which has properties that satisfy the needs for payload processing units. Sabrewing is BSD licensed and made in Europe such that it bypasses the export regulations of the USA. It combines floating-point and fix

  9. SAR Systems and Related Signal Processing

    NARCIS (Netherlands)

    Hoogeboom, P.; Dekker, R.J.; Otten, M.P.G.

    1996-01-01

    Synthetic Aperture Radar (SAR) is today a valuable source of remote sensing information. SAR is a side-looking imaging radar and operates from airborne and spacebome platforms. Coverage, resolution and image quality are strongly influenced by the platform. SAR processing can be performed on standard

  10. SAR Systems and Related Signal Processing

    NARCIS (Netherlands)

    Hoogeboom, P.; Dekker, R.J.; Otten, M.P.G.

    1996-01-01

    Synthetic Aperture Radar (SAR) is today a valuable source of remote sensing information. SAR is a side-looking imaging radar and operates from airborne and spacebome platforms. Coverage, resolution and image quality are strongly influenced by the platform. SAR processing can be performed on standard

  11. All-optical signal processing of OTDM and OFDM signals based on time-domain Optical Fourier Transformation

    DEFF Research Database (Denmark)

    Clausen, Anders; Guan, Pengyu; Mulvad, Hans Christian Hansen

    2014-01-01

    All-optical time-domain Optical Fourier Transformation utilised for signal processing of ultra-high-speed OTDM signals and OFDM signals will be presented.......All-optical time-domain Optical Fourier Transformation utilised for signal processing of ultra-high-speed OTDM signals and OFDM signals will be presented....

  12. Human Walking Pattern Recognition Based on KPCA and SVM with Ground Reflex Pressure Signal

    Directory of Open Access Journals (Sweden)

    Zhaoqin Peng

    2013-01-01

    Full Text Available Algorithms based on the ground reflex pressure (GRF signal obtained from a pair of sensing shoes for human walking pattern recognition were investigated. The dimensionality reduction algorithms based on principal component analysis (PCA and kernel principal component analysis (KPCA for walking pattern data compression were studied in order to obtain higher recognition speed. Classifiers based on support vector machine (SVM, SVM-PCA, and SVM-KPCA were designed, and the classification performances of these three kinds of algorithms were compared using data collected from a person who was wearing the sensing shoes. Experimental results showed that the algorithm fusing SVM and KPCA had better recognition performance than the other two methods. Experimental outcomes also confirmed that the sensing shoes developed in this paper can be employed for automatically recognizing human walking pattern in unlimited environments which demonstrated the potential application in the control of exoskeleton robots.

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

    Science.gov (United States)

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

    2012-01-01

    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.

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

    Science.gov (United States)

    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.

  15. Signal processing for mobile communications handbook

    CERN Document Server

    Ibnkahla, Mohamed

    2004-01-01

    INTRODUCTIONSignal Processing for Future Mobile Communications Systems: Challenges and Perspectives; Quazi Mehbubar Rahman and Mohamed IbnkahlaCHANNEL MODELING AND ESTIMATIONMultipath Propagation Models for Broadband Wireless Systems; Andreas F. Molisch and Fredrik TufvessonModeling and Estimation of Mobile Channels; Jitendra K. TugnaitMobile Satellite Channels: Statistical Models and Performance Analysis; Giovanni E. Corazza, Alessandro Vanelli-Coralli, Raffaella Pedone, and Massimo NeriMobile Velocity Estimation for Wireless Communications; Bouchra Senadji, Ghazem Azemi, and Boualem Boashash

  16. Grating geophone signal processing based on wavelet transform

    Science.gov (United States)

    Li, Shuqing; Zhang, Huan; Tao, Zhifei

    2008-12-01

    Grating digital geophone is designed based on grating measurement technique benefiting averaging-error effect and wide dynamic range to improve weak signal detected precision. This paper introduced the principle of grating digital geophone and its post signal processing system. The signal acquisition circuit use Atmega 32 chip as core part and display the waveform on the Labwindows through the RS232 data link. Wavelet transform is adopted this paper to filter the grating digital geophone' output signal since the signal is unstable. This data processing method is compared with the FIR filter that widespread use in current domestic. The result indicates that the wavelet algorithm has more advantages and the SNR of seismic signal improve obviously.

  17. Assess Sleep Stage by Modern Signal Processing Techniques

    CERN Document Server

    Wu, Hau-tieng; Lo, Yu-Lun

    2014-01-01

    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 s...

  18. Fundamentals of Signal Processing for Sound and Vibration Engineers

    CERN Document Server

    Shin, Kihong

    2008-01-01

    Fundamentals of Signal Processing for Sound and Vibration Engineers is based on Joe Hammond's many years of teaching experience at the Institute of Sound and Vibration Research, University of Southampton. Whilst the applications presented emphasise sound and vibration, the book focusses on the basic essentials of signal processing that ensures its appeal as a reference text to students and practitioners in all areas of mechanical, automotive, aerospace and civil engineering.  Offers an excellent introduction to signal processing for students and professionals in th

  19. High-speed signal processing using highly nonlinear optical fibres

    DEFF Research Database (Denmark)

    Peucheret, Christophe; Oxenløwe, Leif Katsuo; Mulvad, Hans Christian Hansen

    2009-01-01

    relying on the phase of the optical field. Topics covered include all-optical switching of 640 Gbit/s and 1.28 Tbit/s serial data, wavelength conversion at 640 Gbit/s, optical amplitude regeneration of differential phase shift keying (DPSK) signals, as well as midspan spectral inversion for differential 8......We review recent progress in all-optical signal processing techniques making use of conventional silica-based highly nonlinear fibres. In particular, we focus on recent demonstrations of ultra-fast processing at 640 Gbit/s and above, as well as on signal processing of novel modulation formats...

  20. Discrete random signal processing and filtering primer with Matlab

    CERN Document Server

    Poularikas, Alexander D

    2013-01-01

    Engineers in all fields will appreciate a practical guide that combines several new effective MATLAB® problem-solving approaches and the very latest in discrete random signal processing and filtering.Numerous Useful Examples, Problems, and Solutions - An Extensive and Powerful ReviewWritten for practicing engineers seeking to strengthen their practical grasp of random signal processing, Discrete Random Signal Processing and Filtering Primer with MATLAB provides the opportunity to doubly enhance their skills. The author, a leading expert in the field of electrical and computer engineering, offe

  1. Proceedings of IEEE Machine Learning for Signal Processing Workshop XVI

    DEFF Research Database (Denmark)

    Larsen, Jan

    These proceedings contains refereed papers presented at the sixteenth IEEE Workshop on Machine Learning for Signal Processing (MLSP'2006), held in Maynooth, Co. Kildare, Ireland, September 6-8, 2006. This is a continuation of the IEEE Workshops on Neural Networks for Signal Processing (NNSP...... with sponsorship of the IEEE Signal Processing Society. Following the practice started three years ago, the bound volume of the proceedings is going to be published by IEEE following the Workshop, and we are pleased to offer to conference attendees the proceeding in a CDROM electronic format, which maintains...

  2. Proceedings of IEEE Machine Learning for Signal Processing Workshop XVI

    DEFF Research Database (Denmark)

    Larsen, Jan

    These proceedings contains refereed papers presented at the sixteenth IEEE Workshop on Machine Learning for Signal Processing (MLSP'2006), held in Maynooth, Co. Kildare, Ireland, September 6-8, 2006. This is a continuation of the IEEE Workshops on Neural Networks for Signal Processing (NNSP...... with sponsorship of the IEEE Signal Processing Society. Following the practice started three years ago, the bound volume of the proceedings is going to be published by IEEE following the Workshop, and we are pleased to offer to conference attendees the proceeding in a CDROM electronic format, which maintains...

  3. Features of Channel and Signal Processing of Fuze

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    This paper simply discusses the outer channels and their characteristics of information communication between the fuze and outer environments based on the view that the fuze is an information system,and deeply analyzes the information features of high frequency signal processing that mainly recovers the echo signals and controls the noises instead of picking up the required btarget information.But it can reduce the uncertainty of the signal caused by noise.The information processing of fuze is mainly completed by the low frequency information processing system.

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

    Science.gov (United States)

    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.

  5. Radar Array Signal Processing in the Presence of Scattering Effects

    Science.gov (United States)

    2008-01-15

    Final INov . 2004 - Oct. 2007 4. TITLE AND SUBTITLE Sa. CON RACT NUMBER Radar Array Signal Processing in the Presence of Scattering Effects N/A 5b. GRANT...polarization. Hence, we considered models depicting how the features of this signal are affected by the medium materials through which the signal propagates. We...security (e.g., for nuclear materials ), and particle communications. We assume Poisson distribution for each detectors measurement within the

  6. A system for pulsed NQR spectrometer control and signal processing

    Science.gov (United States)

    Gourdji, M.; Péneau, A.

    The system described was built at the IEF around a HP-21OOA computer and is presently used with a nitrogen-14 pulsed NQR spectrometer. Two main functions are provided: spectrometer control (radio-frequency, pulse sequence repetition rate, sample temperature settings) and signal processing (accumulation of the NQR signals, Fourier transform). Results are presented which show typical uses of the system for the observation of complex signals.

  7. Processing of physiological signals in automotive research.

    Science.gov (United States)

    Dambier, Michael; Altmüller, Tobias; Ladstätter, Ulrich

    2006-12-01

    The development of innovative driver assistance systems requires the evaluation of the predisposed hypotheses such as acceptance and driving safety. For this purpose, the conduction of experiments with end-users as subjects is necessary. Analysis and evaluation are based on the recording of numerous sensor values and system variables. Video, gaze and physiological data are recorded for the analysis of gaze distraction and emotional reactions of subjects to system behaviour. In this paper, a modular data streaming and processing architecture is suggested and a concept for this architecture is defined for consistent data evaluation, which integrates off-the-shelf products for data analysis and evaluation.

  8. Signal processing method of a novel polarized array radar seeker

    Institute of Scientific and Technical Information of China (English)

    Lizhong Song; Xiaolin Qiao

    2013-01-01

    This paper proposes a novel polarized radar seeker based on the polarized antenna array. A ful y polarized signal processing method for the proposed radar seeker is studied un-der the environments with electromagnetic interferences. A dual polarized antenna array is employed to transmit and receive the radar signals. The instantaneous polarization signal processing technique is used to detect and recognize the targets. The di-rection of arrival (DOA) of the target is measured through the spatial spectrum with high resolution for the polarized array radar seeker system. The ful y polarized signal model of the polarized array radar seeker is formulated and a specific signal processing algorithm is expounded. The theoretical research and numerical simulation results demonstrate that the proposed radar seeker has good performances in target detection and electronic warfare. The research results can provide an effective technical approach to develop and research the new generation radar seeker.

  9. Modeling laser velocimeter signals as triply stochastic Poisson processes

    Science.gov (United States)

    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.

  10. DESIGN AND IMPLEMENTATION OF FPGA BASED SIGNAL PROCESSING CARD

    Directory of Open Access Journals (Sweden)

    Priya Gupta

    2011-09-01

    Full Text Available This paper describes the design of FPGA based signal processing card. An on board real time digital signal processing system is designed using FPGA. The platform can decode process of various kinds of digital and analog signals simultaneously. The design trend in this card is towards small size, high integration and fast real time processing. For the optimum performance a 16 bit 1 MSPS ADC is used which is interfaced with FPGA to make all the data processing on board in real time. This card can be used in many signal processing based applications like audio signal processing, audio compression, digital image processing, video compression, speech processing, speech recognition, digital communications by interfacing several separate board using inbuilt I/O’s, each with a number of input channels that will communicate with each other in real time over a high speed communication link. The resulting images can be displayed directly on LCD or OLED panel displays using I/O’s peripherals. The project introduces many challenging issues, which are being addressed in turn with different prototype designs. These issues are the ADC performance, interfacing the ADCs to the FPGA, implementing the flexible processing algorithms and high speed interconnection between the boards.

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

    Science.gov (United States)

    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.

  12. Recent Advances in Ultra-High-Speed Optical Signal Processing

    DEFF Research Database (Denmark)

    Mulvad, Hans Christian Hansen; Palushani, Evarist; Hu, Hao;

    2012-01-01

    We review recent advances in the optical signal processing of ultra-high-speed serial data signals up to 1.28 Tbit/s, with focus on applications of time-domain optical Fourier transformation. Experimental methods for the generation of symbol rates up to 1.28 Tbaud are also described....

  13. Ultra-Fast Optical Signal Processing in Nonlinear Silicon Waveguides

    DEFF Research Database (Denmark)

    Oxenløwe, Leif Katsuo; Galili, Michael; Pu, Minhao;

    2011-01-01

    We describe recent demonstrations of exploiting highly nonlinear silicon nanowires for processing Tbit/s optical data signals. We perform demultiplexing and optical waveform sampling of 1.28 Tbit/s and wavelength conversion of 640 Gbit/s data signals....

  14. Software for biomedical engineering signal processing laboratory experiments.

    Science.gov (United States)

    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.

  15. Signal processing techniques for synchronization of wireless sensor networks

    Science.gov (United States)

    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.

  16. Recent Advancements in Semiconductor-based Optical Signal Processing

    DEFF Research Database (Denmark)

    Nielsen, M L; Mørk, Jesper

    2006-01-01

    Significant advancements in technology and basic understanding of device physics are bringing optical signal processing closer to a commercial breakthrough. In this paper we describe the main challenges in high-speed SOA-based switching....

  17. Digital signal processing in power electronics control circuits

    CERN Document Server

    Sozański, Krzysztof

    2017-01-01

    This book discusses problems concerning the design and realization of digital control algorithms for power electronics circuits using digital signal processing (DSP) methods. It includes Matlab examples for illustration of considered problems.

  18. An algorithm for signal processing in multibeam antenna arrays

    Science.gov (United States)

    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.

  19. Array signal processing in the NASA Deep Space Network

    Science.gov (United States)

    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.

  20. Optical signal processing using electro-absorption modulators

    DEFF Research Database (Denmark)

    Mørk, Jesper; Romstad, Francis Pascal; Højfeldt, Sune

    2003-01-01

    Reverse-biased semiconductor waveguides are efficient saturable absorbers and have a number of promising all-optical signal processing applications. Results on ultrafast modulator dynamics as well as demonstrations and investigations of wavelength conversion and regeneration are presented....

  1. Linear signal processing using silicon micro-ring resonators

    DEFF Research Database (Denmark)

    Peucheret, Christophe; Ding, Yunhong; Ou, Haiyan;

    2012-01-01

    We review our recent achievements on the use of silicon micro-ring resonators for linear optical signal processing applications, including modulation format conversion, phase-to-intensity modulation conversion and waveform shaping....

  2. Mathematical summary for digital signal processing applications with Matlab

    CERN Document Server

    Gopi, E S

    2010-01-01

    Mathematical Summary for Digital Signal Processing Applications with Matlab consists of Mathematics which is not usually dealt with in the DSP core subject, but used in DSP applications. It gives Matlab programs with illustrations.

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

    Science.gov (United States)

    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.

  4. Analogue Signal Processing: Collected Papers 1994-95

    DEFF Research Database (Denmark)

    1996-01-01

    This document is a collection of the papers presented at international conferences and in international journals by the analogue signal processing group of Electronics Institute, Technical University of Denmark, in 1994 and 1995.......This document is a collection of the papers presented at international conferences and in international journals by the analogue signal processing group of Electronics Institute, Technical University of Denmark, in 1994 and 1995....

  5. Analogue Signal Processing: Collected Papers 1996-97

    DEFF Research Database (Denmark)

    1997-01-01

    This document is a collection of the papers presented at international conferences and in international journals by the analogue signal processing group of the Department of Information Technology, Technical University of Denmark, in 1996 and 1997.......This document is a collection of the papers presented at international conferences and in international journals by the analogue signal processing group of the Department of Information Technology, Technical University of Denmark, in 1996 and 1997....

  6. Advanced Statistical Signal Processing Techniques for Landmine Detection Using GPR

    Science.gov (United States)

    2014-07-12

    Processing Techniques for Landmine Detection Using GPR The views, opinions and/or findings contained in this report are those of the author(s) and should not...AGENCY NAME(S) AND ADDRESS (ES) U.S. Army Research Office P.O. Box 12211 Research Triangle Park, NC 27709-2211 landmine Detection, Signal...310 Jesse Hall Columbia, MO 65211 -1230 654808 633606 ABSTRACT Advanced Statistical Signal Processing Techniques for Landmine Detection Using GPR Report

  7. Analogue Signal Processing: Collected Papers 1994-95

    DEFF Research Database (Denmark)

    1996-01-01

    This document is a collection of the papers presented at international conferences and in international journals by the analogue signal processing group of Electronics Institute, Technical University of Denmark, in 1994 and 1995.......This document is a collection of the papers presented at international conferences and in international journals by the analogue signal processing group of Electronics Institute, Technical University of Denmark, in 1994 and 1995....

  8. Linear signal processing using silicon micro-ring resonators

    DEFF Research Database (Denmark)

    Peucheret, Christophe; Ding, Yunhong; Ou, Haiyan

    2012-01-01

    We review our recent achievements on the use of silicon micro-ring resonators for linear optical signal processing applications, including modulation format conversion, phase-to-intensity modulation conversion and waveform shaping.......We review our recent achievements on the use of silicon micro-ring resonators for linear optical signal processing applications, including modulation format conversion, phase-to-intensity modulation conversion and waveform shaping....

  9. Ultrafast optical signal processing using semiconductor quantum dot amplifiers

    DEFF Research Database (Denmark)

    Berg, Tommy Winther; Mørk, Jesper

    2002-01-01

    The linear and nonlinear properties of quantum dot amplifiers are discussed on the basis of an extensive theoretical model. These devices show great potential for linear amplification as well as ultrafast signal processing.......The linear and nonlinear properties of quantum dot amplifiers are discussed on the basis of an extensive theoretical model. These devices show great potential for linear amplification as well as ultrafast signal processing....

  10. High-speed optical signal processing using time lenses

    DEFF Research Database (Denmark)

    Galili, Michael; Hu, Hao; Guan, Pengyu;

    2015-01-01

    This paper will discuss time lenses and their broad range of applications. A number of recent demonstrations of complex high-speed optical signal processing using time lenses will be outlined with focus on the operating principle.......This paper will discuss time lenses and their broad range of applications. A number of recent demonstrations of complex high-speed optical signal processing using time lenses will be outlined with focus on the operating principle....

  11. All-optical signal processing using dynamic Brillouin gratings

    Science.gov (United States)

    Santagiustina, Marco; Chin, Sanghoon; Primerov, Nicolay; Ursini, Leonora; Thévenaz, Luc

    2013-01-01

    The manipulation of dynamic Brillouin gratings in optical fibers is demonstrated to be an extremely flexible technique to achieve, with a single experimental setup, several all-optical signal processing functions. In particular, all-optical time differentiation, time integration and true time reversal are theoretically predicted, and then numerically and experimentally demonstrated. The technique can be exploited to process both photonic and ultra-wide band microwave signals, so enabling many applications in photonics and in radio science. PMID:23549159

  12. 4th International Conference on Communications, Signal Processing, and Systems

    CERN Document Server

    Mu, Jiasong; Wang, Wei; Zhang, Baoju

    2016-01-01

    This book brings together papers presented at the 4th International Conference on Communications, Signal Processing, and Systems, which provides a venue to disseminate the latest developments and to discuss the interactions and links between these multidisciplinary fields. Spanning topics ranging from Communications, Signal Processing and Systems, this book is aimed at undergraduate and graduate students in Electrical Engineering, Computer Science and Mathematics, researchers and engineers from academia and industry as well as government employees (such as NSF, DOD, DOE, etc).

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

    Science.gov (United States)

    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.

  14. Ultra-high-speed optical signal processing of serial data signals

    DEFF Research Database (Denmark)

    Clausen, Anders; Mulvad, Hans Christian Hansen; Palushani, Evarist;

    2012-01-01

    To ensure that ultra high-speed serial data signals can be utilised in future optical communication networks, it is indispensable to have all-optical signal processing elements at our disposal. In this paper, the most recent advances in our use of non-linear materials incorporated in different...

  15. Ultra-high-speed optical signal processing of Tbaud data signals

    DEFF Research Database (Denmark)

    Oxenløwe, Leif Katsuo; Galili, Michael; Mulvad, Hans Christian Hansen;

    2010-01-01

    We describe methods to generate and optically signal process Tbaud serial optical data signals. We present sub-systems making serial optical Tbit/s systems compatible with standard Ethernet data for data centre applications, and present Tbit/s results using a.o. silicon nanowires....

  16. A Study on Signal Group Processing of AUTOSAR COM Module

    Science.gov (United States)

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

    2013-06-01

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

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

    Science.gov (United States)

    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

  18. Variable-time-delay optical coherent transient signal processing.

    Science.gov (United States)

    Merkel, K D; Babbitt, W R; Anderson, K E; Wagner, K H

    1999-10-15

    A technique is proposed and experimentally demonstrated that achieves simultaneous optical pattern waveform storage and programmable time delay for continuous real-time signal processing by use of optical coherent transient technology. We achieve variable-time-delay and broadband signal processing by frequency shifting of two chirped programming pulses, the chirp rate of one being twice that of the other, without using brief reference pulses and without changing the timing of the programming sequence. We demonstrate the technique experimentally in Tm(3+): YAG at 5 K for 40-MHz chirps by performing temporal signal convolution with true-time delays that vary over a 250-ns range.

  19. Digital signal processing in power system protection and control

    CERN Document Server

    Rebizant, Waldemar; Wiszniewski, Andrzej

    2011-01-01

    Digital Signal Processing in Power System Protection and Control bridges the gap between the theory of protection and control and the practical applications of protection equipment. Understanding how protection functions is crucial not only for equipment developers and manufacturers, but also for their users who need to install, set and operate the protection devices in an appropriate manner. After introductory chapters related to protection technology and functions, Digital Signal Processing in Power System Protection and Control presents the digital algorithms for signal filtering, followed

  20. Conjugate spectrum filters for eddy current signal processing

    Energy Technology Data Exchange (ETDEWEB)

    Stepinski, T.; Maszi, N. (Univ. of Uppsala (Sweden). 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.

  1. A Hydrogen Containment Process for Nuclear Thermal Engine Ground testing

    Science.gov (United States)

    Wang, Ten-See; Stewart, Eric; Canabal, Francisco

    2016-01-01

    The objective of this study is to propose a new total hydrogen containment process to enable the testing required for NTP engine development. This H2 removal process comprises of two unit operations: an oxygen-rich burner and a shell-and-tube type of heat exchanger. This new process is demonstrated by simulation of the steady state operation of the engine firing at nominal conditions.

  2. Serial optical communications and ultra-fast optical signal processing of Tbit/s data signals

    DEFF Research Database (Denmark)

    Oxenløwe, Leif Katsuo; Galili, Michael; Hu, Hao;

    2010-01-01

    This paper reviews our recent advances in ultra-high speed serial optical communications. It describes Tbit/s optical signal processing and various materials allowing for this, as well as network scenarios embracing this technology......This paper reviews our recent advances in ultra-high speed serial optical communications. It describes Tbit/s optical signal processing and various materials allowing for this, as well as network scenarios embracing this technology...

  3. Biomedical signal acquisition, processing and transmission using smartphone

    Energy Technology Data Exchange (ETDEWEB)

    Roncagliolo, Pablo [Department of Electronics, Universidad Tecnica Federico Santa Maria, Casilla 110-V, ValparaIso (Chile); Arredondo, Luis [Department of Biomedical Engineering, Universidad de ValparaIso, Casilla 123-V, ValparaIso (Chile); Gonzalez, AgustIn [Department of Electronics, Universidad Tecnica Federico Santa MarIa, Casilla 110-V, ValparaIso (Chile)

    2007-11-15

    This article describes technical aspects involved in the programming of a system of acquisition, processing and transmission of biomedical signals by using mobile devices. This task is aligned with the permanent development of new technologies for the diagnosis and sickness treatment, based on the feasibility of measuring continuously different variables as electrocardiographic signals, blood pressure, oxygen concentration, pulse or simply temperature. The contribution of this technology is settled on its portability and low cost, which allows its massive use. Specifically this work analyzes the feasibility of acquisition and the processing of signals from a standard smartphone. Work results allow to state that nowadays these equipments have enough processing capacity to execute signals acquisition systems. These systems along with external servers make it possible to imagine a near future where the possibility of making continuous measures of biomedical variables will not be restricted only to hospitals but will also begin to be more frequently used in the daily life and at home.

  4. Mathematical principles of signal processing Fourier and wavelet analysis

    CERN Document Server

    Brémaud, Pierre

    2002-01-01

    Fourier analysis is one of the most useful tools in many applied sciences. The recent developments of wavelet analysis indicates that in spite of its long history and well-established applications, the field is still one of active research. This text bridges the gap between engineering and mathematics, providing a rigorously mathematical introduction of Fourier analysis, wavelet analysis and related mathematical methods, while emphasizing their uses in signal processing and other applications in communications engineering. The interplay between Fourier series and Fourier transforms is at the heart of signal processing, which is couched most naturally in terms of the Dirac delta function and Lebesgue integrals. The exposition is organized into four parts. The first is a discussion of one-dimensional Fourier theory, including the classical results on convergence and the Poisson sum formula. The second part is devoted to the mathematical foundations of signal processing - sampling, filtering, digital signal proc...

  5. High-resolution imaging methods in array signal processing

    DEFF Research Database (Denmark)

    Xenaki, Angeliki

    The purpose of this study is to develop methods in array signal processing which achieve accurate signal reconstruction from limited observations resulting in high-resolution imaging. The focus is on underwater acoustic applications and sonar signal processing both in active (transmit and receive...... in active sonar signal processing for detection and imaging of submerged oil contamination in sea water from a deep-water oil leak. The submerged oil _eld is modeled as a uid medium exhibiting spatial perturbations in the acoustic parameters from their mean ambient values which cause weak scattering......) and passive (only receive) mode. The study addresses the limitations of existing methods and shows that, in many cases, the proposed methods overcome these limitations and outperform traditional methods for acoustic imaging. The project comprises two parts; The first part deals with computational methods...

  6. Interface Design Of Digital Platform For Bio Signal Processing

    Institute of Scientific and Technical Information of China (English)

    Jongsik; Park; Moonsu; Jang; Seongoo; Lee

    2010-01-01

    <正>Bio-sensor arrays for multi-channel recording have been developed recently and signal processing platforms for those signals have been studied actively.But it’s thereal situation which these technologies are generally developed and studied respectively.So the interface design between recording array and signal processing platform is also an important issue to make bio-sensor signal processing system.In this paper,we proposed interface which has unique protocols to control sensor array and operate platform.There are two types of protocols in the interface.One is between sensor array and MCU in platform and the other is between MCU and board for wireless communication.Basically,each protocol has two kinds of modes(single,frame)and it can be extended if needed.

  7. High-speed optical coherence tomography signal processing on GPU

    Energy Technology Data Exchange (ETDEWEB)

    Li Xiqi; Shi Guohua; Zhang Yudong, E-mail: lixiqi@yahoo.cn [Laboratory on Adaptive Optics, Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu 610209 (China)

    2011-01-01

    The signal processing speed of spectral domain optical coherence tomography (SD-OCT) has become a bottleneck in many medical applications. Recently, a time-domain interpolation method was proposed. This method not only gets a better signal-to noise ratio (SNR) but also gets a faster signal processing time for the SD-OCT than the widely used zero-padding interpolation method. Furthermore, the re-sampled data is obtained by convoluting the acquired data and the coefficients in time domain. Thus, a lot of interpolations can be performed concurrently. So, this interpolation method is suitable for parallel computing. An ultra-high optical coherence tomography signal processing can be realized by using graphics processing unit (GPU) with computer unified device architecture (CUDA). This paper will introduce the signal processing steps of SD-OCT on GPU. An experiment is performed to acquire a frame SD-OCT data (400A-linesx2048 pixel per A-line) and real-time processed the data on GPU. The results show that it can be finished in 6.208 milliseconds, which is 37 times faster than that on Central Processing Unit (CPU).

  8. Signal processing method and system for noise removal and signal extraction

    Science.gov (United States)

    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.

  9. Validation of Atmosphere/Ionosphere Signals Associated with Major Earthquakes by Multi-Instrument Space-Borne and Ground Observations

    Science.gov (United States)

    Ouzounov, Dimitar; Pulinets, Sergey; Hattori, Katsumi; Parrot, Michel; Liu, J. Y.; Yang, T. F.; Arellano-Baeza, Alonso; Kafatos, M.; Taylor, Patrick

    2012-01-01

    The latest catastrophic earthquake in Japan (March 2011) has renewed interest in the important question of the existence of pre-earthquake anomalous signals related to strong earthquakes. Recent studies have shown that there were precursory atmospheric/ionospheric signals observed in space associated with major earthquakes. The critical question, still widely debated in the scientific community, is whether such ionospheric/atmospheric signals systematically precede large earthquakes. To address this problem we have started to investigate anomalous ionospheric / atmospheric signals occurring prior to large earthquakes. We are studying the Earth's atmospheric electromagnetic environment by developing a multisensor model for monitoring the signals related to active tectonic faulting and earthquake processes. The integrated satellite and terrestrial framework (ISTF) is our method for validation and is based on a joint analysis of several physical and environmental parameters (thermal infrared radiation, electron concentration in the ionosphere, lineament analysis, radon/ion activities, air temperature and seismicity) that were found to be associated with earthquakes. A physical link between these parameters and earthquake processes has been provided by the recent version of Lithosphere-Atmosphere-Ionosphere Coupling (LAIC) model. Our experimental measurements have supported the new theoretical estimates of LAIC hypothesis for an increase in the surface latent heat flux, integrated variability of outgoing long wave radiation (OLR) and anomalous variations of the total electron content (TEC) registered over the epicenters. Some of the major earthquakes are accompanied by an intensification of gas migration to the surface, thermodynamic and hydrodynamic processes of transformation of latent heat into thermal energy and with vertical transport of charged aerosols in the lower atmosphere. These processes lead to the generation of external electric currents in specific

  10. Assess sleep stage by modern signal processing techniques.

    Science.gov (United States)

    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.

  11. Analysis and simulation of brain signal data by EEG signal processing technique using MATLAB

    Directory of Open Access Journals (Sweden)

    Sasikumar Gurumurthy

    2013-06-01

    Full Text Available EEG is brain signal processing technique that allows gaining the understanding of the complex inner mechanisms of the brain and abnormal brain waves have shown to be associated with particular brain disorders. The analysis of brain waves plays an important role in diagnosis of different brain disorders. MATLAB provides an interactive graphic user interface (GUI allowing users to flexiblyand interactively process their high-density EEG dataset and other brain signal data different techniques such as independent component analysis (ICA and/or time/frequency analysis (TFA, as well as standard averaging methods. We will be showing different brain signals by comparing, analysing and simulating datasets which is already loaded in the MATLAB software to process the EEG signals.

  12. Signals and Systems in Biomedical Engineering Signal Processing and Physiological Systems Modeling

    CERN Document Server

    Devasahayam, Suresh R

    2013-01-01

    The use of digital signal processing is ubiquitous in the field of physiology and biomedical engineering. The application of such mathematical and computational tools requires a formal or explicit understanding of physiology. Formal models and analytical techniques are interlinked in physiology as in any other field. This book takes a unitary approach to physiological systems, beginning with signal measurement and acquisition, followed by signal processing, linear systems modelling, and computer simulations. The signal processing techniques range across filtering, spectral analysis and wavelet analysis. Emphasis is placed on fundamental understanding of the concepts as well as solving numerical problems. Graphs and analogies are used extensively to supplement the mathematics. Detailed models of nerve and muscle at the cellular and systemic levels provide examples for the mathematical methods and computer simulations. Several of the models are sufficiently sophisticated to be of value in understanding real wor...

  13. The RWP-RK factor GROUNDED promotes embryonic polarity by facilitating YODA MAP kinase signaling.

    Science.gov (United States)

    Jeong, Sangho; Palmer, Travis M; Lukowitz, Wolfgang

    2011-08-09

    The division of plant zygotes is typically asymmetric, generating daughter cells with different developmental fates. In Arabidopsis, the apical daughter cell produces the proembryo, whereas the basal daughter cell forms the mostly extraembryonic suspensor. Establishment of apical and basal fates is known to depend on the YODA (YDA) mitogen-associated protein (MAP) kinase cascade and WUSCHEL-LIKE HOMEOBOX (WOX) homeodomain transcription factors. Mutations in GROUNDED (GRD) cause anatomical defects implying a partial loss of developmental asymmetry in the first division. Subsequently, suspensor-specific WOX8 expression disappears while proembryo-specific ZLL expression expands in the mutants, revealing that basal fates are confounded. GRD encodes a small nuclear protein of the RWP-RK family and is broadly transcribed in the early embryo. Loss of GRD eliminates the dominant effects of hyperactive YDA variants, indicating that GRD is required for YDA-dependent signaling in the embryo. However, GRD function is not regulated via direct phosphorylation by MAP kinases, and forced expression of GRD does not suppress the effect of yda mutations. In a strong synthetic interaction, grd;wox8;wox9 triple mutants arrest as zygotes or one-cell embryos lacking apparent polarity. The predicted transcription factor GRD acts cooperatively with WOX homeodomain proteins to establish embryonic polarity in the first division. Like YDA, GRD promotes zygote elongation and basal cell fates. GRD function is required for YDA-dependent signaling but apparently not regulated by the YDA MAP kinase cascade. Similarity of GRD to Chlamydomonas MID suggests a conserved role for small RWP-RK proteins in regulating the transcriptional programs of generative cells and the zygote. Copyright © 2011 Elsevier Ltd. All rights reserved.

  14. Real-time digital signal processing fundamentals, implementations and applications

    CERN Document Server

    Kuo, Sen M; Tian, Wenshun

    2013-01-01

    Combines both the DSP principles and real-time implementations and applications, and now updated with the new eZdsp USB Stick, which is very low cost, portable and widely employed at many DSP labs. Real-Time Digital Signal Processing introduces fundamental digital signal processing (DSP) principles and will be updated to include the latest DSP applications, introduce new software development tools and adjust the software design process to reflect the latest advances in the field. In the 3rd edition of the book, the key aspect of hands-on experiments will be enhanced to make the DSP principle

  15. Advanced Digital Signal Processing for Hybrid Lidar FY 2014

    Science.gov (United States)

    2014-10-30

    Report 3. DATES COVERED (Frorr) - To) 6/2011 to 9/2014 4. TITLE AND SUBTITLE Advance Digital Signal Processing for Hybrid Lidar 5a. CONTRACT NUMBER...report describes the technical progress towards the development of signed processing algorithms for hybrid lidar - radar designed to improve...detection performance. 15. SUBJECT TERMS Hybrid Lidar

  16. All-Optical Signal Processing using Silicon Devices

    DEFF Research Database (Denmark)

    Oxenløwe, Leif Katsuo; Pu, Minhao; Ding, Yunhong;

    2014-01-01

    This paper presents an overview of recent wo rk on the use of silicon waveguides for processing optical data signals. We will describe ultra-fast, ultra-broadband, polarisation-insensitive and phase-sensitive applications including processing of spectrally-efficient data formats and optical phase...

  17. Signal Processing Techniques for 5G:An Overview

    Institute of Scientific and Technical Information of China (English)

    Fa Long Luo

    2015-01-01

    This paper gives an outline of the algorithms and implementation of the main signal processing techniques being developed for 5G wireless communication. The first part contains a review and comparison of six orthogonal and non⁃orthogonal waveform⁃generation and modulation schemes: generalized frequency⁃division multiplexing (GFDM), filter⁃bank multicarrier (FBMC), universal filtered multicarrier (UFMC), bi⁃orthogonal frequency⁃division multiplexing (BFDM), sparse⁃code multiple⁃access (SCMA), and non⁃orthogo⁃nal multiple access (NOMA). The second part discusses spatial signal processing algorithms and implementations for massive mul⁃tiple⁃input multiple⁃output (massive⁃MIMO), 3D beamforming and diversity, and orbital angular momentum (OAM) based multi⁃plexing. The last part gives an overview of signal processing aspects of other emerging techniques in 5G, such as millimeter⁃wave, cloud radio access networks, full duplex mode, and digital radio⁃frequency processing.

  18. Advances in signal processing and intelligent recognition systems

    CERN Document Server

    Gelbukh, Alexander; Mukhopadhyay, Jayanta

    2014-01-01

    This Edited Volume contains a selection of refereed and revised papers originally presented at the International Symposium on Signal Processing and Intelligent Recognition Systems (SIRS-2014), March 13-15, 2014, Trivandrum, India. The program committee received 134 submissions from 11 countries. Each paper was peer reviewed by at least three or more independent referees of the program committee and the 52 papers were finally selected. The papers offer stimulating insights into Pattern Recognition, Machine Learning and Knowledge-Based Systems; Signal and Speech Processing; Image and Video Processing; Mobile Computing and Applications and Computer Vision. The book is directed to the researchers and scientists engaged in various field of signal processing and related areas.  

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

    Science.gov (United States)

    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.

  20. Fractional Processes and Fractional-Order Signal Processing Techniques and Applications

    CERN Document Server

    Sheng, Hu; Qiu, TianShuang

    2012-01-01

    Fractional processes are widely found in science, technology and engineering systems. In Fractional Processes and Fractional-order Signal Processing, some complex random signals, characterized by the presence of a heavy-tailed distribution or non-negligible dependence between distant observations (local and long memory), are introduced and examined from the ‘fractional’ perspective using simulation, fractional-order modeling and filtering and realization of fractional-order systems. These fractional-order signal processing (FOSP) techniques are based on fractional calculus, the fractional Fourier transform and fractional lower-order moments. Fractional Processes and Fractional-order Signal Processing: • presents fractional processes of fixed, variable and distributed order studied as the output of fractional-order differential systems; • introduces FOSP techniques and the fractional signals and fractional systems point of view; • details real-world-application examples of FOSP techniques to demonstr...

  1. Nonlinear Silicon Photonic Signal Processing Devices for Future Optical Networks

    Directory of Open Access Journals (Sweden)

    Cosimo Lacava

    2017-01-01

    Full Text Available In this paper, we present a review on silicon-based nonlinear devices for all optical nonlinear processing of complex telecommunication signals. We discuss some recent developments achieved by our research group, through extensive collaborations with academic partners across Europe, on optical signal processing using silicon-germanium and amorphous silicon based waveguides as well as novel materials such as silicon rich silicon nitride and tantalum pentoxide. We review the performance of four wave mixing wavelength conversion applied on complex signals such as Differential Phase Shift Keying (DPSK, Quadrature Phase Shift Keying (QPSK, 16-Quadrature Amplitude Modulation (QAM and 64-QAM that dramatically enhance the telecom signal spectral efficiency, paving the way to next generation terabit all-optical networks.

  2. Signal processing techniques for atrial fibrillation source detection.

    Science.gov (United States)

    Ambadkar, Minal; Leonelli, Fabio M; Sankar, Ravi

    2014-01-01

    In clinical practice, Atrial Fibrillation (AF) is the most common and critical cardiac arrhythmia encountered. The treatment that can ensure permanent AF removal is catheter ablation, where cardiologists destroy the affected cardiac muscle cells with RF or Laser. In this procedure it is necessary to know exactly from which part of the heart AF triggers are originated. Various signal processing algorithms provide a strong tool to track AF sources. This study proposes, signal processing techniques that can be exploited for characterization, analysis and source detection of AF signals. These algorithms are implemented on Electrocardiogram (ECG) and intracardiac signals which contain important information that allows the analysis of anatomic and physiologic aspects of the whole cardiac muscle.

  3. Space-Time Coding and Signal Processing for MIMO Communications

    Institute of Scientific and Technical Information of China (English)

    Inaki Berenguer; Xiaodong Wang

    2003-01-01

    Rapid growth in mobile computing and other wireless multimedia services is inspiring many research and development activities on high-speed wireless communication systems.Main challenges in this area include the development of efficient coding and modulation signal processing techniques for improving the quality and spectral efficiency of wireless systems. The recently emerged space-time coding and signal processing techniques for wireless communication systems employing multiple transmit and receive antennas offer a powerful paradigm for meeting these challenges. This paper provides an overview on the recent development in space-time coding and signal processing techniques for multiple-input multiple-output (MIMO) communication systems. We first review the information theoretic results on the capacities of wireless systems employing multiple transmit and receive antennas. We then describe two representative categories of space-time systems, namely, the BLAST system and the space-time block coding system, both of which have been proposed for next-generation high-speed wireless system. Signal processing techniques for channel estimation and decoding in space-time systems are also discussed. Finally, some other coding and signal processing techniques for wireless systems employing multiple transmit and receive antennas that are currently under intensive research are also briefly touched upon.

  4. Signal processing of heart signals for the quantification of non-deterministic events

    Directory of Open Access Journals (Sweden)

    Baddour Natalie

    2011-01-01

    Full Text Available Abstract Background Heart signals represent an important way to evaluate cardiovascular function and often what is desired is to quantify the level of some signal of interest against the louder backdrop of the beating of the heart itself. An example of this type of application is the quantification of cavitation in mechanical heart valve patients. Methods An algorithm is presented for the quantification of high-frequency, non-deterministic events such as cavitation from recorded signals. A closed-form mathematical analysis of the algorithm investigates its capabilities. The algorithm is implemented on real heart signals to investigate usability and implementation issues. Improvements are suggested to the base algorithm including aligning heart sounds, and the implementation of the Short-Time Fourier Transform to study the time evolution of the energy in the signal. Results The improvements result in better heart beat alignment and better detection and measurement of the random events in the heart signals, so that they may provide a method to quantify nondeterministic events in heart signals. The use of the Short-Time Fourier Transform allows the examination of the random events in both time and frequency allowing for further investigation and interpretation of the signal. Conclusions The presented algorithm does allow for the quantification of nondeterministic events but proper care in signal acquisition and processing must be taken to obtain meaningful results.

  5. All Optical Signal-Processing Techniques Utilizing Four Wave Mixing

    Directory of Open Access Journals (Sweden)

    Refat Kibria

    2015-02-01

    Full Text Available Four Wave Mixing (FWM based optical signal-processing techniques are reviewed. The use of FWM in arithmetical operation like subtraction, wavelength conversion and pattern recognition are three key parts discussed in this paper after a brief introduction on FWM and its comparison with other nonlinear mixings. Two different approaches to achieve correlation are discussed, as well as a novel technique to realize all optical subtraction of two optical signals.

  6. Processing of Communication Signal Using Operational Transconductance Amplifier

    OpenAIRE

    Roy, A.; Ghosh, K.; Mondal, S; Ray, B. N.

    2010-01-01

    This paper proposes a signal processing methodology of communication system and realized that circuits using operational transconductance amplifier (OTA). Two important classes of communication circuit, delta modulator and compander have been designed using that procedure. In the first implementation coded pulse modulation system is demonstrated which employ sampling, quantizing and coding to convert analog waveforms to digital signals while the second gives data compression and expansion in ...

  7. Radar signal design problem with neural network processing

    Indian Academy of Sciences (India)

    C Krishnamohan Rao; P S Moharir

    2001-06-01

    Binary and ternary sequences with peaky autocorrelation, measured in terms of high discrimination and merit factor have been searched earlier, using optimization techniques. It is shown that the use of neural network processing of the return signal is much more advantageous. It opens up a new signal design problem, which is solved by an optimization technique called Hamming scan, for both binary and ternary sequences.

  8. Passive silicon photonic devices for microwave photonic signal processing

    Science.gov (United States)

    Wu, Jiayang; Peng, Jizong; Liu, Boyu; Pan, Ting; Zhou, Huanying; Mao, Junming; Yang, Yuxing; Qiu, Ciyuan; Su, Yikai

    2016-08-01

    We present our recent progress on microwave signal processing (MSP) using on-chip passive silicon photonic devices, including tunable microwave notch filtering/millimeter-wave (MMW) signal generation based on self-coupled micro-resonators (SCMRs), and tunable radio-frequency (RF) phase shifting implemented by a micro-disk resonator (MDR). These schemes can provide improved flexibility and performances of MSP. The experimental results are in good agreement with theoretical predictions, which validate the effectiveness of the proposed schemes.

  9. Modelling coloured residual noise in gravitational-wave signal processing

    Energy Technology Data Exchange (ETDEWEB)

    Roever, Christian [Max-Planck-Institut fuer Gravitationsphysik (Albert-Einstein-Institut) and Leibniz Universitaet Hannover, Hannover (Germany); Meyer, Renate [Department of Statistics, University of Auckland, Auckland (New Zealand); Christensen, Nelson, E-mail: christian.roever@aei.mpg.de [Physics and Astronomy, Carleton College, Northfield, MN (United States)

    2011-01-07

    We introduce a signal processing model for signals in non-white noise, where the exact noise spectrum is a priori unknown. The model is based on a Student's t distribution and constitutes a natural generalization of the widely used normal (Gaussian) model. This way, it allows for uncertainty in the noise spectrum, or more generally is also able to accommodate outliers (heavy-tailed noise) in the data. Examples are given pertaining to data from gravitational-wave detectors.

  10. Adaptive digital signal processing for X-ray spectrometry

    Science.gov (United States)

    Lakatos, T.

    1990-05-01

    A real-time fully digital signal processing and analyzing system based on a new concept has been developed for high count rate high resolution spectrometry. The principle has been realized with digital filtering of the preamplifier output signals. The system's unique features are the maximum theoretically possible throughput rate with high resolution, and the adaptive noise filtering for nearly loss-free measurements. In adaptive mode the maximum output rate is about 20 times higher than in the case of the semi-Gaussian shaping, with low degradation of energy resolution. All parameters of the signal processor are software controllable.

  11. Cellular phosphatases facilitate combinatorial processing of receptor-activated signals

    Directory of Open Access Journals (Sweden)

    Siddiqui Zaved

    2008-09-01

    Full Text Available Abstract Background Although reciprocal regulation of protein phosphorylation represents a key aspect of signal transduction, a larger perspective on how these various interactions integrate to contribute towards signal processing is presently unclear. For example, a key unanswered question is that of how phosphatase-mediated regulation of phosphorylation at the individual nodes of the signaling network translates into modulation of the net signal output and, thereby, the cellular phenotypic response. Results To address the above question we, in the present study, examined the dynamics of signaling from the B cell antigen receptor (BCR under conditions where individual cellular phosphatases were selectively depleted by siRNA. Results from such experiments revealed a highly enmeshed structure for the signaling network where each signaling node was linked to multiple phosphatases on the one hand, and each phosphatase to several nodes on the other. This resulted in a configuration where individual signaling intermediates could be influenced by a spectrum of regulatory phosphatases, but with the composition of the spectrum differing from one intermediate to another. Consequently, each node differentially experienced perturbations in phosphatase activity, yielding a unique fingerprint of nodal signals characteristic to that perturbation. This heterogeneity in nodal experiences, to a given perturbation, led to combinatorial manipulation of the corresponding signaling axes for the downstream transcription factors. Conclusion Our cumulative results reveal that it is the tight integration of phosphatases into the signaling network that provides the plasticity by which perturbation-specific information can be transmitted in the form of a multivariate output to the downstream transcription factor network. This output in turn specifies a context-defined response, when translated into the resulting gene expression profile.

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

    Science.gov (United States)

    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.

  13. Digital Signal Processing Filtering Algorithm : Audio Equalization Using Matlab

    OpenAIRE

    Chaguaro Aldaz, Daniel

    2015-01-01

    The contemporary domain of Digital Signal Processing is in constant influx and trying to find new applications that will benefit the everyday life of ordinary people. In modern technology, most of the electronic processes use DSP algorithms in order to collect analogue information that is continually present all around us and convert it into a digital form. The need of understanding the basics of how these processes occur, has inspired to implement a DSP application for educational and testin...

  14. Digital signal processing for wireless communication using Matlab

    CERN Document Server

    Gopi, E S

    2016-01-01

    This book examines signal processing techniques used in wireless communication illustrated by using the Matlab program. The author discusses these techniques as they relate to Doppler spread; delay spread; Rayleigh and Rician channel modeling; rake receiver; diversity techniques; MIMO and OFDM -based transmission techniques; and array signal processing. Related topics such as detection theory, link budget, multiple access techniques, and spread spectrum are also covered.   ·         Illustrates signal processing techniques involved in wireless communication using Matlab ·         Discusses multiple access techniques such as Frequency division multiple access, Time division multiple access, and Code division multiple access ·         Covers band pass modulation techniques such as Binary phase shift keying, Differential phase shift keying, Quadrature phase shift keying, Binary frequency shift keying, Minimum shift keying, and Gaussian minimum shift keying.

  15. 2015 International Conference on Machine Learning and Signal Processing

    CERN Document Server

    Woo, Wai; Sulaiman, Hamzah; Othman, Mohd; Saat, Mohd

    2016-01-01

    This book presents important research findings and recent innovations in the field of machine learning and signal processing. A wide range of topics relating to machine learning and signal processing techniques and their applications are addressed in order to provide both researchers and practitioners with a valuable resource documenting the latest advances and trends. The book comprises a careful selection of the papers submitted to the 2015 International Conference on Machine Learning and Signal Processing (MALSIP 2015), which was held on 15–17 December 2015 in Ho Chi Minh City, Vietnam with the aim of offering researchers, academicians, and practitioners an ideal opportunity to disseminate their findings and achievements. All of the included contributions were chosen by expert peer reviewers from across the world on the basis of their interest to the community. In addition to presenting the latest in design, development, and research, the book provides access to numerous new algorithms for machine learni...

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

    Institute of Scientific and Technical Information of China (English)

    Zara Ghodsi; Emmanuel Sirimal Silva; Hossein Hassani

    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.

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

    Science.gov (United States)

    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.

  18. Distributed Signal Processing for Wireless EEG Sensor Networks.

    Science.gov (United States)

    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.

  19. An implementation of signal processing algorithms for ultrasonic NDE

    Energy Technology Data Exchange (ETDEWEB)

    Ericsson, L.; Stepinski, T. [Uppsala Univ. (Sweden). Dept. of Technology, Circuits and Systems

    1994-12-31

    Probability of detection flaws during ultrasonic pulse-echo inspection is often limited by the presence of backscattered echoes from the material structure. A digital signal processing technique for removal of this material noise, referred to as split spectrum processing (SSP), has been developed and verified using laboratory experiments during the last decade. The authors have performed recently a limited scale evaluation of various SSP techniques for ultrasonic signals acquired during the inspection of welds in austenitic steel. They have obtained very encouraging results that indicate promising capabilities of the SSP for inspection of nuclear power plants. Thus, a more extensive investigation of the technique using large amounts of ultrasonic data is motivated. This analysis should employ different combinations of materials, flaws and transducers. Due to the considerable number of ultrasonic signals required to verify the technique for future practical use, a custom-made computer software is necessary. At the request of the Swedish nuclear power industry the authors have developed such a program package. The program provides a user-friendly graphical interface and is intended for processing of B-scan data in a flexible way. Assembled in the program are a number of signal processing algorithms including traditional Split Spectrum Processing and the more recent Cut Spectrum Processing algorithm developed by them. The program and some results obtained using the various algorithms are presented in the paper.

  20. Communication theory and signal processing for transform coding

    CERN Document Server

    El-Shennawy, Khamies Mohammed Ali

    2014-01-01

    This book is tailored to fulfil the requirements in the area of the signal processing in communication systems. The book contains numerous examples, solved problems and exercises to explain the methodology of Fourier Series, Fourier Analysis, Fourier Transform and properties, Fast Fourier Transform FFT, Discrete Fourier Transform DFT and properties, Discrete Cosine Transform DCT, Discrete Wavelet Transform DWT and Contourlet Transform CT. The book is characterized by three directions, the communication theory and signal processing point of view, the mathematical point of view and utility compu

  1. Signal processing in magnetic resonance spectroscopy with biomedical applications

    CERN Document Server

    Belkic, Dzevad

    2010-01-01

    ""a useful addition to the fields of both magnetic resonance (MR) as well as signal processing. … immensely useful as a practical resource handbook to dip into from time to time and to find specific advice on issues faced during the course of work in MR techniques for cancer research. … the best feature of this book is how it positions the very practical area of digital signal processing in the contextual framework of a much more esoteric and fundamental field-that of quantum mechanics. The direct link between quantum-mechanical spectral analysis and rational response functions and the gene

  2. Ultra-broadband and ultra-fast optical signal processing

    DEFF Research Database (Denmark)

    Oxenløwe, Leif Katsuo

    2015-01-01

    We have recently seen that nanowires can provide unparalleled optical signal processing (OSP) bandwidth and provide ultra-fast operation as well. Utilising the ultra-broad OSP bandwidth for e.g. optical time lenses allows for energy-efficient optical switching. © 2015 OSA.......We have recently seen that nanowires can provide unparalleled optical signal processing (OSP) bandwidth and provide ultra-fast operation as well. Utilising the ultra-broad OSP bandwidth for e.g. optical time lenses allows for energy-efficient optical switching. © 2015 OSA....

  3. Structural health monitoring an advanced signal processing perspective

    CERN Document Server

    Chen, Xuefeng; Mukhopadhyay, Subhas

    2017-01-01

    This book highlights the latest advances and trends in advanced signal processing (such as wavelet theory, time-frequency analysis, empirical mode decomposition, compressive sensing and sparse representation, and stochastic resonance) for structural health monitoring (SHM). Its primary focus is on the utilization of advanced signal processing techniques to help monitor the health status of critical structures and machines encountered in our daily lives: wind turbines, gas turbines, machine tools, etc. As such, it offers a key reference guide for researchers, graduate students, and industry professionals who work in the field of SHM.

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

    Science.gov (United States)

    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. The Savant Hypothesis: is autism a signal-processing problem?

    Science.gov (United States)

    Fabricius, Thomas

    2010-08-01

    Autism is being investigated through many different approaches. This paper suggests the genetic, perceptual, cognitive, and histological findings ultimately manifest themselves as variations of the same signal-processing problem of defective compression. The Savant Hypothesis is formulated from first principles of both mathematical signal-processing and primary neuroscience to reflect the failure of compression. The Savant Hypothesis is applied to the problem of autism in a surprisingly straightforward application. The enigma of the autistic savant becomes intuitive when observed from this approach.

  6. Phosphorelays Provide Tunable Signal Processing Capabilities for the Cell

    Science.gov (United States)

    Kothamachu, Varun B.; Feliu, Elisenda; Wiuf, Carsten; Cardelli, Luca; Soyer, Orkun S.

    2013-01-01

    Achieving a complete understanding of cellular signal transduction requires deciphering the relation between structural and biochemical features of a signaling system and the shape of the signal-response relationship it embeds. Using explicit analytical expressions and numerical simulations, we present here this relation for four-layered phosphorelays, which are signaling systems that are ubiquitous in prokaryotes and also found in lower eukaryotes and plants. We derive an analytical expression that relates the shape of the signal-response relationship in a relay to the kinetic rates of forward, reverse phosphorylation and hydrolysis reactions. This reveals a set of mathematical conditions which, when satisfied, dictate the shape of the signal-response relationship. We find that a specific topology also observed in nature can satisfy these conditions in such a way to allow plasticity among hyperbolic and sigmoidal signal-response relationships. Particularly, the shape of the signal-response relationship of this relay topology can be tuned by altering kinetic rates and total protein levels at different parts of the relay. These findings provide an important step towards predicting response dynamics of phosphorelays, and the nature of subsequent physiological responses that they mediate, solely from topological features and few composite measurements; measuring the ratio of reverse and forward phosphorylation rate constants could be sufficient to determine the shape of the signal-response relationship the relay exhibits. Furthermore, they highlight the potential ways in which selective pressures on signal processing could have played a role in the evolution of the observed structural and biochemical characteristic in phosphorelays. PMID:24244132

  7. Crosstalk between Wnt Signaling and RNA Processing in Colorectal Cancer

    Directory of Open Access Journals (Sweden)

    Michael Bordonaro

    2013-01-01

    Full Text Available RNA processing involves a variety of processes affecting gene expression, including the removal of introns through RNA splicing, as well as 3' end processing (cleavage and polyadenylation. Alternative RNA processing is fundamentally important for gene regulation, and aberrant processing is associated with the initiation and progression of cancer. Deregulated Wnt signaling, which is the initiating event in the development of most cases of human colorectal cancer (CRC, has been linked to modified RNA processing, which may contribute to Wnt-mediated colonic carcinogenesis. Crosstalk between Wnt signaling and alternative RNA splicing with relevance to CRC includes effects on the expression of Rac1b, an alternatively spliced gene associated with tumorigenesis, which exhibits alternative RNA splicing that is influenced by Wnt activity. In addition, Tcf4, a crucial component of Wnt signaling, also exhibits alternative splicing, which is likely involved in colonic tumorigenesis. Modulation of 3' end formation, including of the Wnt target gene COX-2, also can influence the neoplastic process, with implications for CRC. While many human genes are dependent on introns and splicing for normal levels of gene expression, naturally intronless genes exist with a unique metabolism that allows for intron-independent gene expression. Effects of Wnt activity on the RNA metabolism of the intronless Wnt-target gene c-jun is a likely contributor to cancer development. Further, butyrate, a breakdown product of dietary fiber and a histone deacetylase inhibitor, upregulates Wnt activity in CRC cells, and also modulates RNA processing; therefore, the interplay between Wnt activity, the modulation of this activity by butyrate, and differential RNA metabolism in colonic cells can significantly influence tumorigenesis. Determining the role played by altered RNA processing in Wnt-mediated neoplasia may lead to novel interventions aimed at restoring normal RNA metabolism for

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

    Science.gov (United States)

    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.

  9. Signal-oriented processing in a speed independent environment

    Directory of Open Access Journals (Sweden)

    Aleksandr Katkow

    2013-04-01

    Full Text Available This article is devoted to the research of a simulation system that uses signal-oriented inte-grators. The simulation environment is based on SIC (Speed Independent Circuits. The ar-ticle first examines the implementation of arithmetical operations, which have been inspired by the natural world, in environments lacking global synchronization of computational pro-cesses. The article then describes the process used to calculate the Riemann integral using the signal oriented integrator and develops integration algorithms (rectangles and trape-zoids for use in such environments. It includes pseudo-code that implements these algo-rithms. A method is then discussed for fixing the duration of transients in combinational logic circuits and for a signal-oriented implementation of the integration process. It also considers the mapping of the signal oriented integration process as a fuzzy integration pro-cess. Finally, the article presents the results of a computer simulation of a system with sig-nal-oriented integrators for solving differential equations of partial derivatives.

  10. Controlled processing of signal stored in metamaterial with tripod structure

    CERN Document Server

    Zielińska-Raczyńska, S

    2016-01-01

    In the present paper we have discussed in detail electromagnetically induced transparency and signal storing in the case of one signal pulses propagating in a classical electric medium resembling this of four-level atoms in the tripod configuration. Our theoretical results confirm recently observed dependence of transparency windows position on coupling parameters. In the process of storing the pulse energy is confined inside the metamaterial as electric charge oscillations and after required time it is possible to switch the control fields on again and to release the trapped signal. By manipulating the driving fields one can thus control the parameters of the released signal and even to divide it on demand into arbitrary parts.

  11. Grounding context in face processing: color, emotion, and gender.

    Science.gov (United States)

    Gil, Sandrine; Le Bigot, Ludovic

    2015-01-01

    In recent years, researchers have become interested in the way that the affective quality of contextual information transfers to a perceived target. We therefore examined the effect of a red (vs. green, mixed red/green, and achromatic) background - known to be valenced - on the processing of stimuli that play a key role in human interactions, namely facial expressions. We also examined whether the valenced-color effect can be modulated by gender, which is also known to be valenced. Female and male adult participants performed a categorization task of facial expressions of emotion in which the faces of female and male posers expressing two ambiguous emotions (i.e., neutral and surprise) were presented against the four different colored backgrounds. Additionally, this task was completed by collecting subjective ratings for each colored background in the form of five semantic differential scales corresponding to both discrete and dimensional perspectives of emotion. We found that the red background resulted in more negative face perception than the green background, whether the poser was female or male. However, whereas this valenced-color effect was the only effect for female posers, for male posers, the effect was modulated by both the nature of the ambiguous emotion and the decoder's gender. Overall, our findings offer evidence that color and gender have a common valence-based dimension.

  12. Grounding Context in Face Processing: Color, Emotion and Gender

    Directory of Open Access Journals (Sweden)

    Sandrine eGil

    2015-03-01

    Full Text Available In recent years, researchers have become interested in the way that the affective quality of contextual information transfers to a perceived target. We therefore examined the effect of a red (versus green, mixed red/green and achromatic background–known to be valenced−on the processing of stimuli that play a key role in human interactions, namely facial expressions. We also examined whether the valenced-color effect can be modulated by gender, which is also known to be valenced. Female and male adult participants performed a categorization task of facial expressions of emotion in which the faces of female and male posers expressing two ambiguous emotions (i.e., neutral and surprise were presented against the four different colored backgrounds. Additionally, this task was completed by collecting subjective ratings for each colored background in the form of five semantic differential scales corresponding to both discrete and dimensional perspectives of emotion. We found that the red background resulted in more negative face perception than the green background, whether the poser was female or male. However, whereas this valenced-color effect was the only effect for female posers, for male posers, the effect was modulated by both the nature of the ambiguous emotion and the decoder’s gender. Overall, our findings offer evidence that color and gender have a common valence-based dimension.

  13. Open-loop GPS signal tracking at low elevation angles from a ground-based observation site

    Science.gov (United States)

    Beyerle, Georg; Zus, Florian

    2017-01-01

    A 1-year data set of ground-based GPS signal observations aiming at geometric elevation angles below +2° is analysed. Within the "GLESER" measurement campaign about 2600 validated setting events were recorded by the "OpenGPS" open-loop tracking receiver at an observation site located at 52.3808° N, 13.0642° E between January and December 2014. The measurements confirm the feasibility of open-loop signal tracking down to geometric elevation angles of -1 to -1.5° extending the corresponding closed-loop tracking range by up to 1°. The study is based on the premise that observations of low-elevation events by a ground-based receiver may serve as test cases for space-based radio occultation measurements, even if the latter proceed at a significantly faster temporal scale. The results support the conclusion that the open-loop Doppler model has negligible influence on the derived carrier frequency profile for strong signal-to-noise density ratios above about 30 dB Hz. At lower signal levels, however, the OpenGPS receiver's dual-channel design, which tracks the same signal using two Doppler models differing by 10 Hz, uncovers a notable bias. The repeat patterns of the GPS orbit traces in terms of azimuth angle reveal characteristic signatures in both signal amplitude and Doppler frequency with respect to the topography close to the observation site. Mean vertical refractivity gradients, extracted from ECMWF meteorological fields, correlate weakly to moderately with observed signal amplitude fluctuations at geometric elevation angles between +1 and +2°. Results from multiple phase screen simulations support the interpretation that these fluctuations are at least partly produced by atmospheric multipath; at negative elevation angles diffraction at the ground surface seems to contribute.

  14. Signal processing technique for randomly discontinuous spectra HF radar waveforms

    Institute of Scientific and Technical Information of China (English)

    张东坡; 刘兴钊

    2004-01-01

    A major problem with all high frequency (HF) radars is a relatively poor range resolution available due to many interference sources. To avoid the interferences in frequency domain and operate with wideband, the randomly discontinuous spectra (RDS) signal is employed. However, it results in high range sidelobes when matching the reflected echo, which is much more difficult for target detection. A new signal processing technique that is radically different from the conventional technique to lower range sidelobes is introduced. This method is based on suppressing the selfclutter of the radar range ambiguity function (AF) by mismatched filtering. An effective algorithm is adopted to solve the filter coefficients. Simulation results show that the peak sidelobe level can be reduced to -30dB and the achievable system bandwidth is about 400KHz. The technique is adaptable to practical radar systems and applicable for other realtime signal processing.

  15. Smart signal processing for an evolving electric grid

    Science.gov (United States)

    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.

  16. SoC-based architecture for biomedical signal processing.

    Science.gov (United States)

    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.

  17. Signal processing techniques for forward imaging using ultrawideband synthetic aperture radar

    Science.gov (United States)

    Nguyen, Lam H.; Ton, Tuan T.; Wong, David C.; Ressler, Marc A.

    2003-09-01

    The U.S. Army Research Laboratory (ARL), as part of a customer and mission-funded exploratory development program, has been developing a prototype of low-frequency, ultra-wideband (UWB) forward-imaging synthetic aperture radar (SAR) to support the U.S. Army's vision for increased mobility and survivability of unmanned ground vehicle missions. The ability of the UWB radar technology to detect objects under foilage could provide an important obstacle-avoidance capability for robotic vehicles, which could improve the speed and maneuverability of these vehicles and consequently increase the survivability of the U.S. forces. In a recent experiment at Aberdeen Proving Ground (APG), we exercised the UWB SAR radar in forward-looking mode and collected data to support the investigation. This paper discusses the signal processing algorithms and techniques that we developed and applied to the recent UWB SAR forward-looking data. The algorithms include motion data processing, self-interference signal (SIR) removal, radio frequency interference (RFI) signal removal, forward-looking image formation, and visualization techniques. We present forward-loking SAR imagery and also volumetric imagery of some targets.

  18. Parallel Processing of Broad-Band PPM Signals

    Science.gov (United States)

    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).

  19. Introduction to Random Signals and Noise

    NARCIS (Netherlands)

    van Etten, Wim

    Random signals and noise are present in many engineering systems and networks. Signal processing techniques allow engineers to distinguish between useful signals in audio, video or communication equipment, and interference, which disturbs the desired signal. With a strong mathematical grounding,

  20. ATTITUDE RATE ESTIMATION BY GPS DOPPLER SIGNAL PROCESSING

    Institute of Scientific and Technical Information of China (English)

    He Side; Milos Doroslovacki; Guo Zhenyu; Zhang Yufeng

    2003-01-01

    A method is presented for near-Earth spacecraft or aviation vehicle's attitude rate estimation by using relative Doppler frequency shift of the Global Positioning System (GPS)carrier. It comprises two GPS receiving antennas, a signal processing circuit and an algorithm.The whole system is relatively simple, the cost and wcight, as well as power consumption, are very low.

  1. Foundations of digital signal processing theory, algorithms and hardware design

    CERN Document Server

    Gaydecki, Patrick

    2005-01-01

    An excellent introductory text, this book covers the basic theoretical, algorithmic and real-time aspects of digital signal processing (DSP). Detailed information is provided on off-line, real-time and DSP programming and the reader is effortlessly guided through advanced topics such as DSP hardware design, FIR and IIR filter design and difference equation manipulation.

  2. Guidelines for Affective Signal Processing (ASP): From lab to life

    NARCIS (Netherlands)

    van den Broek, Egon; Janssen, Joris H.; Westerink, Joyce H.D.M.; Cohn, J.; Nijholt, Antinus; Pantic, Maja

    2009-01-01

    This article presents the rationale behind ACII2009’s special session: Guidelines for Affective Signal Processing (ASP): From lab to life. Although affect is embraced by both science and engineering, its recognition has not reached a satisfying level. Through a concise overview of ASP and the automa

  3. Tutorial: Signal Processing in Brain-Computer Interfaces

    NARCIS (Netherlands)

    Garcia Molina, G.

    2010-01-01

    Research in Electroencephalogram (EEG) based Brain-Computer Interfaces (BCIs) has been considerably expanding during the last few years. Such an expansion owes to a large extent to the multidisciplinary and challenging nature of BCI research. Signal processing undoubtedly constitutes an essential co

  4. Nonlinear Optical Signal Processing for Tbit/s Ethernet Applications

    DEFF Research Database (Denmark)

    Oxenløwe, Leif Katsuo; Galili, Michael; Mulvad, Hans Christian Hansen;

    2012-01-01

    We review recent experimental demonstrations of Tbaud optical signal processing. In particular, we describe a successful 1.28 Tbit/s serial data generation based on single polarization 1.28 Tbaud symbol rate pulses with binary data modulation (OOK) and subsequent all-optical demultiplexing. We also...

  5. Fast optical signal processing in high bit rate OTDM systems

    DEFF Research Database (Denmark)

    Poulsen, Henrik Nørskov; Jepsen, Kim Stokholm; Clausen, Anders;

    1998-01-01

    As all-optical signal processing is maturing, optical time division multiplexing (OTDM) has also gained interest for simple networking in high capacity backbone networks. As an example of a network scenario we show an OTDM bus interconnecting another OTDM bus, a single high capacity user...

  6. Digital Signal Processing in Acoustics--Part 2.

    Science.gov (United States)

    Davies, H.; McNeill, D. J.

    1986-01-01

    Reviews the potential of a data acquisition system for illustrating the nature and significance of ideas in digital signal processing. Focuses on the fast Fourier transform and the utility of its two-channel format, emphasizing cross-correlation and its two-microphone technique of acoustic intensity measurement. Includes programing format. (ML)

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

    Science.gov (United States)

    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)

  8. Cancer systems biology: signal processing for cancer research

    Institute of Scientific and Technical Information of China (English)

    Olli Yli-Harja; Antti Ylip(a)(a); Matti Nykter; Wei Zhang

    2011-01-01

    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.

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

    Science.gov (United States)

    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.

  10. Guidelines for Affective Signal Processing (ASP): From lab to life

    NARCIS (Netherlands)

    van den Broek, Egon; Janssen, Joris H.; Westerink, Joyce H.D.M.; Cohn, J.; Nijholt, Antinus; Pantic, Maja

    2009-01-01

    This article presents the rationale behind ACII2009’s special session: Guidelines for Affective Signal Processing (ASP): From lab to life. Although affect is embraced by both science and engineering, its recognition has not reached a satisfying level. Through a concise overview of ASP and the

  11. Higher-Dimensional Signal Processing via Multiscale Geometric Analysis

    Science.gov (United States)

    2010-02-10

    1.1 Review of motivation Over the past twenty years multiscale methods like the discrete wavelet transform (DWT) have revolutionized signal processing...sparsity and structure boost the performance of wavelet -domain statistical models and enable simple yet powerful algorithms for estimation/ denoising ...for many state-of-the-art wavelet domain processing algorithms for applications including compression [23,24], denoising [25,26], and segmentation [27

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

    Science.gov (United States)

    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.

  13. Numerical analysis of heat exchange processes for the ground source heat pump system

    Science.gov (United States)

    Saito, H.; Muto, H.; Moritani, S.; Kohgo, Y.; Hamamoto, S.; Takemura, T.; Ohnishi, J.; Komatsu, T.

    2012-12-01

    Ground source heat pump systems (GSHP) use ground or groundwater as a heat source. They can achieve much higher coefficient of performance (COP) than conventional air source heat pump systems because the temperature of the ground is much more stable than that of the air. Heat energy in the ground is then viewed as one of the renewable energy sources. GSHP has been receiving great interests among countries in North America and Western Europe, as well as some developed countries in Asia because it can potentially reduce energy consumption and greenhouse gas emission. While GSHP can inject heat from the buildings to the ground for cooling during the summer, it can pump heat stored in the ground for heating during the winter. As some physical, chemical, and biological properties of the ground and groundwater are temperature dependent, running GSHP can eventually affect groundwater quality. The main objective of this project was to develop a model that allows predicting not only ground and groundwater temperatures but also changes in physical, chemical, and biological properties of ground and groundwater with GSHP under operations. This particular study aims at simulating heat exchange and transfer processes in the ground for a vertical-loop closed GSHP system. In the closed GSHP system, an anti-freezing solution is circulated inside the closed-loop tube, called U-tube, that is buried in the ground. Heat is then transferred to the anti-freezing solution in the U-tube by a heat exchanger. In this study we used HYDRUS to predict temperature of the anti-freezing solution, as well as that of the ground. HYDRUS allows one to simulate variably-saturated water flow and solute and heat transport in porous media numerically in two- and three-dimensional domains with great flexibility in defining boundary conditions. At first changes in anti-freezing solution temperatures measured were predicted in response to Thermal Response Test (TRT) conducted at our study site. Then, heat

  14. The Remodeling Process: A Grounded Theory Study of Perceptions of Treatment among Adult Male Incest Offenders.

    Science.gov (United States)

    Scheela, Rochelle A.

    1992-01-01

    Conducted grounded theory study to explore incest offender perceptions of treatment to generate explanatory theory of sexual abuse treatment process. Findings from theoretical sampling of 20 adult male incest offenders revealed that offenders felt remodeling process occurred as they faced discovery of their abuse and went through treatment.…

  15. Real-Time Signal Processing Data Acquisition Subsystem

    Science.gov (United States)

    Sarafinas, George A.; Stein, Alan J.; Bisson, Kenneth J.

    A digital signal processing sub-system has been developed for a coherent carbon dioxide laser radar system at Lincoln Laboratory's Firepond Research Facility. This high-resolution radar is capable of operating with a variety of waveforms; hence, the signal processing requirements of the sub-system vary from one application to the next, and require a sub-system with a high degree of flexibility. The primary function of the Data Acquisition sub-system is to provide range-Doppler images in real-time. Based on this objective, the sub-system must have the ability to route large amounts of digitized data at high rates between specialized processors performing the functions of data acquisition, digital signal processing, archiving, and image processing. A distributed processing design approach was used and the hardware design implemented was configured using all off-the-shelf commercially available products. The sub-system uses a high speed 24 MB/sec central bus and associated processor acting as the hub of the system. Attached to the bus is a large RAM memory buffer. Also attached to the central bus are individual processors which interface to specialized peripherals, performing the tasks of digitizing, vector processing, imaging, and archiving. The software for the complete Data Acquisition and Signal Processing sub-system was developed on a Digital Equipment MicroVAX IITM computer. Software developed for the completed system is coded mostly in a high level language to promote flexibility, modularity, and reducing development time. Some microcode had to be used where speed is essential. All Software design, development, and testing was done under VMSTM.

  16. Sound Event Detection for Music Signals Using Gaussian Processes

    OpenAIRE

    Pablo A. Alvarado-Durán; Mauricio A. Álvarez-López; Álvaro A. Orozco-Gutiérrez

    2013-01-01

    In this paper we present a new methodology for detecting sound events in music signals using Gaussian Processes. Our method firstly takes a time-frequency representation, i.e. the spectrogram, of the input audio signal. Secondly the spectrogram dimension is reduced translating the linear Hertz frequency scale into the logarithmic Mel frequency scale using a triangular filter bank. Finally every short-time spectrum, i.e. every Mel spectrogram column, is classified as “Event” or “Not Event” by ...

  17. Algorithm-Architecture Matching for Signal and Image Processing

    CERN Document Server

    Gogniat, Guy; Morawiec, Adam; Erdogan, Ahmet

    2011-01-01

    Advances in signal and image processing together with increasing computing power are bringing mobile technology closer to applications in a variety of domains like automotive, health, telecommunication, multimedia, entertainment and many others. The development of these leading applications, involving a large diversity of algorithms (e.g. signal, image, video, 3D, communication, cryptography) is classically divided into three consecutive steps: a theoretical study of the algorithms, a study of the target architecture, and finally the implementation. Such a linear design flow is reaching its li

  18. Fractional Fourier domain analysis of cyclic multirate signal processing

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    The cyclic filter banks, which are used widely in the image subband coding, refer to signal processing on the finite field. This study investigates the fractional Fourier domain (FRFD) analysis of cyclic multirate systems based on the fractional circular convolution and chirp period. The proposed theorems include the fractional Fourier domain analysis of cyclic decimation and cyclic interpolation, the noble identities of cyclic decimation and cyclic interpolation in the FRFD, the polyphase represen-tation of cyclic signal in the FRFD, and the perfect reconstruction condition for the cyclic filter banks in the FRFD. Furthermore, this paper proposes the design methods for perfect reconstruction cyclic filter bank and cyclic filter bank with chirp modulation in the FRFD. The proposed theorems extend the multirate signal processing in the FRFD, which also advance the applications of the theorems of filter bank in the FRFD on the finite signal field, such as digital image processing. At last, the proposed design methods for the cyclic filter banks in the FRFD are validated by simulations.

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

    Science.gov (United States)

    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.

  20. Signal processing for 5G algorithms and implementations

    CERN Document Server

    Luo, Fa-Long

    2016-01-01

    A comprehensive and invaluable guide to 5G technology, implementation and practice in one single volume. For all things 5G, this book is a must-read. Signal processing techniques have played the most important role in wireless communications since the second generation of cellular systems. It is anticipated that new techniques employed in 5G wireless networks will not only improve peak service rates significantly, but also enhance capacity, coverage, reliability , low-latency, efficiency, flexibility, compatibility and convergence to meet the increasing demands imposed by applications such as big data, cloud service, machine-to-machine (M2M) and mission-critical communications. This book is a comprehensive and detailed guide to all signal processing techniques employed in 5G wireless networks. Uniquely organized into four categories, New Modulation and &n sp;Coding, New Spatial Processing, New Spectrum Opportunities and New System-level Enabling Technologies, it covers everything from network architecture...

  1. Digital Signal Processing for In-Vehicle Systems and Safety

    CERN Document Server

    Boyraz, Pinar; Takeda, Kazuya; Abut, Hüseyin

    2012-01-01

    Compiled from papers of the 4th Biennial Workshop on DSP (Digital Signal Processing) for In-Vehicle Systems and Safety this edited collection features world-class experts from diverse fields focusing on integrating smart in-vehicle systems with human factors to enhance safety in automobiles. Digital Signal Processing for In-Vehicle Systems and Safety presents new approaches on how to reduce driver inattention and prevent road accidents. The material addresses DSP technologies in adaptive automobiles, in-vehicle dialogue systems, human machine interfaces, video and audio processing, and in-vehicle speech systems. The volume also features: Recent advances in Smart-Car technology – vehicles that take into account and conform to the driver Driver-vehicle interfaces that take into account the driving task and cognitive load of the driver Best practices for In-Vehicle Corpus Development and distribution Information on multi-sensor analysis and fusion techniques for robust driver monitoring and driver recognition ...

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

    Science.gov (United States)

    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.

  3. Applying traditional signal processing techniques to social media exploitation for situational understanding

    Science.gov (United States)

    Abdelzaher, Tarek; Roy, Heather; Wang, Shiguang; Giridhar, Prasanna; Al Amin, Md. Tanvir; Bowman, Elizabeth K.; Kolodny, Michael A.

    2016-05-01

    Signal processing techniques such as filtering, detection, estimation and frequency domain analysis have long been applied to extract information from noisy sensor data. This paper describes the exploitation of these signal processing techniques to extract information from social networks, such as Twitter and Instagram. Specifically, we view social networks as noisy sensors that report events in the physical world. We then present a data processing stack for detection, localization, tracking, and veracity analysis of reported events using social network data. We show using a controlled experiment that the behavior of social sources as information relays varies dramatically depending on context. In benign contexts, there is general agreement on events, whereas in conflict scenarios, a significant amount of collective filtering is introduced by conflicted groups, creating a large data distortion. We describe signal processing techniques that mitigate such distortion, resulting in meaningful approximations of actual ground truth, given noisy reported observations. Finally, we briefly present an implementation of the aforementioned social network data processing stack in a sensor network analysis toolkit, called Apollo. Experiences with Apollo show that our techniques are successful at identifying and tracking credible events in the physical world.

  4. A computational model of human auditory signal processing and perception

    DEFF Research Database (Denmark)

    Jepsen, Morten Løve; Ewert, Stephan D.; Dau, Torsten

    2008-01-01

    A model of computational auditory signal-processing and perception that accounts for various aspects of simultaneous and nonsimultaneous masking in human listeners is presented. The model is based on the modulation filterbank model described by Dau et al. [J. Acoust. Soc. Am. 102, 2892 (1997......)] but includes major changes at the peripheral and more central stages of processing. The model contains outer- and middle-ear transformations, a nonlinear basilar-membrane processing stage, a hair-cell transduction stage, a squaring expansion, an adaptation stage, a 150-Hz lowpass modulation filter, a bandpass...

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

    Science.gov (United States)

    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.

  6. Experimental quantum key distribution with simulated ground-to-satellite photon losses and processing limitations

    Science.gov (United States)

    Bourgoin, Jean-Philippe; Gigov, Nikolay; Higgins, Brendon L.; Yan, Zhizhong; Meyer-Scott, Evan; Khandani, Amir K.; Lütkenhaus, Norbert; Jennewein, Thomas

    2015-11-01

    Quantum key distribution (QKD) has the potential to improve communications security by offering cryptographic keys whose security relies on the fundamental properties of quantum physics. The use of a trusted quantum receiver on an orbiting satellite is the most practical near-term solution to the challenge of achieving long-distance (global-scale) QKD, currently limited to a few hundred kilometers on the ground. This scenario presents unique challenges, such as high photon losses and restricted classical data transmission and processing power due to the limitations of a typical satellite platform. Here we demonstrate the feasibility of such a system by implementing a QKD protocol, with optical transmission and full post-processing, in the high-loss regime using minimized computing hardware at the receiver. Employing weak coherent pulses with decoy states, we demonstrate the production of secure key bits at up to 56.5 dB of photon loss. We further illustrate the feasibility of a satellite uplink by generating a secure key while experimentally emulating the varying losses predicted for realistic low-Earth-orbit satellite passes at 600 km altitude. With a 76 MHz source and including finite-size analysis, we extract 3374 bits of a secure key from the best pass. We also illustrate the potential benefit of combining multiple passes together: while one suboptimal "upper-quartile" pass produces no finite-sized key with our source, the combination of three such passes allows us to extract 165 bits of a secure key. Alternatively, we find that by increasing the signal rate to 300 MHz it would be possible to extract 21 570 bits of a secure finite-sized key in just a single upper-quartile pass.

  7. Analysis of Wide-Band Signals Using Wavelet Array Processing

    Science.gov (United States)

    Nisii, V.; Saccorotti, G.

    2005-12-01

    Wavelets transforms allow for precise time-frequency localization in the analysis of non-stationary signals. In wavelet analysis the trade-off between frequency bandwidth and time duration, also known as Heisenberg inequality, is by-passed using a fully scalable modulated window which solves the signal-cutting problem of Windowed Fourier Transform. We propose a new seismic array data processing procedure capable of displaying the localized spatial coherence of the signal in both the time- and frequency-domain, in turn deriving the propagation parameters of the most coherent signals crossing the array. The procedure consists in: a) Wavelet coherence analysis for each station pair of the instruments array, aimed at retrieving the frequency- and time-localisation of coherent signals. To this purpose, we use the normalised wavelet cross- power spectrum, smoothed along the time and scale domains. We calculate different coherence spectra adopting smoothing windows of increasing lengths; a final, robust estimate of the time-frequency localisation of spatially-coherent signals is eventually retrieved from the stack of the individual coherence distribution. This step allows for a quick and reliable signal discrimination: wave groups propagating across the network will manifest as high-coherence patches spanning the corresponding time-scale region. b) Once the signals have been localised in the time and frequency domain,their propagation parameters are estimated using a modified MUSIC (MUltiple SIgnal Characterization) algorithm. We select the MUSIC approach as it demonstrated superior performances in the case of low SNR signals, more plane waves contemporaneously impinging at the array and closely separated sources. The narrow-band Coherent Signal Subspace technique is applied to the complex Continuous Wavelet Transform of multichannel data for improving the singularity of the estimated cross-covariance matrix and the accuracy of the estimated signal eigenvectors. Using

  8. Analog integrated circuits design for processing physiological signals.

    Science.gov (United States)

    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.

  9. Performance Comparison of Sub Phonetic Model with Input Signal Processing

    Directory of Open Access Journals (Sweden)

    Dr E. Ramaraj

    2006-01-01

    Full Text Available The quest to arrive at a better model for signal transformation for speech has resulted in striving to develop better signal representations and algorithm. The article explores the word model which is a concatenation of state dependent senones as an alternate for phoneme. The Research Work has an objective of involving the senone with the Input signal processing an algorithm which has been tried with phoneme and has been quite successful and try to compare the performance of senone with ISP and Phoneme with ISP and supply the result analysis. The research model has taken the SPHINX IV[4] speech engine for its implementation owing to its flexibility to the new algorithm, robustness and performance consideration.

  10. A review of channel selection algorithms for EEG signal processing

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

  12. Social multimedia signals a signal processing approach to social network phenomena

    CERN Document Server

    Roy, Suman Deb

    2014-01-01

    This book provides a comprehensive coverage of the state-of-the-art in understanding media popularity and trends in online social networks through social multimedia signals. With insights from the study of popularity and sharing patterns of online media, trend spread in social media, social network analysis for multimedia and visualizing diffusion of media in online social networks. In particular, the book will address the following important issues: Understanding social network phenomena from a signal processing point of view; The existence and popularity of multimedia as shared and social me

  13. Demodulating Subsampled Direct Sequence Spread Spectrum Signals using Compressive Signal Processing

    DEFF Research Database (Denmark)

    Fyhn, Karsten; Arildsen, Thomas; Larsen, Torben

    2012-01-01

    We show that to lower the sampling rate in a spread spectrum communication system using Direct Sequence Spread Spectrum (DSSS), compressive signal processing can be applied to demodulate the received signal. This may lead to a decrease in the power consumption or the manufacturing price of wireless...... theoretical work is exemplified with a numerical experiment using the IEEE 802.15.4 standard’s 2.4GHz band specification. The numerical results support our theoretical indings and indicate that compressive sensing may be used successfully in spread spectrum communication systems. The results obtained here may...

  14. Nonlinear signal processing of electroencephalograms for automated sleep monitoring

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

  16. Biological Signal Processing with a Genetic Toggle Switch

    Science.gov (United States)

    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. PMID:23874595

  17. Sound Event Detection for Music Signals Using Gaussian Processes

    Directory of Open Access Journals (Sweden)

    Pablo A. Alvarado-Durán

    2013-11-01

    Full Text Available In this paper we present a new methodology for detecting sound events in music signals using Gaussian Processes. Our method firstly takes a time-frequency representation, i.e. the spectrogram, of the input audio signal. Secondly the spectrogram dimension is reduced translating the linear Hertz frequency scale into the logarithmic Mel frequency scale using a triangular filter bank. Finally every short-time spectrum, i.e. every Mel spectrogram column, is classified as “Event” or “Not Event” by a Gaussian Processes Classifier. We compare our method with other event detection techniques widely used. To do so, we use MATLAB® to program each technique and test them using two datasets of music with different levels of complexity. Results show that the new methodology outperforms the standard approaches, getting an improvement by about 1.66 % on the dataset one and 0.45 % on the dataset two in terms of F-measure.

  18. TOF-LIDAR signal processing using the CFAR detector

    Science.gov (United States)

    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.

  19. Signal processing for all fiber optical current transducer

    Institute of Scientific and Technical Information of China (English)

    裴焕斗; 祖静; 陈鸿

    2008-01-01

    The work principle of all fiber optical current transducer (AFOCT) was introduced. By analyzing the characteristic of photo-detector’s output, a measurement and signal processing scheme based on sine wave modulation and demodulation was put forward for eliminating the influence of light intensity change and modulation degree change. A digital signal processing system and a calibration scheme were also advanced. The experimental data show that the mean ratio error is 0.016 74% for direct current and 0.035% for alternating current, and the correlation coefficient of linearity is up to 0.999 982 4, meeting the precision requirement of 0.2 grade. Stability experiments and temperature drift experiments show the AFOCT has a better stable capability.

  20. Study of CMOS integrated signal processing circuit in capacitive sensors

    Institute of Scientific and Technical Information of China (English)

    CAO Yi-jiang; YU Xiang; WANG Lei

    2007-01-01

    A CMOS integrated signal processing circuit based on capacitance resonance principle whose structure is simple in capacitive sensors is designed. The waveform of output voltage is improved by choosing bootstrap reference current mirror with initiate circuit, CMOS analogy switch and positive feedback of double-stage inverter in the circuit. Output voltage of this circuit is a symmetric square wave signal. The variation of sensitive capacitance, which is part of the capacitive sensors, can be denoted by the change of output voltage's frequency. The whole circuit is designed with 1.5 μm P-well CMOS process and simulated by PSpice software.Output frequency varies from 261.05 kHz to 47.93 kHz if capacitance varies in the range of 1PF~15PF. And the variation of frequency can be easily detected using counter or SCU.

  1. Ultra-high-speed Optical Signal Processing using Silicon Photonics

    DEFF Research Database (Denmark)

    Oxenløwe, Leif Katsuo; Ji, Hua; Jensen, Asger Sellerup

    on silicon photonics. In particular we use nano-engineered silicon waveguides (nanowires) [1] enabling efficient phasematched four-wave mixing (FWM), cross-phase modulation (XPM) or self-phase modulation (SPM) for ultra-high-speed optical signal processing of ultra-high bit rate serial data signals. We show......— In supercomputers, the optical inter-connects are getting closer and closer to the processing cores. Today, a single supercomputer system has as many optical links as the whole worldwide web together, and it is envisaged that future computing chips will contain multiple electronic processor cores...... with a photonic layer on top to interconnect them. For such systems, silicon is an attractive candidate enabling both electronic and photonic control. For some network scenarios, it may be beneficial to use optical on-chip packet switching, and for high data-density environments one may take advantage...

  2. Advanced Signal Processing for MIMO-OFDM Receivers

    DEFF Research Database (Denmark)

    Manchón, Carles Navarro

    This thesis deals with a wide range of topics within the research area of advanced baseband receiver design for wireless communication systems. In particular, the work focuses on signal processing algorithms for receivers in multiple-input multiple-output (MIMO) orthogonal frequency-division mult......This thesis deals with a wide range of topics within the research area of advanced baseband receiver design for wireless communication systems. In particular, the work focuses on signal processing algorithms for receivers in multiple-input multiple-output (MIMO) orthogonal frequency...... contributions is the derivation of a novel message-passing scheme combining the MF and BP frameworks; the algorithm is derived from the stationary points of a region-based free energy approximation, and is guaranteed to converge if the underlying probabilistic model satisfies certain conditions. Moreover, we...

  3. Fast on-detector integrated signal processing status and perspectives

    CERN Document Server

    Lindenstruth, V

    2004-01-01

    The large and increasing channel count of modern detectors requires the use of microelectronics. The data rate and signal integrity requirements drive complex electronics to be mounted close to or directly on the detectors, possibly even integrating the complete first-level trigger stage. The latest silicon road maps indicate that the integration density of microelectronics will continue to increase during the next decade. However, there are several constraints to be taken into account that cause ramifications with respect to on- detector electronics. For instance, the core voltage will be reduced to below 500 mV, the clock rates will exceed GHz, and the power density will increase further. This article outlines two examples of trigger and readout systems, the ALICE TPC and TRD, which are completely integrated in microchips. The article expands on the expected impact future silicon processes may have on the on-detector integrated signal processing. (9 refs).

  4. Massive MIMO Systems: Signal Processing Challenges and Research Trends

    OpenAIRE

    de Lamare, R.C.

    2013-01-01

    This article presents a tutorial on multiuser multiple-antenna wireless systems with a very large number of antennas, known as massive multi-input multi-output (MIMO) systems. Signal processing challenges and future trends in the area of massive MIMO systems are presented and key application scenarios are detailed. A linear algebra approach is considered for the description of the system and data models of massive MIMO architectures. The operational requirements of massive MIMO systems are di...

  5. A Cockcroft-Walton PMT base with signal processing circuit

    CERN Document Server

    Jun, Yin; Yapeng, Zhang

    2016-01-01

    Design a surface mount 14-PIN Cockcroft-Walton photomultiplier tube base for a muon detector, which provides both high voltage power supply and signal processing. The whole system, including the detector, adopts a +5V DC power input, and features as tiny size, low power-consumption and good portability, extremely well meeting the requirements of the power supply with a battery on a mobile workstation. Detailed descriptions and test results of a prototype are presented.

  6. Synthesis of computational structures for analog signal processing

    CERN Document Server

    Popa, Cosmin Radu

    2011-01-01

    Presents the most important classes of computational structures for analog signal processing, including differential or multiplier structures, squaring or square-rooting circuits, exponential or Euclidean distance structures and active resistor circuitsIntroduces the original concept of the multifunctional circuit, an active structure that is able to implement, starting from the same circuit core, a multitude of continuous mathematical functionsCovers mathematical analysis, design and implementation of a multitude of function generator structures

  7. High Precision Signal Processing Algorithm for White Light Interferometry

    OpenAIRE

    Kim, Jeonggon Harrison

    2008-01-01

    A new signal processing algorithm for absolute temperature measurement using white light interferometry has been proposed and investigated theoretically. The proposed algorithm determines the phase delay of an interferometer with very high precision (≪ one fringe) by identifying the zero order fringe peak of cross-correlation of two fringe scans of white light interferometer. The algorithm features cross-correlation of interferometer fringe scans, hypothesis testing and fine tuning. The hypot...

  8. Digital signal processor and processing method for GPS receivers

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

  10. High Precision Signal Processing Algorithm for White Light Interferometry

    Directory of Open Access Journals (Sweden)

    Jeonggon Harrison Kim

    2008-12-01

    Full Text Available A new signal processing algorithm for absolute temperature measurement using white light interferometry has been proposed and investigated theoretically. The proposed algorithm determines the phase delay of an interferometer with very high precision (<< one fringe by identifying the zero order fringe peak of cross-correlation of two fringe scans of white light interferometer. The algorithm features cross-correlation of interferometer fringe scans, hypothesis testing and fine tuning. The hypothesis test looks for a zero order fringe peak candidate about which the cross-correlation is symmetric minimizing the uncertainty of mis-identification. Fine tuning provides the proposed algorithm with high precision subsample resolution phase delay estimation capability. The shot noise limited performance of the proposed algorithm has been analyzed using computer simulations. Root-mean-square (RMS phase error of the estimated zero order fringe peak has been calculated for the changes of three different parameters (SNR, fringe scan sample rate, coherence length of light source. Computer simulations showed that the proposed signal processing algorithm identified the zero order fringe peak with a miss rate of 3 x 10-4 at 31 dB SNR and the extrapolated miss rate at 35 dB was 3 x 10-8. Also, at 35 dB SNR, RMS phase error less than 10-3 fringe was obtained. The proposed signal processing algorithm uses a software approach that is potentially inexpensive, simple and fast.

  11. Fetal QRS extraction from abdominal recordings via model-based signal processing and intelligent signal merging.

    Science.gov (United States)

    Haghpanahi, Masoumeh; Borkholder, David A

    2014-08-01

    Noninvasive fetal ECG (fECG) monitoring has potential applications in diagnosing congenital heart diseases in a timely manner and assisting clinicians to make more appropriate decisions during labor. However, despite advances in signal processing and machine learning techniques, the analysis of fECG signals has still remained in its preliminary stages. In this work, we describe an algorithm to automatically locate QRS complexes in noninvasive fECG signals obtained from a set of four electrodes placed on the mother's abdomen. The algorithm is based on an iterative decomposition of the maternal and fetal subspaces and filtering of the maternal ECG (mECG) components from the fECG recordings. Once the maternal components are removed, a novel merging technique is applied to merge the signals and detect the fetal QRS (fQRS) complexes. The algorithm was trained and tested on the fECG datasets provided by the PhysioNet/CinC challenge 2013. The final results indicate that the algorithm is able to detect fetal peaks for a variety of signals with different morphologies and strength levels encountered in clinical practice.

  12. Artificial intelligence and signal processing for infrastructure assessment

    Science.gov (United States)

    Assaleh, Khaled; Shanableh, Tamer; Yehia, Sherif

    2015-04-01

    The Ground Penetrating Radar (GPR) is being recognized as an effective nondestructive evaluation technique to improve the inspection process. However, data interpretation and complexity of the results impose some limitations on the practicality of using this technique. This is mainly due to the need of a trained experienced person to interpret images obtained by the GPR system. In this paper, an algorithm to classify and assess the condition of infrastructures utilizing image processing and pattern recognition techniques is discussed. Features extracted form a dataset of images of defected and healthy slabs are used to train a computer vision based system while another dataset is used to evaluate the proposed algorithm. Initial results show that the proposed algorithm is able to detect the existence of defects with about 77% success rate.

  13. Image and signal processing for networked eHealth applications

    CERN Document Server

    Maglogiannis, Ilias

    2006-01-01

    E-health is closely related with networks and telecommunications when dealing with applications of collecting or transferring medical data from distant locations for performing remote medical collaborations and diagnosis. In this book we provide an overview of the fields of image and signal processing for networked and distributed e-health applications and their supporting technologies. The book is structured in 10 chapters, starting the discussion from the lower end, that of acquisition and processing of biosignals and medical images and ending in complex virtual reality systems and technique

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

    Science.gov (United States)

    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.

  15. DSPSR: Digital Signal Processing Software for Pulsar Astronomy

    CERN Document Server

    van Straten, W

    2010-01-01

    DSPSR is a high-performance, open-source, object-oriented, digital signal processing software library and application suite for use in radio pulsar astronomy. Written primarily in C++, the library implements an extensive range of modular algorithms that can optionally exploit both multiple-core processors and general-purpose graphics processing units. After over a decade of research and development, DSPSR is now stable and in widespread use in the community. This paper presents a detailed description of its functionality, justification of major design decisions, analysis of phase-coherent dispersion removal algorithms, and demonstration of performance on some contemporary microprocessor architectures.

  16. Interactions between visceral afferent signaling and stimulus processing

    Directory of Open Access Journals (Sweden)

    Hugo D Critchley

    2015-08-01

    Full Text Available Visceral afferent signals to the brain influence thoughts, feelings and behaviour. 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 behaviours, 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.

  17. The Process of Social Identity Development in Adolescent High School Choral Singers: A Grounded Theory

    Science.gov (United States)

    Parker, Elizabeth Cassidy

    2014-01-01

    The purpose of this grounded theory study was to describe the process of adolescent choral singers' social identity development within three midsized, midwestern high school mixed choirs. Forty-nine interviews were conducted with 36 different participants. Secondary data sources included memoing, observations, and interviews with the choir…

  18. Jinchuan Group Breaks Ground for a 300,000-ton Copper Deep Processing Project

    Institute of Scientific and Technical Information of China (English)

    2012-01-01

    <正>According to Jinchang Municipal Government of Gansu,on August 21,Jinchuan Group broke ground for its 400,000-ton ionic membrane caustic soda project,300,000-ton PVC project,300,000-ton copper deep processing project,

  19. Factors Affecting Christian Parents' School Choice Decision Processes: A Grounded Theory Study

    Science.gov (United States)

    Prichard, Tami G.; Swezey, James A.

    2016-01-01

    This study identifies factors affecting the decision processes for school choice by Christian parents. Grounded theory design incorporated interview transcripts, field notes, and a reflective journal to analyze themes. Comparative analysis, including open, axial, and selective coding, was used to reduce the coded statements to five code families:…

  20. Factors Affecting Christian Parents' School Choice Decision Processes: A Grounded Theory Study

    Science.gov (United States)

    Prichard, Tami G.; Swezey, James A.

    2016-01-01

    This study identifies factors affecting the decision processes for school choice by Christian parents. Grounded theory design incorporated interview transcripts, field notes, and a reflective journal to analyze themes. Comparative analysis, including open, axial, and selective coding, was used to reduce the coded statements to five code families:…

  1. A Grounded Theory of Text Revision Processes Used by Young Adolescents Who Are Deaf

    Science.gov (United States)

    Yuknis, Christina

    2014-01-01

    This study examined the revising processes used by 8 middle school students who are deaf or hard-of-hearing as they composed essays for their English classes. Using grounded theory, interviews with students and teachers in one middle school, observations of the students engaging in essay creation, and writing samples were collected for analysis.…

  2. The Process of Social Identity Development in Adolescent High School Choral Singers: A Grounded Theory

    Science.gov (United States)

    Parker, Elizabeth Cassidy

    2014-01-01

    The purpose of this grounded theory study was to describe the process of adolescent choral singers' social identity development within three midsized, midwestern high school mixed choirs. Forty-nine interviews were conducted with 36 different participants. Secondary data sources included memoing, observations, and interviews with the choir…

  3. Computer Simulation and Optimization of the Process of Thawing of Grounds Using Microwave Energy

    Science.gov (United States)

    Nekrasov, S. A.; Volkov, V. S.

    2017-01-01

    In this article, consideration is given to a mathematical model and a numerical method to calculate and optimize the process of high-speed thawing of grounds using microwave energy. Relevant examples of calculations and an analysis of results are presented.

  4. Effects of Outdoor School Ground Lessons on Students' Science Process Skills and Scientific Curiosity

    Science.gov (United States)

    Ting, Kan Lin; Siew, Nyet Moi

    2014-01-01

    The purpose of this study was to investigate the effects of outdoor school ground lessons on Year Five students' science process skills and scientific curiosity. A quasi-experimental design was employed in this study. The participants in the study were divided into two groups, one subjected to the experimental treatment, defined as…

  5. A signal processing analysis of Purkinje cells in vitro

    Directory of Open Access Journals (Sweden)

    Ze'ev R Abrams

    2010-05-01

    Full Text Available 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.

  6. Wireless receiver architectures and design antennas, RF, synthesizers, mixed signal, and digital signal processing

    CERN Document Server

    Rouphael, Tony J

    2014-01-01

    Wireless Receiver Architectures and Design presents the various designs and architectures of wireless receivers in the context of modern multi-mode and multi-standard devices. This one-stop reference and guide to designing low-cost low-power multi-mode, multi-standard receivers treats analog and digital signal processing simultaneously, with equal detail given to the chosen architecture and modulating waveform. It provides a complete understanding of the receiver's analog front end and the digital backend, and how each affects the other. The book explains the design process in great detail, s

  7. Computer Modeling and Simulation of Ultrasonic Signal Processing and Measurements

    Directory of Open Access Journals (Sweden)

    Y. B. Gandole

    2012-01-01

    Full Text Available The system for simulation, measurement, and processing in Graphical User Interface implementation is presented. The received signal from the simulation is compared to that of an actual measurement in the time domain. The comparison of simulated, experimental data clearly shows that acoustic wave propagation can be modeled. The feasibility has been demonstrated in an ultrasound transducer setup for material property investigations. The results of simulation are compared to experimental measurements. The simulation result has good agreement with the experimental data which confirms the validity of the model. The simulation tool therefore provides a way to predict the received signal before anything is built. Furthermore, the use of an ultrasonic simulation package allows for the development of the associated electronics to amplify and process the received ultrasonic signals. Such a virtual design and testing procedure not only can save us time and money, but also can provide better understanding on design failures and allow us to modify designs more efficiently and economically.

  8. Signal Processing and Data Acquisition for Wind Profiler Using Labview

    Directory of Open Access Journals (Sweden)

    Priyank V. Gandhi

    2014-04-01

    Full Text Available This paper presents the design of Wind Profiler using LabVIEW. Wind speed is a useful weather parameter to monitor and record for many applications like shipping, aviation, meteorology, construction etc. Wind observations are crucial importance for general (operational aviation meteorology, and numerical weather prediction. Wind profiler radars are vertically directed pulsed Doppler radars capable of analyzing the back-scattered signals to determine the velocity of air along the beams. Steering the beams typically 15° from zenith, the horizontal and vertical components of the air moment can be obtained. The extraction of zeroth, first and second moments is the key reason for doing all the signal processing. For measurements above 20 km, the 50 MHz frequency band can be used. The paper discusses the issues such as the principle of wind profiler radar, how wind profilers estimate the horizontal wind as a function of altitude in "clear air‟, Doppler Beam Swinging (DBS technique for Wind velocity measurement. Moment calculation and Signal processing of recoded experimental data is performed by LabVIEW code developed in my project.

  9. Research progress of the fractional Fourier transform in signal processing

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    The fractional Fourier transform is a generalization of the classical Fourier transform, which is introduced from the mathematic aspect by Namias at first and has many applications in optics quickly. Whereas its potential appears to have remained largely unknown to the signal processing community until 1990s. The fractional Fourier transform can be viewed as the chirp-basis expansion directly from its definition, but essentially it can be interpreted as a rotation in the time-frequency plane, i.e. the unified time-frequency transform. With the order from 0 increasing to 1, the fractional Fourier transform can show the characteristics of the signal changing from the time domain to the frequency domain. In this research paper, the fractional Fourier transform has been comprehensively and systematically treated from the signal processing point of view. Our aim is to provide a course from the definition to the applications of the fractional Fourier transform, especially as a reference and an introduction for researchers and interested readers.

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

    Science.gov (United States)

    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.

  11. Perspectives of using spin waves for computing and signal processing

    Energy Technology Data Exchange (ETDEWEB)

    Csaba, György, E-mail: gcsaba@gmail.com [Center for Nano Science and Technology, University of Notre Dame (United States); Faculty for Information Technology and Bionics, Pázmány Péter Catholic University (Hungary); Papp, Ádám [Center for Nano Science and Technology, University of Notre Dame (United States); Faculty for Information Technology and Bionics, Pázmány Péter Catholic University (Hungary); Porod, Wolfgang [Center for Nano Science and Technology, University of Notre Dame (United States)

    2017-05-03

    Highlights: • We give an overview of spin wave-based computing with emphasis on non-Boolean signal processors. • Spin waves can combine the best of electronics and photonics and do it in an on-chip and integrable way. • Copying successful approaches from microelectronics may not be the best way toward spin-wave based computing. • Practical devices can be constructed by minimizing the number of required magneto-electric interconnections. - Abstract: Almost all the world's information is processed and transmitted by either electric currents or photons. Now they may get a serious contender: spin-wave-based devices may just perform some information-processing tasks in a lot more efficient and practical way. In this article, we give an engineering perspective of the potential of spin-wave-based devices. After reviewing various flavors for spin-wave-based processing devices, we argue that the niche for spin-wave-based devices is low-power, compact and high-speed signal-processing devices, where most traditional electronics show poor performance.

  12. Time Reversal Signal Processing in Communications - A Feasibility Study

    Energy Technology Data Exchange (ETDEWEB)

    Meyer, A W; Candy, J V; Poggio, A J

    2002-01-30

    A typical communications channel is subjected to a variety of signal distortions, including multipath, that corrupt the information being transmitted and reduce the effective channel capacity. The mitigation of the multipath interference component is an ongoing concern for communication systems operating in complex environments such as might be experienced inside buildings, urban environments, and hilly or heavily wooded areas. Communications between mobile units and distributed sensors, so important to national security, are dependent upon flawless conveyance of information in complex environments. The reduction of this multipath corruption necessitates better channel equalization, i.e., the removal of channel distortion to extract the transmitted information. But, the current state of the art in channel equalization either requires a priori knowledge of the channel or the use of a known training sequence and adaptive filtering. If the ''assumed'' model within the equalization processor does not at least capture the dominant characteristics of the channel, then the received information may still be highly distorted and possibly useless. Also, the processing required for classical equalization is demanding in computational resources. To remedy this situation, many techniques have been investigated to replace classical equalization. Such a technique, the subject of this feasibility study, is Time Reversal Signal Processing (TRSP). Multipath is particularly insidious and a major factor in the deterioration of communication channels. Unlike most other characteristics that corrupt a communications channel, the detrimental effects of multipath cannot be overcome by merely increasing the transmitted power. Although the power in a signal diminishes as a function of the distance between the transmitter and receiver, multipath further degrades a signal by creating destructive interference that results in a loss of received power in a very localized area

  13. Predicting Protein Subcellular Location Using Digital Signal Processing

    Institute of Scientific and Technical Information of China (English)

    Yu-Xi PAN; Da-Wei LI; Yun DUAN; Zhi-Zhou ZHANG; Ming-Qing XU; Guo-Yin FENG; Lin HE

    2005-01-01

    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.

  14. Predicting protein subcellular location using digital signal processing.

    Science.gov (United States)

    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.

  15. Signal Processing Techniques Applied in RFI Mitigation of Radio Astronomy

    Directory of Open Access Journals (Sweden)

    Sixiu Wang

    2012-08-01

    Full Text Available Radio broadcast and telecommunications are present at different power levels everywhere on Earth. Radio Frequency Interference (RFI substantially limits the sensitivity of existing radio telescopes in several frequency bands and may prove to be an even greater obstacle for next generation of telescopes (or arrays to overcome. A variety of RFI detection and mitigation techniques have been developed in recent years. This study describes various signal process methods of RFI mitigation in radio astronomy, choose the method of Time-frequency domain cancellation to eliminate certain interference and effectively improve the signal to noise ratio in pulsar observations. Finally, RFI mitigation researches and implements in China radio astronomy will be also presented.

  16. A time-over-threshold technique for PMT signals processing

    Institute of Scientific and Technical Information of China (English)

    LIU Xuzong; LIU Shubin; AN Qi

    2007-01-01

    A novel front-end circuit designed for PMT signals processing considering the solution of "Time Walk"correction is discussed in this paper. We are trying to apply the TOT (Time over Threshold) technique to our research.Different from traditional ways, where amplitude is measured, time width is measured for slew correction here, which takes the advantage of TDC. Expensive fast ADCs are abandoned and the whole time measurement electronics design becomes more effective and economical. Test boards have been developed and a convenient method is introduced to evaluate our TOT technique. Results have shown that a 10ps slew correction resolution is achieved throughout the amplitude range from -108mV to -2000mV for negative signals of both 5 ns leading and trailing edge with 10 ns 50%-50% pulse width.

  17. Increased noise signal processing in incoherent radar systems

    Directory of Open Access Journals (Sweden)

    I. I. Chesanovskyi

    2013-09-01

    Full Text Available Introduction. The work is devoted to the method of increasing coherence and noise immunity pulse radar systems with incoherent sources probing signals. Problem. Incongruities between a resolution and a range of pulsed radar systems can not be resolved within the classical approaches of building incoherent radar systems, requiring new approaches in their construction. The main part. The paper presents a method of two-stage processing incoherent pulsed radar signals, allowing to compensate and use the information available to them and the angular amplitude of spurious modulation. Conclusions. Simulation results and research functions of these expressions of uncertainty indicate that use volatility as an additional transmitter modulation allows to significantly improve the resolution and robustness of the radar system.

  18. Wigner Ville Distribution in Signal Processing, using Scilab Environment

    Directory of Open Access Journals (Sweden)

    Petru Chioncel

    2011-01-01

    Full Text Available The Wigner Ville distribution offers a visual display of quantitative information about the way a signal’s energy is distributed in both, time and frequency. Through that, this distribution embodies the fundamentally concepts of the Fourier and time-domain analysis. The energy of the signal is distributed so that specific frequencies are localized in time by the group delay time and at specifics instants in time the frequency is given by the instantaneous frequency. The net positive volum of the Wigner distribution is numerically equal to the signal’s total energy. The paper shows the application of the Wigner Ville distribution, in the field of signal processing, using Scilab environment.

  19. Digital Signal Processing for Optical Coherent Communication Systems

    DEFF Research Database (Denmark)

    Zhang, Xu

    In this thesis, digital signal processing (DSP) algorithms are studied to compensate for physical layer impairments in optical fiber coherent communication systems. The physical layer impairments investigated in this thesis include optical fiber chromatic dispersion, polarization demultiplexing......, light sources frequency and phase offset and phase noise. The studied DSP algorithms are considered as key building blocks in digital coherent receivers for the next generation of optical communication systems such as 112-Gb/s dual polarization (DP) quadrature phase shift keying (QPSK) optical...... spectrum narrowing tolerance 112-Gb/s DP-QPSK optical coherent systems using digital adaptive equalizer. The demonstrated results show that off-line DSP algorithms are able to reduce the bit error rate (BER) penalty induced by signal spectrum narrowing. Third, we also investigate bi...

  20. Approaches to Chemical and Biochemical Information and Signal Processing

    Science.gov (United States)

    Privman, Vladimir

    2012-02-01

    We outline models and approaches for error control required to prevent buildup of noise when ``gates'' and other ``network elements'' based on (bio)chemical reaction processes are utilized to realize stable, scalable networks for information and signal processing. We also survey challenges and possible future research. [4pt] [1] Control of Noise in Chemical and Biochemical Information Processing, V. Privman, Israel J. Chem. 51, 118-131 (2010).[0pt] [2] Biochemical Filter with Sigmoidal Response: Increasing the Complexity of Biomolecular Logic, V. Privman, J. Halamek, M. A. Arugula, D. Melnikov, V. Bocharova and E. Katz, J. Phys. Chem. B 114, 14103-14109 (2010).[0pt] [3] Towards Biosensing Strategies Based on Biochemical Logic Systems, E. Katz, V. Privman and J. Wang, in: Proc. Conf. ICQNM 2010 (IEEE Comp. Soc. Conf. Publ. Serv., Los Alamitos, California, 2010), pages 1-9.

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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.

  3. Enhancement of MS Signal Processing For Improved Cancer Biomarker Discovery

    Science.gov (United States)

    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.

  4. The SIMCA algorithm for processing Ground Penetrating Radar data and its use in landmine detection

    OpenAIRE

    Sengodan, A.; Cockshott, W. P.

    2012-01-01

    The main challenge of ground penetrating radar (GPR)\\ud based land mine detection is to have an accurate image\\ud analysis method that is capable of reducing false alarms.\\ud However an accurate image relies on having sufficient spatial\\ud resolution in the received signal. But because the diameter\\ud of an AP mine can be as low as 2cm and many soils\\ud have very high attenuations at frequencies above 3GHz,\\ud the accurate detection of landmines is accomplished using\\ud advanced algorithms. U...

  5. Photonics for microwave systems and ultra-wideband signal processing

    Science.gov (United States)

    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.

  6. DSPSR: Digital Signal Processing Software for Pulsar Astronomy

    Science.gov (United States)

    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.

  7. Digital signal processing in power electronics control circuits

    CERN Document Server

    Sozanski, Krzysztof

    2013-01-01

    Many digital control circuits in current literature are described using analog transmittance. This may not always be acceptable, especially if the sampling frequency and power transistor switching frequencies are close to the band of interest. Therefore, a digital circuit is considered as a digital controller rather than an analog circuit. This helps to avoid errors and instability in high frequency components. Digital Signal Processing in Power Electronics Control Circuits covers problems concerning the design and realization of digital control algorithms for power electronics circuits using

  8. Music Signal Processing Using Vector Product Neural Networks

    Science.gov (United States)

    Fan, Z. C.; Chan, T. S.; Yang, Y. H.; Jang, J. S. R.

    2017-05-01

    We propose a novel neural network model for music signal processing using vector product neurons and dimensionality transformations. Here, the inputs are first mapped from real values into three-dimensional vectors then fed into a three-dimensional vector product neural network where the inputs, outputs, and weights are all three-dimensional values. Next, the final outputs are mapped back to the reals. Two methods for dimensionality transformation are proposed, one via context windows and the other via spectral coloring. Experimental results on the iKala dataset for blind singing voice separation confirm the efficacy of our model.

  9. Computational information geometry for image and signal processing

    CERN Document Server

    Critchley, Frank; Dodson, Christopher

    2017-01-01

    This book focuses on the application and development of information geometric methods in the analysis, classification and retrieval of images and signals. It provides introductory chapters to help those new to information geometry and applies the theory to several applications. This area has developed rapidly over recent years, propelled by the major theoretical developments in information geometry, efficient data and image acquisition and the desire to process and interpret large databases of digital information. The book addresses both the transfer of methodology to practitioners involved in database analysis and in its efficient computational implementation.

  10. Some recent work on lattice structures for digital signal processing

    Indian Academy of Sciences (India)

    S C Dutta Roy

    2014-12-01

    This paper is concerned with a review of some recent work on derivation and synthesis of lattice structures for digital signal processing (DSP). In particular, synthesis of canonical structures for both finite impulse response (FIR) and infinite impulse response (IIR) transfer functions is presented in detail. This has been an outstanding problem in DSP, and I demonstrate here how the solution came through very simple ideas and reasoning. Besides a consolidation of results published earlier in various papers, some new results containing refinements and simplifications in the synthesis procedures have also been presented.

  11. Modeling, estimation and optimal filtration in signal processing

    CERN Document Server

    Najim, Mohamed

    2010-01-01

    The purpose of this book is to provide graduate students and practitioners with traditional methods and more recent results for model-based approaches in signal processing.Firstly, discrete-time linear models such as AR, MA and ARMA models, their properties and their limitations are introduced. In addition, sinusoidal models are addressed.Secondly, estimation approaches based on least squares methods and instrumental variable techniques are presented.Finally, the book deals with optimal filters, i.e. Wiener and Kalman filtering, and adaptive filters such as the RLS, the LMS and the

  12. Social signal processing for studying parent–infant interaction

    Science.gov (United States)

    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

  13. Social signal processing for studying parent-infant interaction.

    Science.gov (United States)

    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.

  14. Detection of shallow buried objects using an autoregressive model on the ground penetrating radar signal

    Science.gov (United States)

    Nabelek, Daniel P.; Ho, K. C.

    2013-06-01

    The detection of shallow buried low-metal content objects using ground penetrating radar (GPR) is a challenging task. This is because these targets are right underneath the ground and the ground bounce reflection interferes with their detections. They do not create distinctive hyperbolic signatures as required by most existing GPR detection algorithms due to their special geometric shapes and low metal content. This paper proposes the use of the Autoregressive (AR) modeling method for the detection of these targets. We fit an A-scan of the GPR data to an AR model. It is found that the fitting error will be small when such a target is present and large when it is absent. The ratio of the energy in an Ascan before and after AR model fitting is used as the confidence value for detection. We also apply AR model fitting over scans and utilize the fitting residual energies over several scans to form a feature vector for improving the detections. Using the data collected from a government test site, the proposed method can improve the detection of this kind of targets by 30% compared to the pre-screener, at a false alarm rate of 0.002/m2.

  15. The Accuratre Signal Model and Imaging Processing in Geosynchronous SAR

    Science.gov (United States)

    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

  16. The positive side of a negative reference: the delay between linguistic processing and common ground

    Science.gov (United States)

    Noveck, Ira; Rivera, Natalia; Jaume-Guazzini, Francisco

    2017-01-01

    Interlocutors converge on names to refer to entities. For example, a speaker might refer to a novel looking object as the jellyfish and, once identified, the listener will too. The hypothesized mechanism behind such referential precedents is a subject of debate. The common ground view claims that listeners register the object as well as the identity of the speaker who coined the label. The linguistic view claims that, once established, precedents are treated by listeners like any other linguistic unit, i.e. without needing to keep track of the speaker. To test predictions from each account, we used visual-world eyetracking, which allows observations in real time, during a standard referential communication task. Participants had to select objects based on instructions from two speakers. In the critical condition, listeners sought an object with a negative reference such as not the jellyfish. We aimed to determine the extent to which listeners rely on the linguistic input, common ground or both. We found that initial interpretations were based on linguistic processing only and that common ground considerations do emerge but only after 1000 ms. Our findings support the idea that—at least temporally—linguistic processing can be isolated from common ground.

  17. TOPICAL REVIEW: A survey of signal processing algorithms in brain computer interfaces based on electrical brain signals

    Science.gov (United States)

    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?

  18. Tunable photonic filters: a digital signal processing design approach.

    Science.gov (United States)

    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.

  19. Signal processing method for shear wave velocity measurement

    Institute of Scientific and Technical Information of China (English)

    Hou Xingmin; Qu Shuying; Shi Xiangdong

    2007-01-01

    Soil shear wave velocity (SWV) is an important parameter in geotechnical engineering. To measure the soil SWV, three methods are generally used in China, including the single-hole method, cross-hole method and the surface-wave technique. An optimized approach based on a correlation function for single-hole SWV measurement is presented in this paper. In this approach, inherent inconsistencies of the artificial methods such as negative velocities, and too-large and too-small velocities, are eliminated from the single-hole method, and the efficiency of data processing is improved. In addition, verification using the cross-hole method of upper measuring points shows that the proposed optimized approach yields high precision in signal processing.

  20. Revised ground-water monitoring compliance plan for the 300 area process trenches

    Energy Technology Data Exchange (ETDEWEB)

    Schalla, R.; Aaberg, R.L.; Bates, D.J.; Carlile, J.V.M.; Freshley, M.D.; Liikala, T.L.; Mitchell, P.J.; Olsen, K.B.; Rieger, J.T.

    1988-09-01

    This document contains ground-water monitoring plans for process-water disposal trenches located on the Hanford Site. These trenches, designated the 300 Area Process Trenches, have been used since 1973 for disposal of water that contains small quantities of both chemicals and radionuclides. The ground-water monitoring plans contained herein represent revision and expansion of an effort initiated in June 1985. At that time, a facility-specific monitoring program was implemented at the 300 Area Process Trenches as part of a regulatory compliance effort for hazardous chemicals being conducted on the Hanford Site. This monitoring program was based on the ground-water monitoring requirements for interim-status facilities, which are those facilities that do not yet have final permits, but are authorized to continue interim operations while engaged in the permitting process. The applicable monitoring requirements are described in the Resource Conservation and Recovery Act (RCRA), 40 CFR 265.90 of the federal regulations, and in WAC 173-303-400 of Washington State's regulations (Washington State Department of Ecology 1986). The program implemented for the process trenches was designed to be an alternate program, which is required instead of the standard detection program when a facility is known or suspected to have contaminated the ground water in the uppermost aquifer. The plans for the program, contained in a document prepared by the US Department of Energy (USDOE) in 1985, called for monthly sampling of 14 of the 37 existing monitoring wells at the 300 Area plus the installation and sampling of 2 new wells. 27 refs., 25 figs., 15 tabs.