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Externally controlled time-varying constrained notch filter

Externally controlled time-varying constrained notch filter

引用

IEEE International Symposium on Circuits and Systems (ISCAS)

作者： D. Wulich E.I. Plotkin M.N.S. Swamy W. Tong Center of Signal Processing and Communications Department of Electrical and Computer Engineering Concordia University Montreal QUE Canada Department of ECE Ben-Gurion University of the Negev Beersheba Israel

An application of a constrained notch filter (CNF) for filtering a sine signal with arbitrary varying frequency is considered. It is shown that the concept of CNF can be easily extended to time-varying CNF (TVCNF) whose coefficients vary with time according to the rule of frequency variation of the considered FM signal. Such a TVCNF is able to reject the FM signal and at the same time remain transparent to any other signal. The main problem in TVCNF implementation is to provide a proper control (synchronization) of its coefficients. An application of the TVCNF for the enhancement of an arbitrary signal corrupted by a strong FM interference is investigated. It is shown that if the synchronization is based on the input mixture, then for any negative signal-to-interference ratio (SIR<<0 dB) at the input of the TVCNF, the SIR at its output reaches 0 dB.< >

关键词： Frequency modulation Interference Frequency synchronization Adaptive filters Background noise Communication system control signal processing Application software Filtering signal design

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Closed-loop self-synchronized signal controlled constrained notch filter with application for rejection of arbitrary frequency variation speed sinusoidal interference

Closed-loop self-synchronized signal controlled constrained ...

引用

IEEE International Symposium on Circuits and Systems (ISCAS)

作者： W. Tong E.I. Plotkin M.N.S. Swamy D. Wulich Center of Signal Processing and Communications Department of Electrical and Computer Engineering Concordia University Montreal QUE Canada Department of ECE Ben-Gurion University of the Negev Beersheba Israel

The closed-loop self-synchronized constrained notch filter (CLSS-CNF) is proposed, and its ability for retrieval of narrowband signals corrupted by a strong FM interference is studied. Self-synchronization is achieved through the estimation of the instantaneous phase of the FM interference to control time-varying coefficients of SC-CNF by using a closed-loop structure. The CLSS-CNF can overcome the tracking capability threshold of a conventional constrained adaptive notch filter (CANF), and reject a sinusoidal interference with arbitrary speed of frequency variation. Based on this approach, two such filters are discussed, and their system performances compared. It is shown that the proposed filters are superior to both the conventional CANF as well as the recently proposed SC-CNF with open loop structure. Use of closed loop and the specially developed projection scheme for time-varying coefficients allow one to achieve a signal to the interference ratio (SIR/sub O/) of up to 20 dB compared to the input SIR/sub i/ of less than -20 dB.< >

关键词： Interference constraints Phase estimation Frequency synchronization Phase locked loops Adaptive filters Communication system control Application software signal processing algorithms Open loop systems Time varying systems

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Nonlinear adaptive filtering of systems with hysteresis by quantized mean field annealing

Nonlinear adaptive filtering of systems with hysteresis by q...

引用

IEEE Workshop on Neural Networks for signal processing

作者： R.A. Nobakht S.H. Ardalan D.E. Van den Bout International Business Machines Corporation NC USA Center of Communications and Signal Processing Department of Electrical and Computer Engineering North Carolina State University Raleigh NC USA

A technique for nonlinear adaptive filtering of systems with hysteresis has been developed which combines quantized mean field annealing (QMFA) and conventional RLS/FTF adaptive filtering. Hysteresis is modeled as a nonlinear system with memory. Unlike other methods which rely on Volterra and Wiener models, this technique can efficiently handle large order nonlinearities with or without hysteresis effects. The nonlinear channel is divided into a memory nonlinearity followed by a dispersive linear system. Assuming that the dispersive linear system is stationary during initialization, and the nonlinearity does not change while the dispersive linear system varies with time, QMFA is applied to obtain the coefficients and the order of the memory of the nonlinearity and RLS/FTF is applied to determine the weights of the dispersive linear system. Application of this method to a full duplex digital subscriber loop is made. Simulations show the superior performance of our technique compared to that of ordinary RLS/FTF and steepest-descent algorithms.< >

关键词： Adaptive filters Hysteresis Dispersion Linear systems Resonance light scattering Nonlinear systems Neural networks Simulated annealing Least squares approximation Adaptive signal processing

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Performance analysis of reservation random access protocols for cellular packet communications

Performance analysis of reservation random access protocols ...

引用

IEEE Global Telecommunications Conference GLOBECOM '91: Countdown to the New Millennium. Conference Record

作者： S. Jangi L. Merakos Electrical and Computer Engineering Department Communications and Digital Signal Processing Research Center Northeastern University Boston MA USA Hughes Network Systems Germantown MD USA

An analysis method for evaluating the performance of a class of RRA (reservation random access) protocols is developed. The method is based on a Markovian model whose stationary solution is obtained via an iterative computational procedure based on matrix decomposition techniques. Subject to a maximum delay constraint, the steady state probability of voice packet dropping is evaluated for three RRA protocol examples and comparisons are made with the performance of an ideal hypothetical multiplexer. Suggestions for the design of integrated voice/data RRA protocols are made. The transient performance of RRA protocols is evaluated.< >

关键词： Performance analysis Access protocols Delay Speech Base stations Time division multiple access Digital signal processing Data engineering Iterative methods Matrix decomposition

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Exact noise analysis of 'ideal' SC networks

Exact noise analysis of 'ideal' SC networks

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： L. Toth K. Suyama Department of Signal Processing and Computer Science Research Institute of Telecommunication (TKI) Budapest Hungary Department of Electrical Engineering and Center of Telecommunications Research Columbia University New York NY USA

An exact analytical method is presented for computing noise generated in switched capacitor networks (SCNs) including the effects due to frequency-dependent low-frequency (i.e. 1/f noise) as well as broadband noise sources. The low-frequency noise source is modeled by the square of the magnitude of a rational function. A lossy SCN containing finite ON-resistances associated with MOS switches exhibits a well-defined output noise even when a limit-value computation is used to force the resistances to zero. The limit-value computation technique to determine this remaining average power spectral density takes advantage of the complete-charge-transfer assumption fully, and thus leads to an efficient noise analysis. The technique avoids the computation of eigenvalues or matrix exponentials even though the ON-resistors must be formulated.< >

关键词： Low-frequency noise 1f noise Circuit noise Noise shaping Noise generators Frequency Switches signal processing Switched capacitor networks Active noise reduction

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Adaptive equalization using multirate filtering techniques

Adaptive equalization using multirate filtering techniques

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Asilomar Conference on signals, Systems & computers

作者： J.J. Shynk D.P. Witmer M.J. Ready R.P. Gooch C.K. Chan Center for Information Processing Research Department of Electrical and Computer Engineering University of California Santa Barbara CA USA Applied Signal Technology Inc. Sunnyvale CA USA

The authors present a computationally efficient blind equalization architecture that is based on multirate and subband adaptive filtering techniques. The received signal is first partitioned by a filter bank into a set of narrowband frequency bins that are approximately nonoverlapping. The adaptive processing is then performed at a lower sampling rate, thus achieving a considerable savings in complexity. Furthermore, the signal power in each frequency bin is normalized to obtain a more uniform convergence rate across the adaptive filter coefficients. The overall convergence rate of the filter is thus dramatically improved compared to that of conventional time- and frequency-domain implementations. computer simulations of this filter bank equalizer in a multipath environment are presented to illustrate its transient and steady-state convergence properties.< >

关键词： Adaptive equalizers Adaptive filters Filtering Filter bank Convergence Frequency Blind equalizers computer architecture Narrowband signal sampling

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Real-time high-ratio image compression using adaptive VLSI neuroprocessors

Real-time high-ratio image compression using adaptive VLSI n...

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International Conference on Acoustics, Speech, and signal processing (ICASSP)

作者： B.J. Sheu W.-C. Fang Department of Electrical Engineering Signal and Image Processing Institute University of Southern California Los Angeles CA USA Jet Propulsion Laboratory Advanced Computer Systems and Technology Section California Institute of Technology Pasadena CA USA

An adaptive VLSI neuroprocessor based on vector quantization algorithm has been developed for real-time high-ratio image compression applications. This VLSI neural-network-based vector quantization (NNVQ) module combines a fully parallel vector quantizer with a pipelined codebook generator for a broad area of data compression applications. The NNVQ module is capable of producing good-quality reconstructed data at high compression ratios more than 20. The vector quantizer chip has been designed, fabricated, and tested. It contains 64 inner-product neural units and a high-speed extendable winner-take-all block. This mixed-signal chip occupies a compact silicon area of 4.6*6.8 mm/sup 2/ in a 2.0- mu m scalable CMOS technology. The throughput rate of the 2- mu m NNVQ module is 2 million vectors per second and its equivalent computation power is 3.33 billion connections per second.< >

关键词： Image coding Very large scale integration Vector quantization Neural networks Data compression High performance computing Clustering algorithms Application software Image reconstruction CMOS technology

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Convergence behavior and convergence rates of stack filters

Convergence behavior and convergence rates of stack filters

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： M. Gabbouj P.-T. Yu E.J. Coyle Signal Processing Laboratory Tampere University of Technology Tampere Finland Institute of Computer Science and Information Engineering National Chung Cheng University Chiayi Taiwan School of Electrical Engineering Purdue University West Lafayette IN USA

The convergence behavior of type-0 through type-3 stack filters is investigated. It is shown that stack filters of type-0 through type-2 all possess the convergence property; that is, they filter any input signal to a root after consecutive passes of the filter under any appending strategy. A counterexample is given to show that not all type-3 stack filters have this convergence property. The rate of convergence for convergent stack filters is also shown. It is shown that stack filters of type-0 will take at most a single pass to filter any input signal to a root. The rate of convergence of type-1 and type-2 stack filters is shown to be linear in the length of the input signal.< >

关键词： Convergence Filters Boolean functions signal processing Laboratories computer science Shape Filtering theory Design methodology signal design

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A real-time VLSI neuroprocessor for adaptive image compression based upon frequency-sensitive competitive learning

A real-time VLSI neuroprocessor for adaptive image compressi...

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International Joint Conference on Neural Networks (IJCNN)

作者： W.-C. Fang B.J. Sheu O.T.-C. Chen Jet Propulsion Laboratory Advanced Computer Systems and Technology Section California Institute of Technology Pasadena CA USA Department of Electrical Engineering Signal and Image Processing Institute University of Southern California Los Angeles CA USA

The frequency-sensitive competitive learning (FSCL) algorithm and its associated VLSI neuroprocessor have been developed for adaptive vector quantisation (AVQ). Simulation results show that the FSCL algorithm is capable of producing a good-quality codebook for AVQ at high compression ratios of more than 20 in real time. This VLSI neural-network-based vector quantization design includes a fully parallel vector quantizer and a pipelined codebook generator to provide an effective data compression scheme. It provides a computing capability as high as 3.33 billion connections per second. Its performance can achieve a speedup of 750 compared with SUN-3/60 and a compression ratio of 33 at a signal-to-noise ratio of 23.81 dB.< >

关键词： Very large scale integration Image coding Frequency Neural networks Power capacitors Vector quantization CMOS technology Image reconstruction Speech coding Data compression

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Model Based Segmenatation of Synthetic Aperture Radar Data

Model Based Segmenatation of Synthetic Aperture Radar Data

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Multidimensional signal processing Workshop

作者： E. Rignot R. Chellappa Jet Propulsion Laboratory California Institute of Technology Pasadena CA USA Signal and Image Processing Institute Department of Electrical Engineering-Systems University of Southern California Los Angeles CA

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