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

作者： A. Dinc Y. Bar-Ness Center for Communication and Signal Processing Research Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ USA

A fast multidimensional adaptive algorithm, Bootstrap, is proposed for multiple signal separation. It separates multiple uncorrelated signals imposed on each other. The bootstrap adaptive algorithm, which does not require training sequences, uses an optimization criteria that is based on minimization of output signal correlations. The learning process of this algorithm is compared with that of the least mean square (LMS) algorithm for different eigenvalue spreads. It has been found from computer simulations that the Bootstrap algorithm converges much faster than the LMS algorithm. The learning process of the Bootstrap algorithm is almost independent of eigenvalue spread.< >

关键词： Particle separators signal processing algorithms Least squares approximation Convergence Interference Multidimensional systems Adaptive signal processing Multidimensional signal processing Adaptive algorithm Source separation

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Recursive-in-order least squares parameter estimation for 2D Gaussian Markov random field model

Recursive-in-order least squares parameter estimation for 2D...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： C.R. Zou Z.Y. He E.I. Plotkin M.N.S. Swamy Center for Signal Processing and Communications Concordia University Montreal QUE Canada Division of Digital Signal Processing South-East University Nanjing China Department of Radio Engineering South-East University Nanjing China Department of Electrical and Computer Engineering Concordia University Montreal QUE Canada

Presents two recursive-in-order least squares algorithms for parameter estimation of 2D Gaussian Markov random field (GMRF) models. Algorithm I implements the recursive computation by introducing auxiliary variables without changing the structure of the model, while algorithm II realizes the recursive computation by replacing the noncausal symmetric GMRF model by an equivalent causal nonsymmetric model. The concept of recursive path, which is used to increase the speed of computation of the model parameters and accomplish the choice of the optimal model support, is proposed. The computational complexity of both algorithms is O(M/sup 2/m) multiplications per order, where m is the total number of parameters and M/sup 2/ is the size of a sample image.< >

关键词： Least squares approximation Parameter estimation Markov random fields signal processing algorithms Finite impulse response filter Maximum likelihood estimation Filtering algorithms Radio frequency Image edge detection Image segmentation

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An improved increase policy for dynamic window flow control

An improved increase policy for dynamic window flow control

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IEEE Southeastcon

作者： K.J. Christensen A.A. Nilsson LAN System Performance and Analysis IBM Corporation NC USA Center of Communications and Signal Processing Department of Electrical and Computer Engineering North Carolina state university Raleigh NC USA

Dynamic window flow control is an extension to sliding window flow control. An improved increase policy for dynamic window flow control is developed and evaluated. The improved increase policy is named the jump policy for its ability to jump to a possibly optimum window size. The jump policy has a varying increase rate that is a function of the last window size at which a frame loss occurred. Over a variety of configurations, the jump policy yields a higher effective throughout when compared to existing linear and parabolic increase policies. A simulation study to validate the improvement of the jump policy is described.< >

关键词： Communication system control Size control ISDN Frame relay LAN interconnection Local area networks Throughput Communication networks Propagation losses Buffer overflow

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Convergence analysis for the extended-Kalman-filter based algorithm of target tracking and identification

Convergence analysis for the extended-Kalman-filter based al...

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Asilomar Conference on signals, Systems & computers

作者： D.S. Cheng A.R. Stubberud Center for High-speed Image/Signal Processing (CHIP) Department of Electrical and Computer Engineering University of California Irvine Irvine CA USA

The joint problem of target tracking and identification was discussed previously by the authors (1991), and a tracking/identification algorithm using an extended-Kalman-filter-based associative memory (EK-FAM) was demonstrated through several examples. The convergence properties of the algorithm are discussed. Under the appropriate conditions, a contraction operator can be developed, using Banach space concepts that guarantee convergence of the algorithm.< >

关键词： Convergence Algorithm design and analysis Target tracking signal processing algorithms Associative memory Functional analysis Vectors Eigenvalues and eigenfunctions Virtual manufacturing Jacobian matrices

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Target Tracking and Identification using Neural Networks and Associative Memories

Target Tracking and Identification using Neural Networks and...

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IJCNN International Joint Conference on Neural Networks

作者： Dan S.Cheng Allen R.Stubberud Center for High-Speed Image/Signal Processing（CHIP） Department of Electrical and Computer Engineering University of California Irvine IrvineCA 92717

＜正＞The joint problem of tracking and identification of a target from an airplane was discussed in[1].In this paper the problem is discussed using a different system structure which uses a neural *** assume that a set of targets are distinguishable where indistinguishability between any two targets implies that their feature vectors are *** associative memory,which is implemented with an artificial neural network in a feedback loop,is developed as an *** the associative memory is presented with a feature vector it recalls the corresponding *** mathematical concepts in Hilbert space show that perfect identification is possible by using such an identifier in the noise free *** estimate is used to identify correct targets when targets are subject to certain conditions of noise corruption of the feature *** can combine this identifier with a modified extended Kalman filter to solve the combined target tracking and identification *** result of this technique is promising,and fast identification is *** demonstrate this technique through an example.

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Adaptive stack filtering by LMS and perceptron learning

Adaptive stack filtering by LMS and perceptron learning

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

作者： N. Ansari Y. Huang J.-H. Lin Center for Communication and Signal Processing Research Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ USA Department of Electrical Engineering University of Delaware Newark DE USA

Stack filters are a class of sliding-window nonlinear digital filters that possess the weak superposition property (threshold decomposition) and the ordering property known as the stacking property. They have been demonstrated to be robust in suppressing noise. Two methods are introduced to adaptively configure a stack filter. One is by employing the least mean square (LMS) algorithm and the other is based on perceptron learning. Experimental results are presented to demonstrate the effectiveness of the methods for noise suppression.< >

关键词： Adaptive filters Filtering Least squares approximation Nonlinear filters Boolean functions Stacking Digital filters Noise robustness Additive noise Binary sequences

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On generalized adaptive neural filters

On generalized adaptive neural filters

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International Joint Conference on Neural Networks (IJCNN)

作者： Z.Z. Zhang N. Ansari J.-H. Lin Center for Communication and Signal Processing Research Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ USA Department of Electrical Engineering University of Delaware Newark DE USA

The generalized adaptive neural filter (GANF), a new class of nonlinear filters, is introduced. It is effective for non-Gaussian noise suppression. Some properties of GANF are derived, and an algorithm for finding the optimal GANF, based on the upper bound in the minimum absolute error, is proposed. The implementation of the optimal GANF by using the least mean square error and the least perceptron error is also discussed. Experimental results are presented to demonstrate the effectiveness of the new filter.< >

关键词： Adaptive filters Upper bound Nonlinear filters signal processing algorithms Error correction Stacking Adaptive signal processing Digital signal processing Process design signal design

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A parallel router architecture for high speed LAN internetworking

A parallel router architecture for high speed LAN internetwo...

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Conference on Local computer Networks (LCN)

作者： P. Marimuthu I. Viniotis T.L. Sheu Center for Communication and Signal Processing Department t of Electrical and Computer Engineering North Carolina State University Raleigh NC USA Networking Systems IBM Corporation NC USA

A parallel router architecture for processing network-layer protocols at FDDI (fiber distributed data interface) speeds is proposed. At high speeds the computing power of existing routers becomes the performance bottleneck (for processing small frame sizes). Hence, a completely different approach is required in designing a router. The opportunities of parallel processing in a network protocol are investigated. Several levels of parallel processing are considered, and an architecture for the most practical and feasible approach is proposed. The concept of a snoopy header cache is introduced. Algorithms for reducing the mean processing delay by balancing the load among the processors are discussed. The performance of the router is evaluated by analytic methods and is compared with simulation results. The results from both the analytic model and the simulator reinforce the choice of a header cache in a multiprocessor environment.< >

关键词： Local area networks Internetworking computer architecture Protocols FDDI Parallel processing Analytical models High performance computing Delay Performance analysis

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A new approach for evaluating the performance of a symbol timing recovery system employing a general type of nonlinearity

A new approach for evaluating the performance of a symbol ti...

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IEEE International Conference on communications (ICC)

作者： E.Y. Bar-Ness E. Panayirci Center for Communication and Signal Processing Research Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ USA Dept. of Electr. & Comput. Eng. New Jersey Inst. of Technol. Newark NJ USA

A new technique is presented for evaluating the jitter performance of a symbol timing recovery (STR) subsystem for binary synchronous data transmission systems. The STR system consists of any even-symmetric zero-memory nonlinear device followed by a narrowband filter tuned to the pulse repetition frequency. The exact analytical expressions are derived for the mean and the mean-squared values of the timing wave, based on the high-order moments of the input signal. The root-mean-square jitter performance is then computed as a function of various system parameters such as the power series expansion of the zero-memory nonlinear device, prefiltering, and postfiltering. The numerical results obtained from some specific examples serve to illustrate several aspects of the timing recovery problem.< >

关键词： Timing Jitter Clocks Narrowband Circuits Bandwidth Data communication Baseband Band pass filters Frequency

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ADAPTIVE EQUALIZATION FOR TDMA DIGITAL MOBILE RADIO

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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 1991年第2期40卷 333-341页

作者： PROAKIS, JG Department of Electrical and Computer Engineering Communications and Digital Signal Processing Research Center Northeastern University Boston MA USA

Adaptive equalization for a time division multiple access (TDMA) digital cellular system is treated in this paper. First, a survey of adaptive equalization techniques is presented, including their performance characteristics and limitations, and their implementation complexity. Then, the design of adaptive equalization algorithms for a narrow-band TDMA system is considered.

关键词： Adaptive equalizers Time division multiple access Land mobile radio Resonance light scattering signal processing algorithms Least squares approximation Finite impulse response filter Algorithm design and analysis Narrowband Telephony

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