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OPTIMAL SYSTOLIC DESIGN FOR THE TRANSITIVE CLOSURE AND THE SHORTEST-PATH PROBLEMS

IEEE TRANSACTIONS ON COMPUTERS 1987年第5期36卷 603-614页

作者： KUNG, SY LO, SC LEWIS, PS Signal and Image Processing Institute Department of Electrical Engineering University of Southern California

Due to VLSI technological progress, algorithm- oriented array architectures, such as systolic arrays, appear to be very effective, feasible, and economic. This paper discusses how to design systolic arrays for the transitive closure and the shortest path problems. We shall focus on the Warshall algorithm for the transitive closure problem and the Floyd algorithm for the shortest path problem. These two algorithms share exactly the same structural formulation; therefore, they lead to the same systolic array design. In this paper, we first present a general method for mapping algorithms to systolic arrays. Using this methodology, two new systolic designs for the Warshall-Floyd algorithm will be derived. The first one is a spiral array, which is easy to derive and can be further simplified to a hexagonal array. The other is an orthogonal systolic array which is optimal in terms of pipelining rate, block pipelining rate, and the number of input/output connections.

关键词： VLSI Architectures Algorithm Mappings Optimal Algorithms Shortest Path Problem Systolic Arrays Transitive Closure Problems VLSI Algorithms

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COMMON PITFALLS IN THE APPLICATION OF STATIONARY PROCESS THEORY TO TIME-SAMPLED AND MODULATED signalS

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IEEE TRANSACTIONS ON COMMUNICATIONS 1987年第5期35卷 529-534页

作者： GARDNER, WA Signal and Image Processing Lab Signal and Image Processing Lab Department of Electrical and Computer Engineering University of California Davis CA USA

The common practice of applying the theory of stationary stochastic processes to a cyclostationary process by introducing random phase(s) into the probabilistic model in order to stationarize the process can lead to erroneous results, such as incorrect formulas for power spectral density. This is illustrated by showing that commonly used formulas for signals that have undergone frequency conversion or time sampling can be incorrect. The source of error is shown to be inappropriate phase-randomization procedures. The correct procedure is described, and corrected formulas are given. The problem is further illustrated by showing that commonly used resolution and reliability (mean and variance) formulas for spectrum analyzers must be corrected for cyclostationary signals. It is explained that all corrections to formulas reflect the effects of spectral correlation. These effects are inappropriately averaged out by inappropriate phase-randomization procedures. It is further explained that these inappropriate procedures destroy the important property of ergodicity of the probabilistic model.

关键词： signal processing Stochastic processes Phase modulation Frequency conversion signal sampling Spectral analysis Pulse modulation signal resolution Analytical models

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A NEW ALGORITHM FOR ADAPTIVE ARRAYS

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IEEE TRANSACTIONS ON ACOUSTICS SPEECH AND signal processing 1987年第9期35卷 1314-1319页

作者： GARDNER, WA BROWN, WA Signal and Image Processing Laboratory Department of Electrical and Computer Engineering University of California슠Davis Davis CA USA Signal and Image Processing Laboratory Department of Electrical and Computer Engineering University of California Davis Davis CA USA

A new deflected stochastic-gradient algorithm for adaptive sensor arrays is introduced. It is shown to have the capability of converging substantially faster than the nondeflected stochastic gradient (LMS) algorithm but slower than the recursive least squares (RLS) algorithm. Because of its amenability to reduction of computational complexity by data quantization, it has the potential for processing digital signals with bandwidths one to two orders of magnitude larger than the bandwidths manageable with the RLS algorithm for sensor arrays containing a number of adjustable weights in the approximate range of 10-50.

关键词： Adaptive arrays Sensor arrays Least squares approximation Resonance light scattering Bandwidth Stochastic processes Least squares methods Computational complexity Quantization signal processing

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SPECTRAL CORRELATION OF MODULATED signalS .2. DIGITAL MODULATION

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IEEE TRANSACTIONS ON COMMUNICATIONS 1987年第6期35卷 595-601页

作者： GARDNER, WA BROWN, WA CHEN, CK Signal and Image Processing Laboratory Department of Electrical and Computer Engineering University of California Davis CA USA

As a continuation of Part I, the spectral correlation function is presented for a variety of types of digitally modulated signals. These include digital pulse-amplitude, pulse-width, and pulse-position modulation, and various types of phase-shift keying and frequency-shift keying. The magnitudes of the spectral correlation functions are graphed as the heights of surfaces above a bifrequency plane, and these graphs are used as visual aids for comparison and contrast of the spectral correlation properties of different modulation types.

关键词： Digital modulation Space vector pulse width modulation signal processing Pulse modulation Phase shift keying Frequency shift keying Pulse width modulation Filters Matrices Parameter estimation

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SPECTRAL CORRELATION OF MODULATED signalS - .1. ANALOG MODULATION

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IEEE TRANSACTIONS ON COMMUNICATIONS 1987年第6期35卷 584-594页

作者： GARDNER, WA Signal and Image Processing Laboratory Department of Electrical and Computer Engineering University of California Davis CA USA

The importance of the concept of cyclostationarity in design and analysis of signal detectors, synchronizers, and extractors in communication systems is briefly discussed, and the central role of spectral correlation, in the characterization of random processes that are cyclostationary in the wide sense, is explained. A spectral correlation function that is a generalization of the power spectral density function is described, and a corresponding generalization of the Wiener-Khinchine relation and several other fundamental spectral correlation relations also are described. Explicit formulas for the spectral correlation function for various types of analog-modulated signals are derived. This includes pulse and carrier amplitude modulation, quadrature amplitude carrier modulation, and phase and frequency carrier modulation. To illustrate the differing spectral correlation characteristics of different modulation types, the magnitudes of the spectral correlation functions are graphed or described in graphical terms as the heights of surfaces above a bifrequency plane.

关键词： Pulse modulation Amplitude modulation Phase modulation Quadrature amplitude modulation signal design signal analysis signal processing signal detection Detectors Frequency synchronization

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NONSTATIONARY LEARNING CHARACTERISTICS OF THE LMS ALGORITHM

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS 1987年第10期34卷 1199-1207页

作者： GARDNER, WA Signal and Image Processing Laboratory Department of Electrical and Computer Engineering University of California Davis USA

Upper and lower bounding first-order linear recursions for the mean-squared error realized with the LMS algorithm subjected to a sequence of independent nonstationary training vectors are derived. These bounds coincide to give the exact evolution of mean-squared error for the problem of identification of a nonrecursive time-varying system with white-noise excitation. This leads to an exact formula for time-averaged mean-squared error that is used to study optimization of the step-size parameter for minimum time-average misadjustment. New results on dependence of the minimal step size and the minimum misadjustment on the degree of nonstationarity are obtained.

关键词： Least squares approximation System identification Adaptive filters Algorithm design and analysis Vectors Time varying systems Gaussian distribution signal processing image processing

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CUMULANTS - A POWERFUL TOOL IN signal-processing

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PROCEEDINGS OF THE IEEE 1987年第9期75卷 1333-1334页

作者： GIANNAKIS, GB Department of Electrical EngineeringßSystems Signal and Image Processing Institute University of Southern California Los Angeles CA USA

The impulse response of a linear, time-invariant system is related in a simple closed-form solution to the output cumulants, when the input is assumed to be non-Gaussian and independent. This expression permits the use of one-dimensional processing of the output cumulants for identification of non-minimum-phase systems, and opens new directions in other signal processing applications.

关键词： signal processing Higher order statistics Frequency domain analysis Delay estimation Proceedings Editorial Board Gaussian distribution image processing Transfer functions Autocorrelation Amplitude estimation

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CLASSIFICATION OF PARTIAL 2-D SHAPES USING FOURIER DESCRIPTORS

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IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 1987年第5期9卷 686-690页

作者： LIN, CC CHELLAPPA, R Signal and Image Processing Institute Department of Electrical Engineering-Systems University of Southern California Los Angeles CA 90089.

We present a method for the classification of 2-D partial shapes using Fourier descriptors. We formulate the problem as one of estimating the Fourier descriptors of the unknown complete shape from the observations derived from an arbitrarily rotated and scaled shape with missing segments. The method used for obtaining the estimates of the Fourier descriptors minimizes a sum of two terms; the first term of which is a least square fit to the given data subject to the condition that the number of missing boundary points is not known and the second term is the perimeter2/area of the unknown shape. Experiments with synthetic and real boundaries show that estimates closer to the true values of Fourier descriptors of complete boundaries are obtained. Also, classification experiments performed using real boundaries indicate that reasonable classification accuracies are obtained even when 20-30 percent of the data is missing.

关键词： Shape Aircraft Parameter estimation Least squares approximation Pattern analysis Pattern recognition Biological cells image analysis X-ray detection X-ray detectors

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3-D optical interconnection networks

3-D optical interconnection networks

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Optics and the Information Age

作者： Sawchuk, Alexander A. Signal and Image Processing Institute Department of Electrical Engineering University of Southern California Los Angeles CA 90089-0272 United States

Introduction, Network Design and Applications - This paper describes 3-D dynamic optical interconnection networks that interconnect a 2-D array consisting of N × N input lines with a similar 2-D array of N × N output lines. These 3-D networks make specific use of the volume (non-planar) nature of optics and permit the design of interconnections that are extremely difficult or impossible to implement with planar electronic VLSI technology.

关键词： Interconnection networks (circuit switching)

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2-D Spectrum estimation for imperfectly observed lattice data

2-D Spectrum estimation for imperfectly observed lattice dat...

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

作者： R. Hansen R. Chellappa Signal and Image Processing Institute Department of Electrical Engineering University of Southern California USA

In this paper we investigate the use of parametric models and robustified maximum likelihood to estimate two-dimensional power spectra from imperfectly observed lattice data. The maximum likelihood (ML) estimates for the signal plus noise model are consistent and asymptotically efficient for noncausal autoregressive (NCAR) models, but the solution requires the use of computationally expensive non-linear optimization, such as Newton-Raphson. By approximating the ML equations through the use of a toroidal lattice the computational complexity is reduced without unduly destroying the asymptotic properties of the estimates. When outliers in the data occurs, ML might not perform well. In this case we make no strict assumption about the distribution of the observations but assume only that the data are nominally Gaussian but with heavier tails. Then we use a robust procedure to estimate the parameters for the model.

关键词： Spectral analysis Lattices Maximum likelihood estimation Equations Parameter estimation Covariance matrix Noise robustness signal processing image processing Parametric statistics

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