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Exhaustive scheduling and retiming of digital signal processing systems

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-ANALOG AND DIGITAL signal processing 1998年第7期45卷 821-838页

作者： Denk, TC Parhi, KK Lucent Technol Bell Labs Holmdel NJ 07733 USA Univ Minnesota Dept Elect & Comp Engn Minneapolis MN 55455 USA

Scheduling and retiming are important techniques used in the design of hardware and software implementations of digital signal processing algorithms. In this paper, techniques are developed for generating all scheduling and retiming solutions for a strongly connected data-flow graph, allowing a designer to explore the space of possible implementations. Formulations are developed for two scheduling problems. The first scheduling problem assumes a bit-parallel target architecture. The formulation for this problem is general because it considers retiming the dataflow graph as part of scheduling, and this formulation reduces to the retiming formulation as a special case. The second scheduling problem assumes a bit-serial target architecture. Based on these formulations, the conditions for a legal scheduling solution are derived, and a systematic technique is presented for exhaustively generating all legal scheduling solutions for a strongly connected data-flow graph. Since retiming is a special case of scheduling, this systematic technique can also be used for exhaustively generating all legal retiming solutions. A technique is also developed for exhaustively generating only those bit-parallel schedules which satisfy a given set of resource constraints, The techniques for exhaustively generating scheduling and retiming solutions are demonstrated for several filters. For example, we show that a simple filter such as the biquad has 224 possible retiming solutions for a latency of one time unit. We also show that a fifth-order wave digital elliptic filter has 4.7 million and 580 million scheduling solutions for iteration periods of 17 and 18, respectively.

关键词： data flow graphs high-level synthesis parallel architectures retiming scheduling signal processing very large scale integration

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ANALYSIS OF A LINEARLY CONSTRAINED LEAST-SQUARES ALGORITHM FOR ADAPTIVE BEAMFORMING

ANALYSIS OF A LINEARLY CONSTRAINED LEAST-SQUARES ALGORITHM F...

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CONF ON advanced signal processing algorithms, architectures, AND implementations 3

作者： LUK, FT QIAO, SZ Rensselaer Polytechnic Institute (United States) McMaster Univ. (Canada)

ISBN: (纸本)081940943X

The problem of linearly constrained least squares has many applications in signal processing. In this paper, we present a perturbation analysis of a novel, linearly constrained least squares algorithm for adaptive beamforming. The perturbation bounds for the solution as well as for the latest residual element are derived. We also propose an error estimation scheme for the residual element. This error estimation scheme can be incorporated into a systolic array implementation of the algorithm. The additional time required for error estimation is small, as we show how the processor idle time can be used to carry out almost all the calculations.

关键词： Error analysis Chemical elements Analytical research Silicon Evolutionary algorithms signal processing Condition numbers Einsteinium Information operations Matrices

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CONVOLUTION, FILTERING, LINEAR-SYSTEMS, THE WIENER-KHINCHIN THEOREM - GENERALIZATIONS

CONVOLUTION, FILTERING, LINEAR-SYSTEMS, THE WIENER-KHINCHIN ...

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CONF ON advanced signal processing algorithms, architectures, AND implementations 3

作者： COHEN, L Rutgers Univ. (United States)

ISBN: (纸本)081940943X

A simple formulation is given for generating convolution theorems in any representation. Using this method we obtain the convolution theorem for the scale representation. We generalize the concept of invariance to any basis set and devise a method for handling linear invariant systems for arbitrary quantities. The Wiener-Khinchin theorem is generalized to arbitrary power energy densities. Also, we show how standard probability theory can be formulated in terms of signals.

关键词： Transform theory Convolution Fourier transforms Probability theory Linear filtering Electronic filtering Detection theory Information technology signal analysis Matrices

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signal arrival times

Signal arrival times

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Conference on advanced signal processing algorithms architectures and implementations XIII

作者： Hughes, DH USAF Res Lab Ctr Integrated Transmiss & Exploitat Rome NY 13441 USA

ISBN: (纸本)0819450782

A femtosecond electromagnetic pulse propagating in a linear dispersive medium is analyzed in phase spaces of (space, wave number) and (time, frequency). First moment densities are computed as eigenvalues of differential operators acting on Hilbert ray representations of the pulse in relevant domains. These moment densities are used as metrics in the relevant phase spaces to measure the local mean values and their deviations in position and wavenumber, and in time and frequency. For example, arrival times of the pulse over its spectral content are computed as the mean arrival time at a particular frequency to within one half the local deviation at that frequency. These metrics on the pulse are compared to the relevant phase space Wigner distribution.

关键词： space-time signal analysis local moments Wigner distribution time-frequency dispersion wave propagation FDTD moment densities instantaneous frequency

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NEURAL-NETWORK processing TO MINIMIZE QUANTIZATION LOSSES 4

NEURAL-NETWORK PROCESSING TO MINIMIZE QUANTIZATION LOSSES

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4TH CONF ON advanced signal processing algorithms, architectures, AND implementations

作者： WU, YJ CHAU, PM Univ. of California/San Diego (United States)

ISBN: (纸本)0819412767

A general neural network co-processor has been investigated and designed to adaptively adjust the quantization thresholds of a data quantizer, and thus a data quantizer with minimum quantization loss can be obtained. For a given probability density function and number of quantization levels, the neural network is designed to learn the near optimal quantization uniform step-size which minimizes the loss caused by the quantizer. With this neural network co-processor approach, consistent and substantial performance improvements have been verified on either an AWGN or a Rayleigh fading communication channel with convolutional encoder and maximum likelihood decoder. This general neural network co-processor approach can be applied to any digital signal processing system which has quantization loss, such as digital communication, image data compression, or adaptive signal processing.

关键词： Neural networks Quantization Digital signal processing Data communications signal processing signal to noise ratio Analog electronics Modulation signal attenuation Telecommunications

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Transmit diversity for TDD systems

Transmit diversity for TDD systems

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Conference on advanced signal processing algorithms, architectures and implementations XII

作者： Wang, JB Yao, K Univ Calif Los Angeles Dept Elect Engn Los Angeles CA 90095 USA

ISBN: (纸本)0819445584

Multiple input multiple output (MIMO) communications have been a hot research area in recent years. Most literature makes the assumption that the channel information is not known at the transmitter but known perfectly at the receiver. We focus on the situation where both the transmitter and the receiver know the channel information. We consider a transmit diversity scheme that maximizes the signal to noise ratio at the receiver. We analyze its performance in terms of capacity, duality and asymptotic behavior. By simulation, we compare this scheme with Alamouti's transmit diversity to show the advantage of utilizing the channel side information to improve the performance of the wireless systems.

关键词： signal to noise ratio Receivers signal processing Lithium Lutetium Transmitters Antennas

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A NEW ALGORITHM FOR RATIONAL SUBSPACE ESTIMATION BASED ON CASCADABLE ADAPTIVE LOSSLESS FILTERS 4

A NEW ALGORITHM FOR RATIONAL SUBSPACE ESTIMATION BASED ON CA...

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4TH CONF ON advanced signal processing algorithms, architectures, AND implementations

作者： FIJALKOW, I LOUBATON, P REGALIA, PA Telecom Paris Dept. Signal 46 rue Barrault Paris Cedex 13 75634 France Institut National des Telecommunications 9 rue Charles Fourier Evry Cedex 91011 France

ISBN: (纸本)0819412767

In a previous work, a time domain algorithm was proposed to adaptively estimate a rational and orthonormal spanning of a rational subspace. However, its convergence was not proved and it seems that asymptotic misbehaviour may occur. A new algorithm is proposed, for which satisfactory convergence properties hold. It provides robustness with regard to the signal model and shows an especially good asymptotical performance for small SNR. © 1993 SPIE. All rights reserved.

关键词： Time domain analysis

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NEW ENCODING DECODING METHODS FOR DESIGNING FAULT-TOLERANT MATRIX OPERATIONS

NEW ENCODING DECODING METHODS FOR DESIGNING FAULT-TOLERANT M...

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CONF ON advanced signal processing algorithms, architectures, AND implementations 3

作者： TAO, DL HAN, YS HARTMANN, CRP SUNY/Stony Brook (United States) Syracuse Univ. (United States)

ISBN: (纸本)081940943X

The algorithm-based fault tolerance (ABFT) provides low-cost error protection for VLSI processor arrays used in real-time digital signal processing. Several ABFT techniques (weighted check-sum) have be proposed to design fault-tolerant LU decomposition, QR decomposition, and matrix inversion. In these schemes, encoding/decoding uses either multiplication or division so that overhead is high. In this paper, we propose new encoding/decoding methods for designing fault-tolerant matrix operations. Since the new encoding/decoding methods use only additions and subtractions, the overhead of a fault-tolerant processor array can be drastically reduced.

关键词： Array processing Digital signal processing Silicon Tolerancing Chlorine Information operations Osmium signal processing Very large scale integration Electrical engineering

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algorithms FOR INSTANTANEOUS FREQUENCY ESTIMATION - A COMPARATIVE-STUDY

ALGORITHMS FOR INSTANTANEOUS FREQUENCY ESTIMATION - A COMPAR...

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CONF ON advanced signal-processing algorithms, architectures, AND implementations

作者： BOASHASH, B OSHEA, P ARNOLD, MJ Univ. of Queensland (Australia)

ISBN: (纸本)0819404098

This paper examines the problem of instantaneous frequency (IF) estimation for Frequency Modulated (FM) signals imbedded in white Gaussian noise. It reviews currently available techniques and in addition proposes some new ones based on a modelling of the signal phase as a polynomial. Both linear least-squares techniques and Maximum Likelihood (ML) techniques are investigated for estimating the polynomial coefficients. It is seen that the linear least squares approach is efficient (i. e. unbiased and meets the Cramer-Rao bounds) for high SNR while the ML scheme is efficient for a much larger range of SNR. Theoretical lower variance bounds are given for estimating the polynomial coefficients and are compared with the results of simulations. Guidelines are given as to which estimation method should be used for a given signal class and signal to Noise Ratio (SNR) level.

关键词： signal to noise ratio Fermium Frequency modulation Interference (communication) Modeling Modulation

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Time-frequency decomposition based on information

Time-frequency decomposition based on information

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Conference on advanced signal processing algorithms, architectures, and implementations xvI

作者： Aviyente, Selin Michigan State Univ E Lansing MI 48824 USA

ISBN: (纸本)0819463922

In array processing applications, it is desirable to extract the sources that generate the observed signals. There are various source separation and component extraction algorithms in literature including principal component analysis (PCA) and independent component analysis (ICA). However, most of these methods are not designed to deal with time-varying signals and thus are formulated in the time domain. In this paper, we introduce a new time-frequency based decomposition method using an information measure as the decomposition criteria. It is shown that under the assumption of disjoint source signals on the time-frequency plane, this method can extract the sources up to a scalar factor. Based on the QR decomposition of the mixing matrix, the source extraction algorithm is reduced to finding the optimal N-dimensional rotation of the observed time-frequency distributions. The proposed algorithm is implemented using the steepest descent approach to find the optimal rotation angle. The performance of the method is illustrated for example signals and compared to some well-known decomposition techniques.

关键词： Time-frequency analysis Independent component analysis Transform theory Principal component analysis Associative arrays Image information entropy Matrices signal processing Sensors Array processing

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