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共 465 条记录，以下是281-290 订阅

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Application of symmetric redundant residues for fast and reliable arithmetic

Application of symmetric redundant residues for fast and rel...

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Conference on advanced signal processing algorithms, architectures and implementations Xii

作者： Parhami, B Univ Calif Santa Barbara Dept Elect & Comp Engn Santa Barbara CA 93106 USA

ISBN: (纸本)0819445584

Despite difficulties in general division, magnitude comparison, and sign detection, residue number system arithmetic has been used for many special-purpose systems in light of its parallelism and modularity for the most common arithmetic operations of addition/subtraction and multiplication. Computation in RNS requires modular reduction, both for the initial conversion from binary to RNS and after each operation to bring the result back to within a valid residue range. Use of redundant residues simplifies this critical operation, leading to even faster arithmetic. One type of redundant mod-m residue, that keeps the representational redundancy to the minimum of 1 bit per residue, has the nearly symmetric range [-m, m) and allows two values for each pseudoresidue: (m) or (m) - m. We study the extent of simplification and speed-up in the modular reduction process afforded by such redundant residues and discuss its potential implications to the design of RNS arithmetic circuits. In particular, we show that besides cost and performance benefits, introduction of error checking and fault tolerance in arithmetic computations is facilitated when such redundant residues are used.

关键词： computer arithmetic error code modular reduction parallel processing redundant representation RNS

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Parallel uses for serial arithmetic in signal processors

Parallel uses for serial arithmetic in signal processors

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advanced signal processing algorithms, architectures, and implementations ii

作者： Owens, Robert M. Irwin, Mary J. The Pennsylvania State Univ. University Park PA USA

ISBN: (纸本)0819406945

In this paper we consider using 'digit serial' processing to build high performance parallel structures, in particular, parallel signal processors. Digit serial arithmetic processors have digit serial data transmission combined with digit serial computation. Three digit serial arithmetic processors are presented and compared with their digit parallel counterparts. We show that by using a digit serial approach we can achieve a higher throughput than with a digit parallel processor, even though the two processors are structurally similar and have components of similar complexity.

关键词： signal processing

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BLOCK CIRCULANT PRECONDITIONERS FOR 2-D DECONVOLUTION

BLOCK CIRCULANT PRECONDITIONERS FOR 2-D DECONVOLUTION

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

作者： CHAN, RH NAGY, JG PLEMMONS, RJ Univ. of Hong Kong (Hong Kong China) Univ. of Minnesota (United States) Wake Forest Univ. (United States)

ISBN: (纸本)081940943X

Discretized 2-D deconvolution problems arising, e.g., in image restoration and seismic tomography, can be formulated as 1eas squares compuaions, mm lib— Tx112 where T is often a large-scale rectangular Toeplitz-block matrix. We consider solving such block least squares problems by the preconditioned conjugate gradient algorithm using square nonsingular circulant-block and related preconditioners, constructed from the blocks of the rectangular matrix T. Preconditioning with such matrices allows efficient implementation using the 1-D or 2-D Fast Fourier Transform (FFT). It is well known that the resolution of ill-posed deconvolution problems can be substantially improved by regularization to compensate for their ill-posed nature. We show that regularization can easily be incorporated into our preconditioners, and we report on numerical experiments on a Cray Y-MP. The experiments illustrate good convergence properties of these FET—based preconditioned iterations.

关键词： Image restoration Matrices Deconvolution Fourier transforms Point spread functions Radon Image processing Information operations Iterative methods Mathematics

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ADAPTIVE ANTENNA BEAMFORMING USING ORTHOGONAL DECOMPOSITION 4

ADAPTIVE ANTENNA BEAMFORMING USING ORTHOGONAL DECOMPOSITION

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

作者： YU, KB GE Corporate Research and Development Ctr. (United States)

ISBN: (纸本)0819412767

An algorithm has been developed to control the antenna array beam pattern for multiple beam antenna (MBA) or phased array systems. The algorithm is motivated by military satellite communications applications where the uplink received antenna is desired to provide beamforming capability for selective earth coverage and jamming protection. The problem can be formulated as to determine the control weight to meet the user gain and jammer null requirements in their known directions subject to the norm constraint of the weight defined by the power conservation law. The algorithm makes use of an orthogonal decomposition of the weight vector into the constraint weight vector and the zero-output weight vector. If the constraint weight vector satisfies the norm bound constraint, the zero-output vector can further be optimized to minimize the deviation of the resulting weight from the quiescent weight. If the constraint weight vector does not satisfy the norm bound constraint, a recursive procedure has been developed which provides flexibility in the determination of the constraint vectors, the constraint order and the constraint phase optimization. This algorithm provides a practical means to achieve the constraints subject to the norm bound condition.

关键词： Antennas Algorithm development Phased arrays Control systems Nulling interferometry Satellite communications Telecommunications Data processing Mobile communications Receivers

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Efficient computation of densely sampled wavelet transforms

Efficient computation of densely sampled wavelet transforms

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advanced signal processing algorithms, architectures, and implementations ii

作者： Jones, Douglas L. Baraniuk, Richard G. Univ. of Illinois/Urbana-Champaign Urbana IL USA

ISBN: (纸本)0819406945

An efficient algorithm is presented for computing the continuous wavelet transform and the wideband ambiguity function on a sample grid with uniform time spacing but arbitrary sampling in scale. The method is based on the chirp z-transform and requires the same order of computation as constant-bandwidth analysis techniques, such as the short-time Fourier transform and the narrowband ambiguity function. An alternative spline approximation method which is more efficient when the number of scale samples is large is also described.

关键词： signal processing

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Separating desired image and signal invariant components from extraneous variations 6

Separating desired image and signal invariant components fro...

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

作者： Williams, WJ Zalubas, EJ Hero, A UNIV MICHIGAN DEPT ELECT ENGN & COMP SCIANN ARBORMI 48109

ISBN: (纸本)0819422347

Images and signals can be characterized by representations invariant to time shifts, spatial shifts, frequency shifts, and scale changes as the situation dictates. Advances in time-frequency analysis and scale transform techniques have made this possible. The next step is to distinguish between invariant forms representing different classes of image or signal. Unfortunately, additional factors such as noise contamination and `style' differences complicate this. A ready example is found in text, where letters and words may vary in size and position within the image segment being examined. Examples of complicating variations include font used, corruption during fax transmission, and printer characteristics. The solution advanced in this paper is to cast the desired invariants into separate subspaces for each extraneous factor or group of factors. The first goal is to have minimal overlap between these subspaces and the second goal is to be able to identify each subspace accurately. Concepts borrowed from high-resolution spectral analysis, but adapted uniquely to this problem have been found to be useful in this context. Once the pertinent subspace is identified, the recognition of a particular invariant form within this subspace is relatively simple using well-known singular value decomposition techniques.

关键词： scale transform Mellin transform wordspotting singular value decomposition character recognition time-frequency

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Parallel and fault -tolerant techniques for adaptive matched -field processing (MFP) on distributed array systems

Parallel and fault -tolerant techniques for adaptive matched...

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作者： Cho, Kil Seok University of Florida

学位级别：Ph.D.

Sonar array systems in the highly cluttered undersea environment require new and enhanced signal-processing algorithms and sophisticated architectures to meet the stringent real-time and reliability mission requirements. These demands present significant challenges in terms of computational complexity and dependability; and necessitate the development and use of high-performance computing techniques and advanced signal-processing algorithms. Our study introduces novel parallel and fault-tolerant techniques for adaptive matched-field processing (MFP) which we investigated on distributed array systems along with high-performance networking and distributed computing architectures. We developed the parallel algorithms for adaptive MFP to satisfy the computational and memory requirements not readily supported by cutting-edge, high-performance, single-processor systems. We proposed robust MFP algorithms to compensate for the performance degradation presented by sensor failures in sonar array systems. We also developed fault-tolerant parallel algorithms characterized by low overhead and fast recovery time to enhance dependability. We implemented the proposed parallel algorithms and fault-tolerant mechanisms on scalable clusters of computers. We compared their performance considering several critical factors such as parallel and fault-tolerant techniques, communication schemes, and processor architectures. Results show that these parallel and fault-tolerant algorithms can provide a feasible solution for real-time, scalable, and highly reliable beamforming implementations on distributed array systems.

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PARALLEL AND ADAPTIVE HIGH-RESOLUTION DIRECTION FINDING

PARALLEL AND ADAPTIVE HIGH-RESOLUTION DIRECTION FINDING

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

作者： VANPOUCKE, F MOONEN, M DEPRETTERE, E Katholieke Univ. Leuven (Belgium) Delft Univ. of Technology (Netherlands)

ISBN: (纸本)081940943X

The direction-of-arrival (DOA) estimation problem consists in determining the angles of arrival of a number of signals impinging on a sensor array. Recently, the so-called ESPRIT method of Roy and Paulraj has received a great deal of attention in the literature. The method employs matrix decomposition techniques, such as singular value decomposition (SVD) and generalized Schur decomposition (GSD). The computational complexity thus involved represents a serious impediment, especially when a real-time implementation is aimed for. Therefore, the aim here is to develop an ESPRIT-type algorithm which is fully adaptive and amenable to parallel implementation. By introducing adaptivity, the computational complexity per sampling period is reduced from (Omicron) (m³) to (Omicron) (m²), where m is the `problem size,' i.e., the number of antenna doublets. On a parallel processor array with (Omicron) (m²) processors, the throughput is then (Omicron) (m^o), which means that the number of measurements that are processed per time unit is independent of the problem size. The algorithm is based on an adaptive SVD updating algorithm, combined with an adaptive GSD. The corresponding systolic implementation is based on the systolic SVD updating array of Moonen et al.

关键词： Matrices Sensors Algorithm development Interference (communication) Array processing Antennas Data processing Parallel computing Electrical engineering Phase shifts

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Dynamically parameterized algorithms and architectures to exploit signal variations for improved performance and reduced power

Dynamically parameterized algorithms and architectures to ex...

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IEEE International Conference on Acoustics, Speech, and signal processing

作者： Burleson, W Tessier, R Goeckel, D Swaminathan, S Jain, P Euh, J Venkatraman, S Thyagarajan, V Univ Massachusetts Dept Elect & Comp Engn Amherst MA 01003 USA

ISBN: (纸本)0780370414

signal processing algorithms and architectures can use dynamic reconfiguration to exploit variations in signal statistics with the objectives of improved performance and reduced power consumption. Parameters provide a simple and formal way to characterize incremental changes to a computation and its computing mechanism. This paper examines five parameterized computations which are typically implemented in hardware for a wireless multimedia terminal: 1) motion estimation, 2) discrete cosine transform, 3) Lempel-Ziv lossless compression, 4) 3D graphics light rendering and 5) Viterbi decoding, Each computation is examined for the capability of dynamically adapting the algorithm and architecture parameters to variations in their respective input signals. Dynamically reconfigurable low-power implementations of each computation are currently underway.

关键词： Digital signal processing

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Optimizing time-frequency distributions for automatic classification

Optimizing time-frequency distributions for automatic classi...

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Conference on advanced signal processing - algorithms, architectures, and implementations Vii

作者： Atlas, L Droppo, J McLaughlin, J Univ. of Washington (United States) MIT Lincoln Lab. (United States)

ISBN: (纸本)0819425842

An entirely new set of criteria for the design of kernels (generating functions) for time-frequency representations (TFRs) is presented. These criteria aim only to produce kernels (and thus, TFRs) which will enable more accurate classification. We refer to these kernels, which are optimized to discriminate among several classes of signals, as signal class dependent kernels, or simply class dependent kernels. The genesis of the class dependent kernel is to be found in the area of operator theory, which we use to establish a direct link between a discrete-time, discrete-frequency TFR and its corresponding discrete signal. We see that many similarities, but also some important differences, exist between the results of the continuous-time operator approach and our discrete one. The differences between the continuous representations and discrete ones may not be the simple sampling relationship which has often been assumed. From this work, we obtain a very concise, matrix-based expression for a discrete-time/discrete-frequency TFR which is simply the product of the kernel with another matrix. This simple expression opens up the possibility to optimize the kernel in a number of ways. We focus, of course, on optimizations most suitable for classification, and ultimately wind up with the class dependent kernel. When applied to simulated sonar transient signals, we find that our approach does a good job of discriminating within very similar classes of transients and is especially sensitive to differences in time variation across classes.

关键词： Time-frequency analysis Matrices Fourier transforms Convolution Detection theory Distance measurement signal generators signal processing Silicon Stochastic processes

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