THE SVD AND REDUCED RANK SIGNAL-PROCESSING

被引：135

作者：

SCHARF, LL

机构：

[1] Department of Electrical and Computer Engineering, University of Colorado, Boulder

来源：

SIGNAL PROCESSING | 1991年 / 25卷 / 02期

关键词：

ARMA; ANALYSIS AND SYNTHESIS; BAND-LIMITED; BIAS AND VARIANCE; BLOCK QUANTIZER; COMPLEX EXPONENTIAL; DETECTOR; DISTORTION; EIGENVALUES AND EIGENVECTORS; GRAMMIAN; LEAST SQUARES; LINEAR CONSTRAINTS; LINEAR MODELS; LOW-RANK; MATRIX APPROXIMATION; ORDER SELECTION; ORTHOGONAL DECOMPOSITION; ORTHOGONAL SUBSPACE; PARSIMONY; PROJECTION; PSEUDO-INVERSE; QUADRATIC MINIMIZATION; RANK REDUCTION; RATE-DISTORTION; SIGNAL PROCESSING; SIGNAL SUBSPACE; SINGULAR VALUES AND SINGULAR VECTORS; SUBSPACE SPLITTING; SVD; WIENER FILTER;

D O I：

10.1016/0165-1684(91)90058-Q

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

The basic ideas of reduced-rank signal processing are evident in the original work of Shannon, Bienvenu, Schmidt, and Tufts and Kumaresan. In this paper we extend these ideas to a number of fundamental problems in signal processing by showing that rank reduction may be applied whenever a little distortion may be exchanged for a lot of variance. We derive a number of quantitative rules for reducing the rank of signal models that are used in signal processing algorithms.

引用

页码：113 / 133

页数：21

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