Eigen and subspace updating with forward-backward averaging

Author

DeGroat, Ronald D. ; Linebarger, Darel A.

Author_Institution

Erik Jonsson Sch. of Eng. & Comput. Sci., Texas Univ., Dallas, Richardson, TX, USA

fYear

1992

Firstpage

581

Abstract

The authors exploit the structure of forward-backward (FB) matrices to achieve reduced computation. In particular, computationally efficient eigenvalue decomposition (EVD) and EVD updating methods are developed for FB correlation matrices. Similarly, efficient singular value decomposition (SVD) and SVD updating methods are developed for FB data matrices. A general approach to reducing the computation associated with an FB matrix is described

Keywords

correlation methods; eigenvalues and eigenfunctions; matrix algebra; signal processing; eigenvalue decomposition; forward-backward averaging; signal processing; singular value decomposition; subspace updating; Arithmetic; Computer science; Eigenvalues and eigenfunctions; Matrix decomposition; Signal processing; Singular value decomposition;

fLanguage

English

Publisher

ieee

Conference_Titel

Signals, Systems and Computers, 1992. 1992 Conference Record of The Twenty-Sixth Asilomar Conference on

Conference_Location

Pacific Grove, CA

ISSN

1058-6393

Print_ISBN

0-8186-3160-0

Type

conf

DOI

10.1109/ACSSC.1992.269205

Filename

269205

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1587302