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Proceedings Paper

Highly Parallel Eigenvector Update Methods With Applications To Signal Processing
Author(s): R. D. DeGroat; R. A. Roberts
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Paper Abstract

Updating the eigenvalue decomposition (EVD) of the estimated correlation matrix arises in many signal processing problems. In this paper, we present an improved, highly parallel, linear rank-one EVD update algorithm which is based on a quadratic rank-one method due to Bunch, et al [1]. Both methods are evaluated and compared. A number of simulations involving the frequency estimation of non-stationary narrow-band signals are also performed in which linear prediction techniques are used with eigenvector pre-processing.

Paper Details

Date Published: 4 April 1986
PDF: 9 pages
Proc. SPIE 0696, Advanced Algorithms and Architectures for Signal Processing I, (4 April 1986); doi: 10.1117/12.936876
Show Author Affiliations
R. D. DeGroat, University of Colorado (United States)
R. A. Roberts, University of Colorado (United States)


Published in SPIE Proceedings Vol. 0696:
Advanced Algorithms and Architectures for Signal Processing I
Jeffrey M. Speiser, Editor(s)

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