Highly Parallel Eigenvector Update Methods With Applications To Signal Processing

R. D. DeGroat; R. A. Roberts

doi:10.1117/12.936876

4 April 1986 Highly Parallel Eigenvector Update Methods With Applications To Signal Processing

R. D. DeGroat, R. A. Roberts

Proceedings Volume 0696, Advanced Algorithms and Architectures for Signal Processing I; (1986) https://doi.org/10.1117/12.936876
Event: 30th Annual Technical Symposium, 1986, San Diego, United States

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.

Citation Download Citation

R. D. DeGroat and R. A. Roberts "Highly Parallel Eigenvector Update Methods With Applications To Signal Processing", Proc. SPIE 0696, Advanced Algorithms and Architectures for Signal Processing I, (4 April 1986); https://doi.org/10.1117/12.936876

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