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Proceedings Paper

Batch Covariance Relaxation (BCR) Adaptive Processing
Author(s): S. M. Daniel
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Paper Abstract

A BCR adaptive process [1], based on the Conjugate Gradients (CG) method [2], is offered as an alternative to a Sample Matrix Inversion (SMI) [3] approach to solving minimum-mean-square (MMS) problems. In contrast to SMI, BCR does not require that a matrix inverse exist. This point is demonstrated via computer simulation for the case of an adaptive array processing example. Furthermore, BCR lends itself to a simple and efficient fixed-point architecture capable of a numerical accuracy commensurate to sample word lengths, a fact substantiated via a precise computer emulation of the BCR implementation.

Paper Details

Date Published: 30 July 1982
PDF: 8 pages
Proc. SPIE 0298, Real-Time Signal Processing IV, (30 July 1982); doi: 10.1117/12.932526
Show Author Affiliations
S. M. Daniel, Advanced Technology and Systems Analysis (United States)

Published in SPIE Proceedings Vol. 0298:
Real-Time Signal Processing IV
Tien F. Tao, Editor(s)

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