Supervised Identification and Removal of Common Filter Components in Adaptive Blind SIMO System Identification

M. R. P. Thomas, N. D. Gaubitch, E. A. P. Habets, and P. A. Naylor

Abstract

Adaptive blind system identification with LMStype algorithms is prone to misconvergence in the presence of noise. In this paper we consider the hypothesis that such misconvergence is due to the introduction of a common filter to the estimated impulse respones. A technique is presented for identifying and removing the common filter using prior knowledge of the true channels. Experimental results with this approach show an improved rate of convergence and reduced system error. Furthermore, misconvergent behaviour is no longer observed, offering a plausible explanation as to the source of misconvergence in adaptive blind system identification.

Details

Publication typeInproceedings
Published inProc. Intl. Workshop Acoust. Echo Noise Control (IWAENC)
AddressTel Aviv, Israel
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