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Mean-square analysis of the multiple-error and block LMS adaptive algorithms

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1 Author(s)
S. C. Douglas ; Dept. of Electr. Eng., Utah Univ., Salt Lake City, UT, USA

Stochastic-gradient adaptive algorithms for block-based or frequency-domain single channel filters and for true multichannel filters share a common multiple-error LMS algorithm update, given by W k+1=Wk+μXk(Dk-Xk TWk). We examine the mean-square performance of the multiple-error LMS adaptive algorithm for correlated Gaussian input data channels and arbitrary i.i.d. input data channels. Using our analysis, we show that the multiple-error LMS algorithm performs uniformly worse than the single-channel LMS algorithm for a given amount of data consumed. We also derive simple step size bounds to guarantee mean-square convergence of the multiple-error and block LMS adaptive algorithms. Simulations of both the block LMS adaptive algorithm and the multichannel filtered-X LMS adaptive algorithm corroborate our theoretical results

Published in:

Acoustics, Speech, and Signal Processing, 1994. ICASSP-94., 1994 IEEE International Conference on  (Volume:iii )

Date of Conference:

19-22 Apr 1994