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An exponentiated gradient adaptive algorithm for blind identification of sparse SIMO systems

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3 Author(s)
Benesty, J. ; Univ. du Quebec, Montreal, Que., Canada ; Yiteng Huang ; Jingdong Chen

Sparse impulse responses are encountered in many acoustic and wireless channels. Recently, a class of exponentiated gradient (EG) algorithms has been proposed. One of the algorithms belonging to this class, the so-called EG± algorithm, converges and tracks much better than the classical stochastic gradient, or LMS, algorithm for sparse impulse responses. We apply this technique to blind identification of a sparse SIMO system and develop the multichannel EG± algorithm. A simple experiment demonstrates its advantage in convergence compared to the MCLMS algorithm.

Published in:

Acoustics, Speech, and Signal Processing, 2004. Proceedings. (ICASSP '04). IEEE International Conference on  (Volume:2 )

Date of Conference:

17-21 May 2004