Technical Program

Paper Detail

Paper:SPTM-P8.2
Session:Adaptive Filters II
Time:Thursday, May 20, 13:00 - 15:00
Presentation: Poster
Topic: Signal Processing Theory and Methods: Adaptive Systems & Filtering
Title: AN EXPONENTIATED GRADIENT ADAPTIVE ALGORITHM FOR BLIND IDENTIFICATION OF SPARSE SIMO SYSTEMS
Authors: Jacob Benesty; UniversitĂ© du QuĂ©bec, INRS-EMT 
 Yiteng (Arden) Huang; Bell Labs, Lucent Technologies 
 Jingdong Chen; Bell Labs, Lucent Technologies 
Abstract: 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$pm$ algorithm, converges and tracks much better than the classical stochastic gradient, or LMS, algorithm for sparse impulse responses. In this paper, we apply this technique to blind identification of a sparse SIMO system and develop the multichannel EG$pm$ algorithm. A simple experiment demonstrates its advantage in convergence compared to the MCLMS algorithm.
 
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