| 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; Université du Québec, 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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