@inproceedings{b51da72a31bb42c697ca326a1bd7ec89,
title = "Sparse LMS with segment zero attractors for adaptive estimation of sparse signals",
abstract = "Adaptive sparse signal estimation is needed for obtaining accurate channel knowledge in communication systems where the system response can be assumed to contain many near-zero coefficients. For sparse filter design, the zero-attracting LMS (ZA-LMS) incorporates the l1 norm penalty function into the quadratic LMS cost function to promote the sparseness during the adaptation process. The reweighted ZA-LMS (RZA-LMS) is developed using reweighted zero attractors with better performance. In this paper, we propose two new sparse LMS algorithms with segment zero attractors, referred as Segment RZA-LMS and Discrete Segment RZA-LMS. The Segment RZA-LMS outperforms RZA-LMS by using a piece-wise approximation of the reciprocal in the iterative algorithm of RZA-LMS. The Discrete Segment RZA-LMS is further developed to achieve faster convergence speed and lower steady state error performance than Segment RZA-LMS.",
keywords = "Adaptive filters, Least Mean Square (LMS), compressive sensing, l norm, sparse signals, system identification",
author = "Jie Yang and Sobelman, {Gerald E.}",
year = "2010",
doi = "10.1109/APCCAS.2010.5774742",
language = "English (US)",
isbn = "9781424474561",
series = "IEEE Asia-Pacific Conference on Circuits and Systems, Proceedings, APCCAS",
pages = "422--425",
booktitle = "Proceedings of the 2010 Asia Pacific Conference on Circuit and System, APCCAS 2010",
note = "2010 Asia Pacific Conference on Circuit and System, APCCAS 2010 ; Conference date: 06-12-2010 Through 09-12-2010",
}