Volume 8, Issue 3 (9-2016)                   IJICTR 2016, 8(3): 7-14 | Back to browse issues page

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Bekrani M, Zayyani H. A Weighted Soft-Max PNLMS Algorithm for Sparse System Identification. IJICTR. 2016; 8 (3) :7-14
URL: http://ijict.itrc.ac.ir/article-1-58-en.html
1- Department of electrical and computer engineering Qom University of Technology Qom, Iran
Abstract:   (2365 Views)
This paper presents a new Proportionate Normalized Least Mean Square (PNLMS) adaptive algorithm using a soft maximum operator for sparse system identification. To provide a high rate of convergence, soft maximum operator is employed along with a weighting factor, which is proportional to an estimation of output mean square error (MSE). Simulation results show the superiority of the proposed algorithm over its PNLMS-based counterparts.
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Type of Study: Research | Subject: Information Technology

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