A Weighted Soft-Max PNLMS Algorithm for Sparse System Identification
Publish place: International Journal of Information and Communication Technology Research (IJICT، Vol: 8، Issue: 3
Publish Year: 1395
نوع سند: مقاله ژورنالی
زبان: English
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شناسه ملی سند علمی:
JR_ITRC-8-3_002
تاریخ نمایه سازی: 20 اسفند 1399
Abstract:
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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