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A Weighted Soft-Max PNLMS Algorithm for Sparse System Identification

عنوان مقاله: A Weighted Soft-Max PNLMS Algorithm for Sparse System Identification
شناسه ملی مقاله: JR_ITRC-8-3_002
منتشر شده در در سال 1395
مشخصات نویسندگان مقاله:

Mehdi Bekrani
Hadi Zayyani

خلاصه مقاله:
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.

کلمات کلیدی:
Sparse adaptive filter, System identification, Echo cancelation, Soft maximum

صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/1165935/