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

XML Print

Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Bekrani M, Zayyani H. A Weighted Soft-Max PNLMS Algorithm for Sparse System Identification. itrc 2016; 8 (3) :7-14
URL: http://journal.itrc.ac.ir/article-1-58-en.html
A Weighted Soft-Max PNLMS Algorithm for Sparse System Identification
Mehdi Bekrani , Hadi Zayyani
Abstract:   (3199 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.
Keywords: Sparse adaptive filter, System identification, Echo cancelation, Soft maximum
Full-Text [PDF 1442 kb]   (1865 Downloads)    
Type of Study: Research | Subject: Information Technology
Add your comments about this article : Your username or Email:
CAPTCHA
Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.