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Open AccessArticle

A Sparsity-Aware Variable Kernel Width Proportionate Affine Projection Algorithm for Identifying Sparse Systems

1
College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China
2
Key Laboratory of Microwave Remote Sensing, Chinese Academy of Sciences, Beijing 100190, China
*
Author to whom correspondence should be addressed.
Symmetry 2019, 11(10), 1218; https://doi.org/10.3390/sym11101218
Received: 20 August 2019 / Revised: 22 September 2019 / Accepted: 25 September 2019 / Published: 1 October 2019
A sparsity-aware variable kernel width proportionate affine projection (AP) algorithm is devised for identifying sparse system in impulsive noise environments. For the devised algorithm, the symmetry maximum correntropy criterion (MCC) is employed to develop a new cost function for improving the PAP algorithm, then the variable kernel width and the l p -norm-like constraint are incorporated into the cost-function, which is named as l p -norm variable kernel width proportionate affine projection (LP-VPAP) algorithm. The devised LP-VPAP algorithm is investigated and verified under impulsive interference environments. Experimental results show that the LP-VPAP gets a faster convergence and provides a lower steady-state performance compared with AP, zero-attracting AP (ZA-AP), reweighted ZA-AP (RZA-AP), proportionate AP (PAP), MCC, variable kernel width MCC (VKW-MCC), and proportionate AP MCC (PAPMCC) algorithms. View Full-Text
Keywords: maximum correntropy criterion; lp-norm; sparse system identification; impulsive interferences; proportionate affine projection algorithm maximum correntropy criterion; lp-norm; sparse system identification; impulsive interferences; proportionate affine projection algorithm
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Jiang, Z.; Li, Y.; Huang, X.; Jin, Z. A Sparsity-Aware Variable Kernel Width Proportionate Affine Projection Algorithm for Identifying Sparse Systems. Symmetry 2019, 11, 1218.

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