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Open AccessArticle

A Correntropy-Based Proportionate Affine Projection Algorithm for Estimating Sparse Channels with Impulsive Noise

1
College of Information and Communications Engineering, Harbin Engineering University, Harbin 150001, China
2
Key Laboratory of Microwave Remote Sensing, National Space Science Center, Chinese Academy of Sciences, Beijing 100190, China
*
Author to whom correspondence should be addressed.
Entropy 2019, 21(6), 555; https://doi.org/10.3390/e21060555
Received: 2 May 2019 / Revised: 30 May 2019 / Accepted: 31 May 2019 / Published: 2 June 2019
(This article belongs to the Special Issue Information Theoretic Learning and Kernel Methods)
A novel robust proportionate affine projection (AP) algorithm is devised for estimating sparse channels, which often occur in network echo and wireless communication channels. The newly proposed algorithm is realized by using the maximum correntropy criterion (MCC) and the data reusing scheme used in AP to overcome the identification performance degradation of the traditional PAP algorithm in impulsive noise environments. The proposed algorithm is referred to as the proportionate affine projection maximum correntropy criterion (PAPMCC) algorithm, which is derived in the context of channel estimation framework. Many simulation results were obtained to verify that the PAPMCC algorithm is superior to early reported AP algorithms with different input signals under impulsive noise environments. View Full-Text
Keywords: sparse channel estimation; maximum correntropy criterion; proportionate affine projection algorithm; impulsive noise environments sparse channel estimation; maximum correntropy criterion; proportionate affine projection algorithm; impulsive noise environments
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Jiang, Z.; Li, Y.; Huang, X. A Correntropy-Based Proportionate Affine Projection Algorithm for Estimating Sparse Channels with Impulsive Noise. Entropy 2019, 21, 555.

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