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Symmetry 2018, 10(3), 75; doi:10.3390/sym10030075

An Improved Set-Membership Proportionate Adaptive Algorithm for a Block-Sparse System

1,2
,
1,3,4,* and 5
1
College of Information and Communications Engineering, Harbin Engineering University, Harbin 150001, China
2
College of Communication and Electronic Engineering, Qiqihar University, Qiqihar 161006, China
3
National Space Science Center, Chinese Academy of Sciences, Beijing 100190, China
4
Acoustic Science and Technology Laboratory, Harbin Engineering University, Harbin 150001, China
5
Tencent AI Lab, Bellevue, WA 98004, USA
*
Author to whom correspondence should be addressed.
Received: 8 February 2018 / Revised: 12 March 2018 / Accepted: 14 March 2018 / Published: 19 March 2018
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Abstract

In this paper, an improved set-membership proportionate normalized least mean square (SM-PNLMS) algorithm is proposed for block-sparse systems. The proposed algorithm, which is named the block-sparse SM-PNLMS (BS-SMPNLMS), is implemented by inserting a penalty of a mixed l 2 , 1 norm of weight-taps into the cost function of the SM-PNLMS. Furthermore, an improved BS-SMPNLMS algorithm (the (BS-SMIPNLMS algorithm) is also derived and analyzed. The proposed algorithms are well investigated in the framework of network echo cancellation. The results of simulations indicate that the devised BS-SMPNLMS and BS-SMIPNLMS algorithms converge faster and have smaller estimation errors compared with related algorithms. View Full-Text
Keywords: set-membership principle; PNLMS algorithm; block-sparse system set-membership principle; PNLMS algorithm; block-sparse system
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Jin, Z.; Li, Y.; Liu, J. An Improved Set-Membership Proportionate Adaptive Algorithm for a Block-Sparse System. Symmetry 2018, 10, 75.

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