Improved efficient proportionate affine projection algorithm based on l 0-norm for sparse system identification

Haiquan Zhao; Yi Yu

Improved efficient proportionate affine projection algorithm based on l ₀-norm for sparse system identification

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Author(s): Haiquan Zhao¹ and Yi Yu¹
- Affiliations: 1: School of Electrical Engineering , Southwest Jiaotong University , Chengdu 610031 , People's Republic of China
Source: Volume 2014, Issue 1, January 2014, p. 20 – 23
DOI: 10.1049/joe.2013.0129 , Online ISSN 2051-3305

This is an open access article published by the IET under the Creative Commons Attribution-NonCommercial-NoDerivs License (http://creativecommons.org/licenses/by-nc-nd/3.0/)

Received 23/10/2013, Accepted 29/11/2013, Published 04/12/2013

A new improved memorised improved proportionate affine projection algorithm (IMIPAPA) is proposed to improve the convergence performance of sparse system identification, which incorporates l ₀-norm as a measure of sparseness into a recently proposed MIPAPA algorithm. In addition, a simplified implementation of the IMIPAPA (SIMIPAPA) with low-computational burden is presented while maintaining the consistent convergence performance. The simulation results demonstrate that the IMIPAPA and SIMIPAPA algorithms outperform the MIPAPA algorithm for sparse system identification.

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Improved efficient proportionate affine projection algorithm based on l ₀-norm for sparse system identification

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