EURASIP Journal on Audio, Speech, and Music Processing 
Volume 2007 (2007), Article ID 84376, 8 pages
doi:10.1155/2007/84376
Research Article

A Low Delay and Fast Converging Improved Proportionate Algorithm for Sparse System Identification

Andy W. H. Khong,1 Patrick A. Naylor,1 and Jacob Benesty2

 1Department of Electrical and Electronic Engineering, Imperial College London, Exhibition Road, London SW7 2AZ, UK
2INRS-EMT, Université du Québec, Suite 6900, 800 de la Gauchetière Ouest, Montréal H5A 1K6, QC, Canada
Received 4 July 2006; Revised 1 December 2006; Accepted 24 January 2007

Recommended by Kutluyil Dogancay

Abstract

A sparse system identification algorithm for network echo cancellation is presented. This new approach exploits both the fast convergence of the improved proportionate normalized least mean square (IPNLMS) algorithm and the efficient implementation of the multidelay adaptive filtering (MDF) algorithm inheriting the beneficial properties of both. The proposed IPMDF algorithm is evaluated using impulse responses with various degrees of sparseness. Simulation results are also presented for both speech and white Gaussian noise input sequences. It has been shown that the IPMDF algorithm outperforms the MDF and IPNLMS algorithms for both sparse and dispersive echo path impulse responses. Computational complexity of the proposed algorithm is also discussed.