A low delay and fast converging improved proportionate algorithm for sparse system identification

Authors:
Andy W. H. Khong;Patrick A. Naylor;Jacob Benesty
Affiliations:
Department of Electrical and Electronic Engineering, Imperial College London, London, UK;Department of Electrical and Electronic Engineering, Imperial College London, London, UK;INRS-EMT, Université du Québec, Montréal, QC, Canada
Venue:
EURASIP Journal on Audio, Speech, and Music Processing
Year:
2007

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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.