Reduced-complexity proportionate nlms employing block-based selective coefficient updates

This paper proposes a selective coefficient update algorithm for reducing the complexity of the proportionate normalized least- mean-square (P-NLMS) class of algorithms. It is shown that an optimal subset of coefficients to update, namely those minimizing the a posteriori error, cannot be constructe...

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Bibliographic Details
Published in2008 IEEE International Conference on Acoustics, Speech and Signal Processing pp. 233 - 236
Main Authors Gordy, J.D., Aboulnasr, T., Bouchard, M.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.03.2008
Subjects
adaptive echo cancellation
Adaptive filters
complexity reduction
Computer errors
Control systems
Convergence
Echo cancellers
Error correction
Information technology
IP-NLMS
Programmable control
selective coefficient update
Speech
Telecommunication control
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Summary:This paper proposes a selective coefficient update algorithm for reducing the complexity of the proportionate normalized least- mean-square (P-NLMS) class of algorithms. It is shown that an optimal subset of coefficients to update, namely those minimizing the a posteriori error, cannot be constructed efficiently. A sub- optimal block-based coefficient selection algorithm is presented that combines proportional weighting of the input signal vector with fast ranking methods. It is compared to existing sub-optimal algorithms with respect to complexity overhead and convergence rate. Simulations show that the proposed algorithm produces performance approaching that of the optimal subset while maintaining a low coefficient selection overhead.
ISBN:9781424414833
1424414830
ISSN:1520-6149
2379-190X
DOI:10.1109/ICASSP.2008.4517589