The use of orthogonal transforms for improving performance of adaptive filters
- 1 April 1989
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Circuits and Systems
- Vol. 36 (4) , 474-484
- https://doi.org/10.1109/31.92880
Abstract
This paper studies the convergence performance of the transform domain normalized least mean square (TDNLMS) algorithm with general nonlinearity and the transform domain normalized least mean M-estimate (TDNLMM) algorithm in Gaussian inputs and additive Gaussian and impulsive noise environment. The TDNLMM algorithm, which is derived from robust M-estimation, has the advantage of improved performance over the conventional TDNLMS algorithm in combating impulsive noises. Using Price's theorem and its extension, the above algorithms can be treated in a single framework respectively for Gaussian and impulsive noise environments. Further, by introducing new special integral functions, related expectations can be evaluated so as to obtain decoupled difference equations which describe the mean and mean square behaviors of the TDNLMS and TDNLMM algorithms. These analytical results reveal the advantages of the TDNLMM algorithm in impulsive noise environment, and are in good agreement with computer simulation results. © 2010 The Author(s).published_or_final_versionSpringer Open Choice, 21 Feb 201Keywords
This publication has 10 references indexed in Scilit:
- Performance of transform-domain LMS adaptive digital filtersIEEE Transactions on Acoustics, Speech, and Signal Processing, 1986
- The fast Hartley transformProceedings of the IEEE, 1984
- Discrete Hartley transformJournal of the Optical Society of America, 1983
- Transform domain LMS algorithmIEEE Transactions on Acoustics, Speech, and Signal Processing, 1983
- Fast implementations of LMS adaptive filtersIEEE Transactions on Acoustics, Speech, and Signal Processing, 1980
- Adaptive filtering in the frequency domainProceedings of the IEEE, 1978
- Stationary and nonstationary learning characteristics of the LMS adaptive filterProceedings of the IEEE, 1976
- The complex LMS algorithmProceedings of the IEEE, 1975
- Discrete Cosine TransformIEEE Transactions on Computers, 1974
- Automatic equalization using the discrete frequency domainIEEE Transactions on Information Theory, 1973