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The use of the modified escalator algorithm to improve the performance of transform-domain LMS adaptive filters

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2 Author(s)
Parikh, V.N. ; Voxware Inc., Princeton, NJ., USA ; Baraniecki, A.Z.

This paper describes a new algorithm that improves the convergence performance of the transform-domain least mean-square (TRLMS) algorithm. The algorithm exploits the sparse structure of the correlation matrix of the transformed input process to derive a data dependent Gram-Schmidt orthogonalization type transform of the process. We show its faster convergence compared with the time-domain least mean-square (LMS) algorithm and the DCT or the DWT-based TRLMS algorithm. The Gram-Schmidt orthogonalization is realized using a modified adaptive escalator algorithm. The modification significantly reduces the computational complexity of the adaptive escalator algorithm and determines the computational complexity of the proposed algorithm

Published in:

Signal Processing, IEEE Transactions on  (Volume:46 ,  Issue: 3 )

Date of Publication:

Mar 1998

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