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

  • Authors:

  • V.N. Parikh;A.Z. Baraniecki

  • Affiliations:

  • Voxware Inc., Princeton, NJ.;-

  • Venue:
  • IEEE Transactions on Signal Processing
  • Year:
  • 1998

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Abstract

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