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Set-Membership Proportionate Affine Projection Algorithms

EURASIP Journal on Audio, Speech, and Music Processing volume 2007, Article number: 034242 (2007) Cite this article

Abstract

Proportionate adaptive filters can improve the convergence speed for the identification of sparse systems as compared to their conventional counterparts. In this paper, the idea of proportionate adaptation is combined with the framework of set-membership filtering (SMF) in an attempt to derive novel computationally efficient algorithms. The resulting algorithms attain an attractive faster converge for both situations of sparse and dispersive channels while decreasing the average computational complexity due to the data discerning feature of the SMF approach. In addition, we propose a rule that allows us to automatically adjust the number of past data pairs employed in the update. This leads to a set-membership proportionate affine projection algorithm (SM-PAPA) having a variable data-reuse factor allowing a significant reduction in the overall complexity when compared with a fixed data-reuse factor. Reduced-complexity implementations of the proposed algorithms are also considered that reduce the dimensions of the matrix inversions involved in the update. Simulations show good results in terms of reduced number of updates, speed of convergence, and final mean-squared error.

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Author information

Affiliations

  1. Signal Processing Laboratory, Helsinki University of Technology, Otakaari 5A, Espoo, 02150, Finland

    Stefan Werner

  2. Department of Electrical Engineering, Instituto Militar de Engenharia, Rio de Janeiro, 2229-270, Brazil

    José A Apolinário Jr.

  3. Signal Processing Laboratory, COPPE/Poli/Universidade Federal do Rio de Janeiro, Rio de Janeiro, 21945-970, Brazil

    Paulo S R Diniz

Authors
  1. Stefan Werner
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  2. José A Apolinário Jr.
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  3. Paulo S R Diniz
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Corresponding author

Correspondence to Stefan Werner.

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Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License (https://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Werner, S., Apolinário, J.A. & Diniz, P.S.R. Set-Membership Proportionate Affine Projection Algorithms. J AUDIO SPEECH MUSIC PROC. 2007, 034242 (2007). https://doi.org/10.1155/2007/34242

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Keywords

  • Acoustics
  • Convergence Speed
  • Adaptive Filter
  • Matrix Inversion
  • Projection Algorithm