A performance-weighted mixture of LMS filters

Suleyman S. Kozat, Andrew C. Singer

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we explore the use of a particular multistage adaptation algorithm for a variety of adaptive filtering applications where the structure of the underlying process to be estimated is unknown. The proposed algorithm uses a performance-weighted mixture of LMS filters of various orders to construct its final output. The algorithm is analyzed in a stochastic context with respect to its convergence and mean-square error (MSE) behaviors and is shown to achieve the best MSE performance of the constituent algorithms in the mixture. Through simulations, it has been observed that the mixture structure can offer considerable performance improvement for both stationary and time varying observation sequences.

Original languageEnglish (US)
Title of host publication2009 IEEE International Conference on Acoustics, Speech, and Signal Processing - Proceedings, ICASSP 2009
Pages3101-3104
Number of pages4
DOIs
StatePublished - Sep 23 2009
Event2009 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2009 - Taipei, Taiwan, Province of China
Duration: Apr 19 2009Apr 24 2009

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Other

Other2009 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2009
CountryTaiwan, Province of China
CityTaipei
Period4/19/094/24/09

Keywords

  • LMS
  • Model combination
  • Model mixture
  • Prediction
  • Universal

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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  • Cite this

    Kozat, S. S., & Singer, A. C. (2009). A performance-weighted mixture of LMS filters. In 2009 IEEE International Conference on Acoustics, Speech, and Signal Processing - Proceedings, ICASSP 2009 (pp. 3101-3104). [4960280] (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings). https://doi.org/10.1109/ICASSP.2009.4960280