Architectures and algorithms for nonlinear adaptive filters

V. Hegde, C. Radhakrishnan, D. J. Krusienski, William Kenneth Jenkins

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

This paper considers series-cascade nonlinear adaptive filter architectures consisting of a linear input filter, a memoryless polynomial nonlinearity, and a linear output filter (LNL). The learning characteristics of the LNL structure are studied in terms of performance and complexity. Replacing the linear input stage and the memoryless nonlinear stage of the LNL model with a Volterra module is then considered. Adaptive algorithms are summarized for these structures and experimental examples are used to illustrate performance for the identification of an acoustic echo channel.

Original languageEnglish (US)
Pages (from-to)1015-1016
Number of pages2
JournalConference Record of the Asilomar Conference on Signals, Systems and Computers
Volume2
DOIs
StatePublished - Jan 1 2002

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Adaptive filters
Adaptive algorithms
Acoustics
Polynomials

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Computer Networks and Communications

Cite this

Hegde, V. ; Radhakrishnan, C. ; Krusienski, D. J. ; Jenkins, William Kenneth. / Architectures and algorithms for nonlinear adaptive filters. In: Conference Record of the Asilomar Conference on Signals, Systems and Computers. 2002 ; Vol. 2. pp. 1015-1016.
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Architectures and algorithms for nonlinear adaptive filters. / Hegde, V.; Radhakrishnan, C.; Krusienski, D. J.; Jenkins, William Kenneth.

In: Conference Record of the Asilomar Conference on Signals, Systems and Computers, Vol. 2, 01.01.2002, p. 1015-1016.

Research output: Contribution to journalArticle

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