Quantifying the convergence speed of LMS adaptive FIR filter with autoregressive inputs

Homer, J. (2000) Quantifying the convergence speed of LMS adaptive FIR filter with autoregressive inputs. Electronics Letters, 36 6: 585-586. doi:10.1049/el:20000469


Author Homer, J.
Title Quantifying the convergence speed of LMS adaptive FIR filter with autoregressive inputs
Journal name Electronics Letters   Check publisher's open access policy
ISSN 0013-5194
1350-911X
Publication date 2000-03-16
Sub-type Article (original research)
DOI 10.1049/el:20000469
Volume 36
Issue 6
Start page 585
End page 586
Total pages 2
Editor G. Wheeler
J. Davies
A. Kulikowski
S. Govan
Place of publication Stevenage, U.K.
Publisher Institution of Electrical Engineers (IEE)
Collection year 2000
Language eng
Subject C1
280204 Signal Processing
700199 Computer software and services not elsewhere classified
Formatted abstract
In general the least mean squares adaptive finite impulse response (FIR) filter converges more slowly with an increase in filter length and input signal correlation level. An explicit expression is presented relating the convergence speed of this adaptive filter to the FIR filter length and the correlation characteristics of autoregressive (AR) modelled input signals. The expression provides a simple means for justifying (or not) the cost of input signal whitening techniques within for example acoustic echo cancellation, in which very large FIR filter lengths and highly correlated AR modelled speech input signals occur.
Keyword Computer Science, Interdisciplinary Applications
Engineering, Electrical & Electronic
Q-Index Code C1

Document type: Journal Article
Sub-type: Article (original research)
Collection: School of Information Technology and Electrical Engineering Publications
 
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Created: Tue, 10 Jun 2008, 10:47:12 EST