Referenced Items are not available for this document.
The convergence rate of an LMS adaptive FIR filter to an unknown stationary channel may be influenced by the filter parameter dimension as well as by the input signal's characteristics. This dimension influence may be of importance in applications, such as adaptive acoustic echo cancellation, in which the unknown channel is typically modeled as a “long” FIR filter. The paper includes the development and proposal of a novel measure of the expected convergence rate of the LMS/FIR filter followed by analysis of this convergence rate measure. The analysis indicates that unless the input signal is white, the expected convergence rate decreases with increasing dimension down to a limiting value, which is determined by the input signal's autocorrelation level
Published in:
Signal Processing, IEEE Transactions on
(Volume:46
,
Issue:
10
)
Date of Publication: Oct 1998
- Page(s):
- 2611 - 2615
- ISSN :
- 1053-587X
- INSPEC Accession Number:
- 6045589
- Digital Object Identifier :
- 10.1109/78.720364
- Date of Current Version :
- 06 August 2002
- Issue Date :
- Oct 1998
- Sponsored by :
- IEEE Signal Processing Society
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