DocumentCode
1451075
Title
Fast-convergence filtered regressor algorithms for blind equalisation
Author
Douglas, S.C. ; Cichocki, Andrzej ; Amari, S.
Author_Institution
Dept. of Electr. Eng., Utah Univ., Salt Lake City, UT, USA
Volume
32
Issue
23
fYear
1996
fDate
11/7/1996 12:00:00 AM
Firstpage
2114
Lastpage
2115
Abstract
The authors present a simple extension of the standard Bussgang blind equalisation algorithms that significantly improves their convergence properties. The technique uses the inverse channel estimate to filter the regressor signal. The modified algorithms provide quasi-Newton convergence in the vicinity of a local minimum of the chosen cost function with only a modest increase in the overall computational complexity of the system. An example of the technique as applied to the constant-modulus algorithm indicates its superior convergence behaviour
Keywords
computational complexity; convergence of numerical methods; deconvolution; equalisers; filtering theory; signal processing; blind equalisation; computational complexity; constant-modulus algorithm; convergence properties; cost function; fast-convergence algorithms; filtered regressor algorithms; inverse channel estimate; local minimum; quasi-Newton convergence;
fLanguage
English
Journal_Title
Electronics Letters
Publisher
iet
ISSN
0013-5194
Type
jour
DOI
10.1049/el:19961414
Filename
543782
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