DocumentCode
1846469
Title
Comparison of the convergence of IIR evolutionary digital filters and other adaptive digital filters on a multiple-peak surface
Author
Abe, Masahide ; Kawamata, Masayuki
Author_Institution
Dept. of Electron. Eng., Tohoku Univ., Sendai, Japan
Volume
2
fYear
1997
fDate
2-5 Nov. 1997
Firstpage
1674
Abstract
This paper demonstrates a comparison of the convergence behavior of the IIR evolutionary digital filter (IIR-EDF), the LMS adaptive digital filter (LMS-ADF) and the adaptive digital filter based on the simple genetic algorithm (SGA-ADF) on a multiple-peak surface. In numerical examples, the authors use a reduced-order system identification to simulate a multiple-peak surface in which local minimum problems can be encountered. The experimental results show that the EDF adaptive algorithm can search the global minimum in the multiple-peak surface of these examples and has a smaller adaptation noise than the other algorithms.
Keywords
IIR filters; adaptive filters; adaptive signal processing; convergence of numerical methods; digital filters; filtering theory; genetic algorithms; identification; least mean squares methods; noise; search problems; EDF adaptive algorithm; IIR evolutionary digital filters; IIR-EDF; LMS adaptive digital filter; LMS-ADF; SGA-ADF; adaptation noise; adaptive digital filters; convergence; experimental results; global minimum search; local minimum problems; multiple-peak surface; reduced-order system identification; simple genetic algorithm; simulation; Adaptive algorithm; Adaptive filters; Convergence; Digital filters; Filtering; Genetic algorithms; Genetic engineering; IIR filters; Least squares approximation; Reduced order systems;
fLanguage
English
Publisher
ieee
Conference_Titel
Signals, Systems & Computers, 1997. Conference Record of the Thirty-First Asilomar Conference on
Conference_Location
Pacific Grove, CA, USA
ISSN
1058-6393
Print_ISBN
0-8186-8316-3
Type
conf
DOI
10.1109/ACSSC.1997.679187
Filename
679187
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