DocumentCode
1528577
Title
A global optimization method for continuous-time adaptive recursive filters
Author
Edmonson, William ; Palacios, Juan Carlos ; Lai, Chang An ; Latchman, Haniph
Author_Institution
Dept. of Electr. & Comput. Eng., Florida Univ., Gainesville, FL, USA
Volume
6
Issue
8
fYear
1999
Firstpage
199
Lastpage
201
Abstract
A major drawback of recursive adaptive filters based on gradient methods is that convergence to a global minimum is not always achieved. This is due to a nonconvex mean square error (MSE) performance surface. This article develops a continuous-time least mean square algorithm that converges to the global minimum with probability one.
Keywords
IIR filters; adaptive filters; circuit optimisation; continuous time filters; convergence of numerical methods; filtering theory; least mean squares methods; probability; recursive filters; IIR filter; MSE performance surface; continuous-time adaptive recursive filters; continuous-time least mean square algorithm; convergence; global optimization method; gradient methods; nonconvex mean square error; probability; Adaptive filters; Convergence; Gradient methods; Least mean square algorithms; Least squares approximation; Mean square error methods; Optimization methods; Signal processing algorithms; Stochastic processes; Taylor series;
fLanguage
English
Journal_Title
Signal Processing Letters, IEEE
Publisher
ieee
ISSN
1070-9908
Type
jour
DOI
10.1109/97.774864
Filename
774864
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