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A global optimization method for continuous time adaptive recursive filters

delete1999-08-01
delete2
PRE
AI
W
William Edmonson *
P
Palacios, JC
C
Chang An Lai
H
Haniph A. Latchman
DOI：10.1109/97.774864delete
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Abstract

Abstract

En 中文
A major drawback of recursive adaptive filters based on gradient methods is that convergence to global minimum is not always achieved. This is due to a nonconvex mean square error (MSE) performance surface. This letter develops a continuous-time least mean square algorithm that converges to the global minimum with probability one.
Keywords:
adaptive recursive filters
global optimization
stochastic approximation
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Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

IEEE Signal Processing Magazine cover
IEEE Signal Processing Magazine
IF:
9.6
Papers:
1.1W
Citations:
1.7W

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No organization information available