NDLI: Convergence and applications of stochastic approximation with state-dependent noise

Content Provider	IEEE Xplore Digital Library
Author	Han-Fu Chen
Copyright Year	2001
Description	Author affiliation: Acad. of Math. & Syst. Sci., Chinese Acad. of Sci., China (Han-Fu Chen)
Abstract	The purpose of stochastic approximation (SA) is to find the roots of f(/spl middot/) when the unknown function f(/spl middot/) can be observed with noise. In this paper the pathwise convergence of SA algorithms is considered for the case where the observation noise may depend on state, by which we mean the estimate for the sought-for root of f(/spl middot/). The conditions imposed on the observation noise are the weakest in comparison with the existing ones. The superiority of the noise condition given in the paper over those used in Chen (1994) and Chen and Zhu (1996) consists in that the present condition is directly verifiable, needless to pay attention to the behavior of the algorithm. The conditions imposed on f(/spl middot/) are general: f(/spl middot/) is only required to be measurable and locally bounded. Applications to optimization and signal processing demonstrate the strong points of the convergence theorems given in the paper.
Sponsorship	American Autom. Control Council
Starting Page	744
Ending Page	749
File Size	500869
Page Count	6
File Format	PDF
ISBN	0780364953
ISSN	07431619
DOI	10.1109/ACC.2001.945804
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2001-06-25
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	American Automatic Control Council(AACC)
Subject Keyword	Stochastic resonance Signal processing algorithms Convergence Noise measurement Stochastic systems Adaptive signal processing Time measurement Temperature dependence Laboratories Control systems
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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