DocumentCode
1367915
Title
General results on the convergence of stochastic algorithms
Author
Delyon, Bernard
Author_Institution
IRISA, Rennes, France
Volume
41
Issue
9
fYear
1996
fDate
9/1/1996 12:00:00 AM
Firstpage
1245
Lastpage
1255
Abstract
A deterministic approach is proposed for proving the convergence of stochastic algorithms of the most general form under necessary conditions on the input noise and reasonable conditions on the (nonnecessarily continuous) mean field. Emphasis is placed on the case where more than one stationary point exists. We also use this approach to prove the convergence of a stochastic algorithm with Markovian dynamics
Keywords
convergence; noise; stochastic processes; Markovian dynamics; convergence; input noise; mean field; necessary conditions; stationary point; stochastic algorithms; Convergence; Filtering algorithms; Helium; Heuristic algorithms; Random variables; Recursive estimation; Stochastic processes; Stochastic resonance; Stochastic systems; System identification;
fLanguage
English
Journal_Title
Automatic Control, IEEE Transactions on
Publisher
ieee
ISSN
0018-9286
Type
jour
DOI
10.1109/9.536495
Filename
536495
Link To Document