DocumentCode
2173508
Title
Almost sure convergence of the BMP scheme with resetting
Author
Gerencser, Laszlo ; Matyas, Zalan
Author_Institution
MTA SZTAKI, Comput. & Autom. Inst., Budapest, Hungary
fYear
2007
fDate
2-5 July 2007
Firstpage
4526
Lastpage
4531
Abstract
We consider stochastic approximation algorithms with Markovian dynamics as introduced in Benveniste, Métivier and Priouret [2]. Using a resetting mechanism with a fairly arbitrary truncation domain, the algorithm is shown to converge to the unique stationary point of the associated ODE with probability one. A self-contained outline to the basic technical aspects of the BMP theory will be also given.
Keywords
Markov processes; approximation theory; convergence; BMP scheme; Markovian dynamics; ODE; almost sure convergence; arbitrary truncation domain; probability; resetting mechanism; stochastic approximation algorithms; Approximation methods; Convergence; Heuristic algorithms; Kernel; Markov processes; Poisson equations; Vectors; Markovian dynamics; almost sure convergence; recursive estimation; resetting; stochastic systems;
fLanguage
English
Publisher
ieee
Conference_Titel
Control Conference (ECC), 2007 European
Conference_Location
Kos
Print_ISBN
978-3-9524173-8-6
Type
conf
Filename
7069014
Link To Document