@inbook{067f1004beae49e28ac95e575d436b74,

title = "Weighted averaging and stochastic approximation",

abstract = "We explore the relationship between weighted averaging and stochastic approximation algorithms, and study their convergence via a sample-path analysis. We prove that the convergence of a stochastic approximation algorithm is equivalent to the convergence of the weighted average of the associated noise sequence. We also present necessary and sufficient noise conditions for convergence of the average of the output of a stochastic approximation algorithm in the linear case. We show that the averaged stochastic approximation algorithms can tolerate a larger class of noise sequences than the stand-alone stochastic approximation algorithms.",

author = "Wang, {I. Jeng} and Chong, {Edwin K P} and Kulkarni, {Sanjeev R.}",

year = "1996",

language = "English (US)",

series = "Proceedings of the IEEE Conference on Decision and Control",

editor = "Anon",

booktitle = "Proceedings of the IEEE Conference on Decision and Control",

note = "Proceedings of the 1996 35th IEEE Conference on Decision and Control. Part 3 (of 4) ; Conference date: 11-12-1996 Through 13-12-1996",

}