AN ALMOST SURE INVARIANCE PRINCIPLE FOR STOCHASTIC APPROXIMATION PROCEDURES IN LINEAR FILTERING THEORY
成果类型：
Article
署名作者：
Berger, Erich
署名单位：
University of Gottingen
刊物名称：
ANNALS OF APPLIED PROBABILITY
ISSN/ISSBN：
1050-5164
发表日期：
1997
页码：
444-459
关键词：
摘要：
In this paper we consider a class of stochastic approximation procedures that arises in linear filtering and regression theory. Our main result asserts that the stochastic approximation process satisfies an almost sure invariance principle (with a certain rate of convergence) if the partial sums of the errors do.