An almost sure invariance principle for stochastic approximation procedures in linear filtering theory

DOI10.1214/aoap/1034625339zbMath0877.62078OpenAlexW1980654622MaRDI QIDQ1364396

Erich Berger

Publication date: 25 August 1997

Published in: The Annals of Applied Probability (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1214/aoap/1034625339

zbMATH Keywords

linear filteringalmost sure invariance principles

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Stochastic approximation (62L20) Functional limit theorems; invariance principles (60F17)

Related Items (2)

Stochastic algorithms for computing means of probability measures ⋮ Convergence Rates and Decoupling in Linear Stochastic Approximation Algorithms

Cites Work

• An almost sure invariance principle for stationary ergodic sequences of Banach space valued random variables
• Asymptotic behaviour of a class of stochastic approximation procedures
• On the interrelation of almost sure invariance principles for certain stochastic adaptive algorithms and for partial sums of random variables
• Convergence of the Robbins-Monro method for linear problems in a Banach space
• An invariance principle for the Robbins-Monro process in a Hilbert space
• Rates of Convergence for an Adaptive Filtering Algorithm Driven by Stationary Dependent Data
• An invariance principle for the law of the iterated logarithm
• On Asymptotic Normality in Stochastic Approximation
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