Convergence of Recursive Adaptive and Identification Procedures via Weak Convergence Theory.

Abstract

Results and concepts in the theory of weak convergence of a sequence of probability measures are applied to convergence problems for a variety of recursive adaptive (stochastic approximation like) methods. Similar techniques have had wide applicability in areas of operations research and in some other areas in stochastic control. It is quite likely that they will play a much more important role in control theory than they do at present, since they allow relatively simple and natural proofs for many types of convergence and approximation problems. Part of the aim of the paper is tutorial: to introduce the ideas, and to show how they might be applied. Also, many of the results are new, and they can all be generalized in many directions. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1976
Accession Number
ADA033789

Entities

People

  • Harold J. Kushner

Organizations

  • Brown University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Abstracts
  • Air Force
  • Algorithms
  • Applied Mathematics
  • Control Theory
  • Convergence
  • Differential Equations
  • Equations
  • Identification
  • Mathematics
  • Numbers
  • Operations Research
  • Probability
  • Random Variables
  • Sequences
  • Stochastic Control
  • Weak Convergence

Fields of Study

  • Mathematics

Readers

  • Operations Research
  • Theoretical Analysis.