Stochastic Approximation and Large Deviations: General Results for W.p.l. Convergence,

Abstract

W.p.l. convergence results are obtained for stochastic recursive approximation algorithms under very general conditions. The gain sequence (a sub n) can go to zero very slowly and state-dependent noise, discontinuous dynamical equations and the projected or constrained algorithm are all treated. The basic technique is the theory of large deviations. Prior results obtained via this theory are extended in many directions. Keywords: Local linearization; Errors for tracking systems.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Feb 01, 1987
Accession Number
ADA185818

Entities

People

  • Harold J. Kushner
  • Paul Dupuis

Organizations

  • Brown University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Convergence
  • Data Science
  • Differential Equations
  • Equations
  • Indicators
  • Inequalities
  • Intervals
  • Mathematics
  • Probability
  • Random Variables
  • Sequences
  • Stationary
  • Statistics
  • Stochastic Processes
  • Theorems
  • Weak Convergence

Readers

  • Control Systems Engineering.
  • Mathematical Modeling and Probability Theory.