An alternative proof for convergence of stochastic approximation algorithms

S. R. Kulkarni, C. S. Horn

Research output: Contribution to journalArticle

9 Scopus citations

Abstract

An alternative proof for convergence of stochastic approximation algorithms is provided. The proof is completely deterministic, very elementary (involving only basic notions of convergence), and direct in that it remains in a discrete setting. An alternative form of the Kushner-Clark condition is introduced and utilized and the results are the first to prove necessity for general gain sequences in a Hilbert space setting.

Original languageEnglish (US)
Pages (from-to)419-424
Number of pages6
JournalIEEE Transactions on Automatic Control
Volume41
Issue number3
DOIs
StatePublished - Dec 1 1996

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering

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