Convergence of the Robbins-Monro algorithm under arbitrary disturbances

Research output: Contribution to journalConference article

2 Scopus citations

Abstract

The Robbins-Monro algorithm under arbitrary deterministic disturbances is studied and necessary and sufficient conditions on the noise sequence are obtained for convergence of the algorithm. We introduce a notion of persistently disturbing noise sequences, and show that it characterizes convergence of the algorithm under each fixed noise sequence. The results obtained are stronger than previous conditions and the proof techniques are simpler, involving only basic notions of convergence.

Original languageEnglish (US)
Pages (from-to)537-538
Number of pages2
JournalProceedings of the IEEE Conference on Decision and Control
Volume1
StatePublished - Dec 1 1993
EventProceedings of the 32nd Conference on Decision and Control - San Antonio, TX, USA
Duration: Dec 15 1993Dec 15 1993

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

Fingerprint Dive into the research topics of 'Convergence of the Robbins-Monro algorithm under arbitrary disturbances'. Together they form a unique fingerprint.

  • Cite this