APPROXIMATION OF MARKOVIAN MODELS WITH NON-CONSTANT PARAMETERS.

Uday B. Desai, Saibal Banerjee, Sayfollah Kiaei

Research output: Contribution to journalConference article

Abstract

A generalization of the canonical correlation analysis approach has been developed for nonstationary processes generated by Markovian models with nonconstant parameters. This generalization is then used to develop two model reduction (approximation) algorithms.

Original languageEnglish (US)
Pages (from-to)1642-1644
Number of pages3
JournalProceedings of the IEEE Conference on Decision and Control
StatePublished - Dec 1 1984
Externally publishedYes

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ASJC Scopus subject areas

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

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