APPROXIMATION OF THE BAYES RULE.

M. Karny, K. M. Hangos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Bayesian statistics provides a useful theoretical framework for conceptual solution of a broad range of identification problems. However, the class of numerically feasible problems is too narrow. An attempt is made to equip this theory with a systematic construction of feasible approximations applicable in real-time. The essence of the proposed solution consists in a parametric global approximation of the probabilistic system model. The problem formulation is justified, its inherent difficulties are discussed and an illustrative application to the identification of a mixture of distributions is presented.

Original languageEnglish
Title of host publicationIFAC Proceedings Series
PublisherPergamon Press
Pages985-989
Number of pages5
Edition7
ISBN (Print)0080325424
Publication statusPublished - Dec 1 1985

Publication series

NameIFAC Proceedings Series
Number7
ISSN (Print)0741-1146

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ASJC Scopus subject areas

  • Engineering(all)

Cite this

Karny, M., & Hangos, K. M. (1985). APPROXIMATION OF THE BAYES RULE. In IFAC Proceedings Series (7 ed., pp. 985-989). (IFAC Proceedings Series; No. 7). Pergamon Press.