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Optimal Hankel-norm approximation approach to model reduction of large-scale Markov chains

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

A model reduction problem of certain large-scale Markov chains under an optimal criterion for Hankel-norm approximation is discussed. The multi-dimensional Markov chain under investigation is assumed to have a finite-dimensional stationary state-transition matrix, which is first reformulated as a multi-input/multi-output (MIMO) linear time-invariant (LT1) stochastic system. Consequently, the resulting large-scale MIMO LTI stochastic system has a closed-form best approximant in the Hankel-norm from a specified class of stable lower-dimensional MIMO LTI systems. © 1992 Taylor & Francis Group, LLC.
Original languageEnglish
Pages (from-to)1289-1297
JournalInternational Journal of Systems Science
Volume23
Issue number8
DOIs
Publication statusPublished - Aug 1992
Externally publishedYes

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