APPROXIMATE REALIZATION AND MODEL REDUCTION OF NON-MINIMUM PHASE STOCHASTIC SYSTEMS.

Georgios B. Giannakis, Jerry M. Mendel

Research output: Contribution to journalConference articlepeer-review

13 Scopus citations

Abstract

The authors deal with the stochastic realization and reduction of non-minimum-phase, linear, time-invariant systems. Assuming that the input is non-Gaussian, stationary and white, they propose the use of second and higher-order output statistics to identify a finite-dimensional ARMA model. Both the input/output, and state space approaches are considered. It is shown that higher-order output cumulants are useful in estimating the AR coefficients of the minimum-phase (MP) part, and in providing a means for model order determination. Higher order cumulants are exploited to realize the all-pass part of the ARMA model.

Original languageEnglish (US)
Pages (from-to)1079-1084
Number of pages6
JournalProceedings of the IEEE Conference on Decision and Control
DOIs
StatePublished - 1986

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