DETERMINISTIC BALANCING AND STOCHASTIC MODEL REDUCTION.

Document Type

Conference Proceeding

Date of Original Version

12-1-1984

Abstract

A recent approach to the deterministic model reduction problem is based on the notion of balancing. This notion has been extended to the stochastic case; however, there does not seem to be a direct relationship between these deterministic and stochastic balanced realizations. It is shown in this paper that there are two stochastic model reduction algorithms in the literature which result in a deterministically balanced model. These algorithms constitute the realization and transformation approaches to the same stochastic realization algorithm. Their equivalence with deterministic balancing provides a stochastic interpretation to the deterministic algorithm.

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