Identification of linear stochastic systems based on partial information

N. U. Ahmed and S. M. Radaideh

International Journal of Stochastic Analysis, 1995, vol. 8, 1-12

Abstract:

In this paper, we consider an identification problem for a system of partially observed linear stochastic differential equations. We present a result whereby one can determine all the system parameters including the covariance matrices of the noise processes. We formulate the original identification problem as a deterministic control problem and prove the equivalence of the two problems. The method of simulated annealing is used to develop a computational algorithm for identifying the unknown parameters from the available observation. The procedure is then illustrated by some examples.

Date: 1995
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnijsa:794618

DOI: 10.1155/S1048953395000220

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