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Identification of linear stochastic systems based on partial information
1995
Journal of Applied Mathematics and Stochastic Analysis
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
doi:10.1155/s1048953395000220
fatcat:orj6e3mlyvaqhiwf5amtegbduq