Identification of linear stochastic systems based on partial
information
1995 ◽
Vol 8
(3)
◽
pp. 249-260
◽
Keyword(s):
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.
1982 ◽
Vol 36
(6)
◽
pp. 1045-1057
◽
1980 ◽
Vol 102
(1)
◽
pp. 28-34
◽
Proceedings of the ISCIE International Symposium on Stochastic Systems Theory and its Applications
◽
2016 ◽
Vol 2016
(0)
◽
pp. 96-103
1980 ◽
Vol 16
(4)
◽
pp. 498-503