Huixin Chen, Xin-wei Wang, Chun-Li Liu, Fang Wen, R. Ruan
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Modeling and simulation of a class of stochastic bilinear systems
In this paper the modeling and simulation of a class of discrete-time stochastic bilinear systems are studied, the extended least squares (ELS) algorithm are used to estimate unknown parameters of the system, and two simulation examples show that the ELS algorithms of the modeling and simulation are effective for discrete-time stochastic bilinear systems with correlated noises and unknown parameters. The ELS algorithm is applied to adaptive tracking of a class of the systems and two simulation examples of the adaptive tracking are presented to show that the proposed adaptive tracking algorithm is of the good performance.