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- W2055705969 abstract "Techniques of state estimator design for a class of non-linear distributed parameter systems by discrete-time models are presented. Two construction methods of discrete-time models for non-linear stochastic distributed Darameter svstems are presented. One is a method by weighted-average finite-difference approximation and the other is a discrelization method by partial inversion using Green's function. For these discrete-time models, me stability preservation is examined. Based on these sample data discrete-time models, a state filtering algorithm for a non-linear stochastic distributed parameter system is derived by means of the bayesian approach combined with local linearization. The study shows that the discrete-time models of non-linear distributed parameter systems can better be treated in the form of non-linear integral equations, and the state filtering algorithm can be derived from these integral models." @default.
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- W2055705969 date "1991-10-01" @default.
- W2055705969 modified "2023-09-24" @default.
- W2055705969 title "State estimation of a non-linear stochastic distributed parameter system by discrete-time models" @default.
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- W2055705969 doi "https://doi.org/10.1080/00207729108910752" @default.
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