Modeling method for nonlinear stochastic dynamic system based on neural network and extended Kalman filter

Zu Xu Qin Zu Xu Qin,Hong Yue Zhang Hong Yue Zhang

doi:10.1109/icit.1994.467035

Modeling method for nonlinear stochastic dynamic system based on neural network and extended Kalman filter

Zu Xu Qin Zu Xu Qin, Hong Yue Zhang Hong Yue Zhang

https://doi.org/10.1109/icit.1994.467035

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Publication Date: Dec 5, 1994

Citations: 1

Affiliation: Beihang University

#Nonlinear Stochastic Dynamic System #Dynamic Neural Network + Show 8 more

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Abstract

This paper presents a modelling method for nonlinear stochastic dynamic system (NSDS) modelling based on a neural network and an extended Kalman filter (EKP). Using this method, the data contaminated by noise can be filtered by the EKP. A dynamic neural network (DNN) which is a good approximation to the deterministic part of the NSDS can be obtained. Meanwhile the DNN can be used as a state estimator for the NSDS. >

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