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This paper deals with the state filtering problem of nonlinear state-space functions with partial parameters unknown. A novel filtering algorithm is proposed based on a modified maximum likelihood method. Using a new likelihood probabilistic function, we obtain a two-stages strategy of Expectation and Maximization (EM) with the help of Monte Carlo method. The convergence of EM parameter updating strategy...
This article presents a method to build a T-S fuzzy model based on Generalized Dynamic Fuzzy Neural Network (GD-FNN) of Elliptical Basis Function in order to solve the problem of ship motion model's uncertainty and nonlinearity. The proposed method needs neither prior fuzzy neural networks structure knowledge nor prior training phase, it can be used to build the nonlinear and uncertain part through...
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