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• W1607401020 abstract "This paper presents a new theoretical design of how an optimal synchronization is achieved for stochastic coupled neural networks with respect to a risk sensitive optimality criterion. The approach is rigorously developed by using the Hamilton-Jacobi-Bellman equation, Lyapunov technique, and inverse optimality, to obtain a risk sensitive state feedback controller, which guarantees that the chaotic drive network synchronizes with the chaotic response network influenced by uncertain noise signals, with an eye on a given risk sensitivity parameter. Finally, a numerical example is given to demonstrate the effectiveness of the proposed approach." @default.
• W1607401020 created "2016-06-24" @default.
• W1607401020 creator A5087235476 @default.
• W1607401020 date "2015-05-01" @default.
• W1607401020 modified "2023-09-25" @default.
• W1607401020 title "Risk sensitive optimal synchronization of coupled stochastic neural networks with chaotic phenomena" @default.
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• W1607401020 doi "https://doi.org/10.1109/cisda.2015.7208632" @default.
• W1607401020 hasPublicationYear "2015" @default.
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