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Dynamical Behavior of Nonautonomous Stochastic Reaction–Diffusion Neural-Network Models.

Authors :
Wei, Tengda
Lin, Ping
Zhu, Quanxin
Wang, Linshan
Wang, Yangfan
Source :
IEEE Transactions on Neural Networks & Learning Systems; May2019, Vol. 30 Issue 5, p1575-1580, 6p
Publication Year :
2019

Abstract

This brief investigates nonautonomous stochastic reaction–diffusion neural-network models with S-type distributed delays. First, the existence and uniqueness of mild solution are studied under the Lipschitz condition without the linear growth condition. Due to the existence of a nonautonomous reaction–diffusion term and the infinite dimensional Wiener process, the criteria for the well-posedness of the models are established based on the evolution system theory. Then, the S-type distributed delay, which is an infinite delay, is handled by the truncation method, and sufficient conditions for the global exponential stability are obtained by constructing a simple Lyapunov–Krasovskii functional candidate. Finally, neural-network examples and an illustrative example are given to show the applications of the obtained results. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
2162237X
Volume :
30
Issue :
5
Database :
Complementary Index
Journal :
IEEE Transactions on Neural Networks & Learning Systems
Publication Type :
Periodical
Accession number :
136117568
Full Text :
https://doi.org/10.1109/TNNLS.2018.2869028