Dynamical behaviors of reaction–diffusion fuzzy neural networks with mixed delays and general boundary conditions

2011 ◽  
Vol 16 (2) ◽  
pp. 993-1001 ◽  
Author(s):  
Teng Lv ◽  
Ping Yan
Keyword(s):  
Neural Networks ◽  
Boundary Conditions ◽  
Reaction Diffusion ◽  
Fuzzy Neural Networks ◽  
General Boundary ◽  
Mixed Delays ◽  
General Boundary Conditions ◽  
Dynamical Behaviors ◽  
Fuzzy Neural

scholarly journals Stability Analysis for Discrete-Time Stochastic Fuzzy Neural Networks with Mixed Delays

2019 ◽  
Vol 2019 ◽  
pp. 1-13
Author(s):  
YaJun Li ◽  
Quanxin Zhu
Keyword(s):  
Neural Networks ◽  
Discrete Time ◽  
Sufficient Conditions ◽  
Fuzzy Neural Networks ◽  
Linear Matrix ◽  
Mixed Delays ◽  
The Novel ◽  
Free Weight ◽  
Fuzzy Neural ◽  
The Stability

This paper is concerned with the stability problem of a class of discrete-time stochastic fuzzy neural networks with mixed delays. New Lyapunov-Krasovskii functions are proposed and free weight matrices are introduced. The novel sufficient conditions for the stability of discrete-time stochastic fuzzy neural networks with mixed delays are established in terms of linear matrix inequalities (LMIs). Finally, numerical examples are given to illustrate the effectiveness and benefits of the proposed method.

scholarly journals Synchronization of Chaotic Delayed Fuzzy Neural Networks under Impulsive and Stochastic Perturbations

2013 ◽  
Vol 2013 ◽  
pp. 1-14 ◽  
Author(s):  
Bing Li ◽  
Qiankun Song
Keyword(s):  
Neural Networks ◽  
Cellular Neural Networks ◽  
Fuzzy Neural Networks ◽  
Itô’S Formula ◽  
Mixed Delays ◽  
Fuzzy Cellular Neural Networks ◽  
Stochastic Perturbations ◽  
Synchronization Problem ◽  
Ito’S Formula ◽  
Fuzzy Neural

The synchronization problem of chaotic fuzzy cellular neural networks with mixed delays is investigated. By an impulsive integrodifferential inequality and the Itô's formula, some sufficient criteria to synchronize the networks under both impulsive and stochastic perturbations are obtained. The example and simulations are given to demonstrate the efficiency and advantages of the proposed results.

Stability Analysis of Stochastic Fuzzy Neural Networks with Time-Varying Delays and Reaction–Diffusion Terms

2013 ◽  
Vol 33 (3) ◽  
pp. 713-732
Author(s):  
Hongyu Zhang ◽  
Chenhui Zhou ◽  
Hongbin Zhang ◽  
Qichong Tian ◽  
Gang Wang
Keyword(s):  
Neural Networks ◽  
Stability Analysis ◽  
Reaction Diffusion ◽  
Fuzzy Neural Networks ◽  
Time Varying ◽  
Fuzzy Neural
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