Stochastic stability analysis for delayed neural networks of neutral type with Markovian jump parameters

2009 ◽  
Vol 39 (5) ◽  
pp. 2188-2197 ◽  
Author(s):  
Xuyang Lou ◽  
Baotong Cui
Keyword(s):  
Neural Networks ◽  
Stability Analysis ◽  
Stochastic Stability ◽  
Neutral Type ◽  
Markovian Jump ◽  
Delayed Neural Networks ◽  
Markovian Jump Parameters ◽  
Stochastic Stability Analysis

scholarly journals Robust Stochastic Stability Analysis for Uncertain Neutral-Type Delayed Neural Networks Driven by Wiener Process

2012 ◽  
Vol 2012 ◽  
pp. 1-12 ◽  
Author(s):  
Weiwei Zhang ◽  
Linshan Wang
Keyword(s):  
Neural Networks ◽  
Wiener Process ◽  
Stochastic Stability ◽  
Neutral Type ◽  
Linear Matrix ◽  
Delayed Neural Networks ◽  
System A ◽  
Inequality Technique ◽  
Stochastic Stability Analysis ◽  
The Stability

The robust stochastic stability for a class of uncertain neutral-type delayed neural networks driven by Wiener process is investigated. By utilizing the Lyapunov-Krasovskii functional and inequality technique, some sufficient criteria are presented in terms of linear matrix inequality (LMI) to ensure the stability of the system. A numerical example is given to illustrate the applicability of the result.

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