On robust exponential stability of delayed neural networks

2004 ◽  
Author(s):  
Chuandong Li ◽  
Xiaofeng Liao
Keyword(s):  
Neural Networks ◽  
Exponential Stability ◽  
Robust Exponential Stability ◽  
Delayed Neural Networks

scholarly journals Novel Robust Exponential Stability of Markovian Jumping Impulsive Delayed Neural Networks of Neutral-Type with Stochastic Perturbation

2016 ◽  
Vol 2016 ◽  
pp. 1-20
Author(s):  
Yang Fang ◽  
Kelin Li ◽  
Yunqi Yan
Keyword(s):  
Neural Networks ◽  
Exponential Stability ◽  
Neutral Type ◽  
Stochastic Perturbation ◽  
Linear Matrix ◽  
Stochastic Neural Networks ◽  
Time Varying ◽  
Markovian Jumping ◽  
Robust Exponential Stability ◽  
Delayed Neural Networks

The robust exponential stability problem for a class of uncertain impulsive stochastic neural networks of neutral-type with Markovian parameters and mixed time-varying delays is investigated. By constructing a proper exponential-type Lyapunov-Krasovskii functional and employing Jensen integral inequality, free-weight matrix method, some novel delay-dependent stability criteria that ensure the robust exponential stability in mean square of the trivial solution of the considered networks are established in the form of linear matrix inequalities (LMIs). The proposed results do not require the derivatives of discrete and distributed time-varying delays to be 0 or smaller than 1. Moreover, the main contribution of the proposed approach compared with related methods lies in the use of three types of impulses. Finally, two numerical examples are worked out to verify the effectiveness and less conservativeness of our theoretical results over existing literature.

On exponential stability of delayed neural networks with a general class of activation functions

2002 ◽  
Vol 298 (2-3) ◽  
pp. 122-132 ◽  
Author(s):  
Changyin Sun ◽  
Kanjian Zhang ◽  
Shumin Fei ◽  
Chun-Bo Feng
Keyword(s):  
Neural Networks ◽  
Exponential Stability ◽  
General Class ◽  
Activation Functions ◽  
Delayed Neural Networks
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