Novel delay-dependent stability criterion for delayed neural networks

2008 ◽  
Vol 41 (2) ◽  
pp. 5429-5432
Author(s):  
Bin Yang ◽  
Hong WangYanhong ◽  
Jiang Min Han
Keyword(s):  
Neural Networks ◽  
Stability Criterion ◽  
Delayed Neural Networks ◽  
Delay Dependent ◽  
Delay Dependent Stability

Delay-dependent stability criterion for delayed Hopfield neural networks

2009 ◽  
Vol 39 (5) ◽  
pp. 2133-2137 ◽  
Author(s):  
Yanhong Jiang ◽  
Bin Yang ◽  
Jincheng Wang ◽  
Cheng Shao
Keyword(s):  
Neural Networks ◽  
Stability Criterion ◽  
Hopfield Neural Networks ◽  
Delay Dependent ◽  
Delay Dependent Stability

New Delay-Dependent Stability Criteria for Recurrent Neural Networks with Time-Varying Delays

2014 ◽  
Vol 513-517 ◽  
pp. 922-926
Author(s):  
Ze Rong Ren ◽  
Xiang Jun Xie
Keyword(s):  
Neural Networks ◽  
Stability Criterion ◽  
Recurrent Neural Networks ◽  
Linear Matrix ◽  
Time Varying ◽  
Matrix Inequalities ◽  
Neuron Activation ◽  
Delay Dependent ◽  
Delay Partitioning ◽  
Delay Dependent Stability

This paper is concerned with the problem of delay-dependent asymptotic stability criterion for recurrent neural networks with time-varying delays. A new Lyapunov functional is introduced by considering the information of neuron activation functions adequately. By using the improved delay-partitioning method and reciprocally convex approach, a less conservative stability criterion is obtained in terms of linear matrix inequalities (LMIs). A numerical example is finally given to illustrate the effectiveness of the derived method.

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