Robust Control of Uncertain Stochastic Recurrent Neural Networks with Time-varying Delay

2007 ◽  
Vol 26 (2) ◽  
pp. 101-119 ◽  
Author(s):  
Wenwu Yu ◽  
Jinde Cao
2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Lei Ding ◽  
Hong-Bing Zeng ◽  
Wei Wang ◽  
Fei Yu

This paper investigates the stability of static recurrent neural networks (SRNNs) with a time-varying delay. Based on the complete delay-decomposing approach and quadratic separation framework, a novel Lyapunov-Krasovskii functional is constructed. By employing a reciprocally convex technique to consider the relationship between the time-varying delay and its varying interval, some improved delay-dependent stability conditions are presented in terms of linear matrix inequalities (LMIs). Finally, a numerical example is provided to show the merits and the effectiveness of the proposed methods.


2014 ◽  
Vol 138 ◽  
pp. 383-391 ◽  
Author(s):  
Meng-Di Ji ◽  
Yong He ◽  
Chuan-Ke Zhang ◽  
Min Wu

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