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A Method for Tracking the Time Evolution of Steady-State Evoked Potentials
Published on: May 25, 2019
Exponential input-to-state stability of recurrent neural networks with multiple time-varying delays
Zhichun Yang1, Weisong Zhou2, Tingwen Huang3
1Department of Mathematics, Key Laboratory for Optimization and Control of Ministry of Education, Chongqing Normal University, Chongqing, 400047 China.
Abstract:
In this paper, input-to-state stability problems for a class of recurrent neural networks model with multiple time-varying delays are concerned with. By utilizing the Lyapunov-Krasovskii functional method and linear matrix inequalities techniques, some sufficient conditions ensuring the exponential input-to-state stability of delayed network systems are firstly obtained. Two numerical examples and its simulations are given to illustrate the efficiency of the derived results.
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