Stability of Markovian jump neural networks with impulse control and time varying delays

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• 作者：Quanxin Zhu^a ; ^{zqx22@126.com} ; Jinde Cao^b ; ^{jdcao@seu.edu.cn}
• 关键词：Delayed recurrent neural network ; Time varying delay ; Impulse control ; Linear matrix inequality ; Exponential stability ; Markovian jump parameter
• 刊名：Nonlinear Analysis ; Real World Applications
• 出版年：2012
• 期刊代码：44_14681218
• 类别：mt
• 出版时间：October, 2012
• 卷：13
• 期：5
• 页码：2259-2270
• 文件大小：326 K

摘要

This paper is concerned with the stability of delayed recurrent neural networks with impulse control and Markovian jump parameters. The jumping parameters are modeled as a continuous-time, discrete-state Markov process. By applying the Lyapunov stability theory, Dynkin鈥檚 formula and linear matrix inequality technique, some new delay-dependent conditions are derived to guarantee the exponential stability of the equilibrium point. Moreover, three numerical examples and their simulations are given to show the less conservatism and effectiveness of the obtained results. In particular, the traditional assumptions on the differentiability of the time varying delays and the boundedness of their derivatives are removed since the time varying delays considered in this paper may not be differentiable, even not continuous.