Mean Square Exponential Stability of Stochastic Delayed Static Neural Networks with Markovian Switching

  • He HuangEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9377)


This paper is concerned with globally exponential stability in the mean square of stochastic static neural networks with Markovian switching and time delay. Firstly, the mathematical model of this kind of recurrent neural networks is established by taking information latching and noise disturbance into consideration. Then, a stability condition, which is dependent on both time delay and system mode, is presented in terms of linear matrix inequalities. Based on it, the maximum value of the exponential decay rate can be efficiently found by solving a convex optimization problem.


Static neural networks stability time delay Markovian switching exponential decay rate convex optimization 


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© Springer International Publishing Switzerland 2015

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Authors and Affiliations

  1. 1.School of Electronics and Information EngineeringSoochow UniversitySuzhouP. R. China

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