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Input-to-State Stability of Stochastic Memristive Neural Networks with Time-Varying Delay

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  • Xu Y. Lou
  • Qian Ye

Abstract

This paper is concerned with the input-to-state stability problem of a class of memristive neural networks. We consider the neural networks that take into account both the stochastic effects and time-varying delay, and introduce the notions of meansquare exponential input-to-state stability. Using the stochastic analysis theory and Itô formula for stochastic differential equations, we establish sufficient conditions for both mean-square exponential input-to-state stability and mean-square exponential stability. Numerical simulations are also provided to demonstrate the theoretical results.

Suggested Citation

  • Xu Y. Lou & Qian Ye, 2015. "Input-to-State Stability of Stochastic Memristive Neural Networks with Time-Varying Delay," Mathematical Problems in Engineering, Hindawi, vol. 2015, pages 1-8, February.
    • Handle: RePEc:hin:jnlmpe:140857
    DOI: 10.1155/2015/140857
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