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Global Exponential Anti-synchronization of Coupled Memristive Chaotic Neural Networks with Time-Varying Delays

  • Zheng Yan
  • Shuzhan Bi
  • Xijun Xue
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9377)

Abstract

This paper investigates the problem of global exponential anti-synchronization of a class of memristive chaotic neural networks with time-varying delays. First, a memrsitive neural network is modeled. Then, considering the state-dependent properties of the memristor, a new fuzzy model employing parallel distributed compensation (PDC) provides a new way to analyze the complicated memristive neural networks with only two subsystems. And the controller is dependent on the output of the system in the case of packed circuits. An illustrative example is also presented to show the effectiveness of the results.

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© Springer International Publishing Switzerland 2015

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Authors and Affiliations

  1. 1.Shannon LabHuawei Technologies Co., Ltd.BeijingChina

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