Acta mathematica scientia,Series A

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Global Exponential Stability of Neural Networks’ Periodic Solution Involving Finite Distributed Delays with Periodic Inputs

1Xia Wenhua;2Deng Feiqi;1Luo Yiping   

  1. (1.Hunan Institute of Engineering, Hunan Xiantan 411101; 2.College of Automation Science and Engineering, South China University of Technology,
    Guangzhou 510640)
  • Received:2006-10-29 Revised:2008-07-15 Online:2009-02-25 Published:2009-02-25
  • Contact: Xia Wenhua

Abstract: Without assuming the boundedness, continuous, derivation of the active functions and the boundedness of the mean time-delay, the existence of a class of neural networks’ periodic solution involving distributed delays with periodic inputs is obtained by using the theory of coincidence degree and the knowledge of Dini derivative, when the active functions satisfy the Lipchitz condition and the relations of the interconnection matrix is an M-matrix.
Meanwhile, under the same conditions, the global exponential stability of neural networks’ periodic solution is obtained by employing Dini derivative and the analysis technique of inequality. Some existing conclusions are improved, extended and complemented. An example is also worked out to demonstrate the advantages of these results.

Key words: Neural network, Periodic solution, Continuously distributed time-delay, Global exponential stability.

CLC Number: 

  • 60F15
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