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Neural Computing and Applications

, Volume 28, Issue 4, pp 775–782 | Cite as

Impulsive stabilization and synchronization of Hopfield-type neural networks with impulse time window

  • Yinghua Zhou
  • Chuandong LiEmail author
  • Tingwen Huang
  • Xin Wang
Original Article

Abstract

This paper studies the problem of global exponential stabilization and synchronization for impulsive Hopfield-type neural networks with impulse time window. By using the stability theory of impulsive dynamical systems, some sufficient conditions guaranteeing the global exponential stabilization and synchronization of Hopfield-type NNs are derived. The main innovation embodies that the impulsive instants are no longer limited at fixed instants, but suggested to be at some certain time intervals, named by impulse time windows. We shall show that impulses occurring randomly in impulse time windows can still stabilize and/or synchronize the considered neural networks under certain suitable assumptions. Two numerical examples are also given to illustrate the effectiveness of theoretical results.

Keywords

Hopfield-type neural networks (NNs) Impulsive stabilization Synchronization Impulse time window 

Notes

Acknowledgments

This research is supported by the Natural Science Foundation of China (Grant No. 63174078), the Fundamental Research Funds for the Central Universities (XDJK2012C069), and NPRP grant # NPRP 4-1162-1-181 from the Qatar National Research Fund (a member of Qatar Foundation).

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Copyright information

© The Natural Computing Applications Forum 2015

Authors and Affiliations

  • Yinghua Zhou
    • 1
  • Chuandong Li
    • 1
    Email author
  • Tingwen Huang
    • 2
  • Xin Wang
    • 1
  1. 1.College of Electronic and Information EngineeringSouthwest UniversityChongqingChina
  2. 2.Department of MathematicsTexas A&M University at QatarDohaQatar

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