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Exponential Stability of a Class of High-Order Hybrid Neural Networks

  • Qian Ye
  • Baotong Cui
  • Xuyang Lou
  • Ke Lou
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7389)

Abstract

This paper considers a generalized model of high-order hybrid neural networks with time-varying delays and impulsive effects is considered. By establishing an impulsive delay differential inequality and using the method of Lyapunov functions, we investigate the global exponential stability of high-order dynamical neural networks with time-varying delays and impulsive effects. Our sufficient conditions ensuring the stability are dependent on delays and impulses and show delay and impulsive effects on the stability of neural networks.

Keywords

Exponential stability high-order hybrid neural networks Lyapunov function impulse effects 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Qian Ye
    • 1
  • Baotong Cui
    • 1
  • Xuyang Lou
    • 1
  • Ke Lou
    • 1
  1. 1.Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education)Jiangnan UniversityWuxiChina

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