Neural Computing and Applications

, Volume 21, Issue 7, pp 1593–1616 | Cite as

Global robust asymptotic stability analysis of uncertain switched Hopfield neural networks with time delay in the leakage term

  • P. Balasubramaniam
  • V. Vembarasan
  • R. Rakkiyappan
Original Article

Abstract

This paper deals with the problem of delay-dependent global robust asymptotic stability of uncertain switched Hopfield neural networks (USHNNs) with discrete interval and distributed time-varying delays and time delay in the leakage term. Some Lyapunov––Krasovskii functionals are constructed and the linear matrix inequality (LMI) approach are employed to derive some delay-dependent global robust stability criteria which guarantee the global robust asymptotic stability of the equilibrium point for all admissible parametric uncertainties. The proposed results that do not require the boundedness, differentiability, and monotonicity of the activation functions. Moreover, the stability behavior of USHNNs is very sensitive to the time delay in the leakage term. It can be easily checked via the LMI control toolbox in Matlab. In the absence of leakage delay, the results obtained are also new results. Finally, nine numerical examples are given to show the effectiveness of the proposed results.

Keywords

Switched systems Hopfield neural networks Linear matrix inequality Mixed interval time-varying delay Leakage delay 

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Copyright information

© Springer-Verlag London Limited 2011

Authors and Affiliations

  • P. Balasubramaniam
    • 1
  • V. Vembarasan
    • 1
  • R. Rakkiyappan
    • 2
  1. 1.Department of MathematicsGandhigram Rural UniversityGandhigramIndia
  2. 2.Department of MathematicsBharathiyar UniversityCoimbatoreIndia

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