Dynamic analysis for high-order Hopfield neural networks with leakage delay and impulsive effects

R. Rakkiyappan, C. Pradeep, A. Vinodkumar, Fathalla A. Rihan

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)

Abstract

This paper considers existence, uniqueness, and the global asymptotic stability for a class of High-order Hopfield neural networks with mixed delays and impulses. The mixed delays include constant delay in the leakage term (i.e., "leakage delay") and time-varying delays. Based on the Lyapunov stability theory, together with the linear matrix inequality approach and free-weighting matrix method, some less conservative delay-dependent sufficient conditions are presented for the global asymptotic stability of the equilibrium point of the considered neural networks. These conditions are expressed in terms of LMI and can be easily checked by MATLAB LMI toolbox. In addition, two numerical examples are given to illustrate the applicability of the result.

Original languageEnglish
Pages (from-to)55-73
Number of pages19
JournalNeural Computing and Applications
Volume22
Issue numberSUPPL.1
DOIs
Publication statusPublished - May 2013

Keywords

  • Impulsive high-order Hopfield neural networks
  • Leakage delays
  • Linear matrix inequality
  • Stability

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

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