A new stability criterion for discrete-time neural networks: Nonlinear spectral radius

K. L. Mak, J. G. Peng, Z. B. Xu, Ka Fai Cedric Yiu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

14 Citations (Scopus)

Abstract

In this paper, the exponential stability of nonlinear discrete-time systems is studied. A novel notion of nonlinear spectral radius is defined. Under the assumption of Lipschitz continuity for the activation function, the developed approach is applied to stability analysis of discrete-time neural networks. A series of sufficient conditions for global exponential stability of the neural networks are established and an estimate of the exponential decay rate is also derived for each case.
Original languageEnglish
Pages (from-to)424-436
Number of pages13
JournalChaos, Solitons and Fractals
Volume31
Issue number2
DOIs
Publication statusPublished - 1 Jan 2007
Externally publishedYes

ASJC Scopus subject areas

  • Statistical and Nonlinear Physics

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