New conditions for stability of switched Hopfield neural networks

Research output: Contribution to journalArticle

Abstract

In this paper, the input/output-to-state stability (IOSS) concept is used to derive new stability conditions for switched Hopfield neural networks. Based on matrix norm and linear matrix inequality (LMI), the proposed stability conditions ensure input/outputto- state stability for external input vector. We also present the conditions for asymptotic stability of switched Hopfield neural networks without external input vector.

Original languageEnglish
Pages (from-to)71-78
Number of pages8
JournalCommunications on Applied Nonlinear Analysis
Volume19
Issue number1
Publication statusPublished - 2012 Mar 29
Externally publishedYes

Fingerprint

Hopfield neural networks
Hopfield Neural Network
Stability Condition
Matrix Norm
Asymptotic Stability
Matrix Inequality
Linear Inequalities
Output
Asymptotic stability
Linear matrix inequalities
Concepts

Keywords

  • Input/output-to-state stability (IOSS)
  • Linear matrix inequality (LMI)
  • Switched Hopfield neural networks

ASJC Scopus subject areas

  • Analysis
  • Applied Mathematics

Cite this

New conditions for stability of switched Hopfield neural networks. / Ahn, Choon Ki.

In: Communications on Applied Nonlinear Analysis, Vol. 19, No. 1, 29.03.2012, p. 71-78.

Research output: Contribution to journalArticle

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