Analysis of ℒ 2-ℒ stability for multilayer hopfield neural networks

Research output: Contribution to journalArticlepeer-review

Abstract

In this paper, we propose some new conditions on ℒ 2 - ℒ stability of multilayer Hopfield neural networks. These sufficient conditions are represented based on matrix norm and linear matrix inequality (LMI). Under these conditions, multilayer Hopfield neural networks reduce the effect of external input on the state vector to a predefined level. Moreover, the proposed conditions ensure asymptotic stability for multilayer Hopfield neural networks without external input. Dynamic Publishers, Inc.

Original languageEnglish
Pages (from-to)111-118
Number of pages8
JournalNeural, Parallel and Scientific Computations
Volume20
Issue number1
Publication statusPublished - 2012 Mar
Externally publishedYes

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Computer Networks and Communications
  • Artificial Intelligence
  • Applied Mathematics

Fingerprint

Dive into the research topics of 'Analysis of ℒ 2-ℒ stability for multilayer hopfield neural networks'. Together they form a unique fingerprint.

Cite this