Stability analysis for uncertain switched delayed complex-valued neural networks

Nallappan Gunasekaran, Guisheng Zhai

Research output: Contribution to journalArticle

Abstract

The main concern of the paper is to address the stability of switched delayed complex-valued neural networks with uncertainties. Based on suitable Lyapunov–Krasovskii functional (LKF) and proposed lemma, the delay-dependent sufficient conditions are derived to guarantee the asymptotical stability of considered uncertain switched complex-valued neural networks. The derived sufficient conditions in terms of linear matrix inequalities are solved with the help of YALMIP toolbox in MATLAB. Two numerical examples are provided to ensure the effectiveness of the theoretical conditions.

Original languageEnglish
JournalNeurocomputing
DOIs
Publication statusAccepted/In press - 2019 Jan 1

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Neural networks
Linear matrix inequalities
MATLAB
Uncertainty

Keywords

  • Complex-valued neural networks
  • Integral inequality
  • Linear matrix inequality
  • Lyapunov method
  • Stability

ASJC Scopus subject areas

  • Computer Science Applications
  • Cognitive Neuroscience
  • Artificial Intelligence

Cite this

Stability analysis for uncertain switched delayed complex-valued neural networks. / Gunasekaran, Nallappan; Zhai, Guisheng.

In: Neurocomputing, 01.01.2019.

Research output: Contribution to journalArticle

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