Linear matrix inequality approach to passive filtering for delayed neural networks

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

The delay-dependent passive filtering problem is studied for delayed neural networks. A new delay-dependent passive filter is proposed such that the filtering error system is asymptotically stable and passive from the external disturbance to the output error. The desired filter matrix gain is characterized in terms of the solution to a linear matrix inequality (LMI), which can be easily facilitated by using some standard numerical packages. An illustrative example is given to demonstrate the effectiveness of the proposed filter.

Original languageEnglish
Pages (from-to)1040-1047
Number of pages8
JournalProceedings of the Institution of Mechanical Engineers. Part I: Journal of Systems and Control Engineering
Volume224
Issue number8
DOIs
Publication statusPublished - 2010 Dec 1
Externally publishedYes

Fingerprint

Linear matrix inequalities
Neural networks
Passive filters

Keywords

  • delayed neural networks
  • linear matrix inequality (LMI)
  • Lyapunov-Krasovskii stability theory
  • passive filtering

ASJC Scopus subject areas

  • Mechanical Engineering
  • Control and Systems Engineering

Cite this

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