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Passivity analysis of memristor-based complex-valued neural networks with time-varying delays

Version 2 2024-06-06, 11:54
Version 1 2015-08-27, 15:03
journal contribution
posted on 2024-06-06, 11:54 authored by G Velmurugan, R Rakkiyappan, L Shanmugam
In this paper, the model of memristor-based complex-valued neural networks (MCVNNs) with time-varying delays is established and the problem of passivity analysis for MCVNNs is considered and extensively investigated. The analysis in this paper employs results from the theory of differential equations with discontinuous right-hand side as introduced by Filippov. By employing the appropriate Lyapunov–Krasovskii functional, differential inclusion theory and linear matrix inequality (LMI) approach, some new sufficient conditions for the passivity of the given MCVNNs are obtained in terms of both complex-valued and real-value LMIs, which can be easily solved by using standard numerical algorithms. Numerical examples are provided to illustrate the effectiveness of our theoretical results.

History

Journal

Neural processing letters

Volume

42

Pagination

517-540

Location

N.Y. United States

ISSN

1370-4621

eISSN

1573-773X

Language

eng

Publication classification

C Journal article, C1.1 Refereed article in a scholarly journal

Copyright notice

2014, Springer Science & Business Media

Issue

3

Publisher

Springer New York