Deakin University
Browse

File(s) under permanent embargo

A delay partitioning approach to delay-dependent stability analysis for neutral type neural networks with discrete and distributed delays

Version 2 2024-06-13, 09:17
Version 1 2023-10-26, 03:21
journal contribution
posted on 2024-06-13, 09:17 authored by S Lakshmanan, JH Park, HY Jung, OM Kwon, R Rakkiyappan
This paper is concerned with the stability analysis of neutral type neural networks with discrete and distributed delays. Some improved delay-dependent stability results are established by using a delay partitioning approach for the networks. By employing a new type of Lyapunov-Krasovskii functionals, new delay-dependent stability criteria are derived. All the criteria are expressed in terms of linear matrix inequalities (LMIs), which can be solved efficiently by using standard convex optimization algorithms. Finally, numerical examples are given to illustrate the less conservatism of the proposed method.

History

Journal

Neurocomputing

Volume

111

Pagination

81-89

Location

Amsterdam, The Netherlands

ISSN

0925-2312

eISSN

1872-8286

Language

eng

Copyright notice

2013, Elsevier

Publisher

Elsevier

Usage metrics

    Research Publications

    Categories

    No categories selected

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC