New augmented Lyapunov-Krasovskii functional approach to stability analysis of neural networks with time-varying delays

O. M. Kwon; Ju H. Park; S. M. Lee; E. J. Cha

doi:10.1007/s11071-013-1122-2

New augmented Lyapunov-Krasovskii functional approach to stability analysis of neural networks with time-varying delays

O. M. Kwon, Ju H. Park, S. M. Lee, E. J. Cha

School of Electronics Engineering

Research output: Contribution to journal › Article › peer-review

100 Scopus citations

Abstract

This paper is concerned with the problem of stability analysis for neural networks with time-varying delays. By constructing a newly augmented Lyapunov functional and some novel techniques, delay-dependent criteria to guarantee the asymptotic stability of the concerned networks are derived in terms of linear matrix inequalities (LMIs). The improvement of feasible region of the proposed criteria comparing with the previous works is shown by two numerical examples.

Original language	English
Pages (from-to)	221-236
Number of pages	16
Journal	Nonlinear Dynamics
Volume	76
Issue number	1
DOIs	https://doi.org/10.1007/s11071-013-1122-2
State	Published - Apr 2014

Keywords

Asymptotic stability
Lyapunov method
Neural networks
Time-varying delays

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abstract = "This paper is concerned with the problem of stability analysis for neural networks with time-varying delays. By constructing a newly augmented Lyapunov functional and some novel techniques, delay-dependent criteria to guarantee the asymptotic stability of the concerned networks are derived in terms of linear matrix inequalities (LMIs). The improvement of feasible region of the proposed criteria comparing with the previous works is shown by two numerical examples.",

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New augmented Lyapunov-Krasovskii functional approach to stability analysis of neural networks with time-varying delays

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Keywords

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