Delay-dependent Stability Criteria for Uncertain Stochastic Neural Networks with Interval Time-varying Delays

Oh Min Kwon; Ju Hyun Park; Sang Moon Lee

Delay-dependent Stability Criteria for Uncertain Stochastic Neural Networks with Interval Time-varying Delays

Oh Min Kwon, Ju Hyun Park, Sang Moon Lee

School of Electronics Engineering

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

2 Scopus citations

Abstract

In this paper, the problem of global asymptotic stability of uncertain stochastic neural networks with delay is considered. The delay is assumed to be time-varying and belong to a given interval. Based on the Lyapunov stability theory, new delay-dependent stability criteria for the system is derived in terms of LMI(linear matrix inequality). Three numerical examples are given to show the effectiveness of proposed method.

Original language	English
Pages (from-to)	2066-2073
Number of pages	8
Journal	Transactions of the Korean Institute of Electrical Engineers
Volume	57
Issue number	11
State	Published - Nov 2008

Keywords

Interval time-varying delays
Linear matrix inequalities
Lyapunov method
Stochastic neural networks

Cite this

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abstract = "In this paper, the problem of global asymptotic stability of uncertain stochastic neural networks with delay is considered. The delay is assumed to be time-varying and belong to a given interval. Based on the Lyapunov stability theory, new delay-dependent stability criteria for the system is derived in terms of LMI(linear matrix inequality). Three numerical examples are given to show the effectiveness of proposed method.",

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N2 - In this paper, the problem of global asymptotic stability of uncertain stochastic neural networks with delay is considered. The delay is assumed to be time-varying and belong to a given interval. Based on the Lyapunov stability theory, new delay-dependent stability criteria for the system is derived in terms of LMI(linear matrix inequality). Three numerical examples are given to show the effectiveness of proposed method.

AB - In this paper, the problem of global asymptotic stability of uncertain stochastic neural networks with delay is considered. The delay is assumed to be time-varying and belong to a given interval. Based on the Lyapunov stability theory, new delay-dependent stability criteria for the system is derived in terms of LMI(linear matrix inequality). Three numerical examples are given to show the effectiveness of proposed method.

KW - Interval time-varying delays

KW - Linear matrix inequalities

KW - Lyapunov method

KW - Stochastic neural networks

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Delay-dependent Stability Criteria for Uncertain Stochastic Neural Networks with Interval Time-varying Delays

Abstract

Keywords

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