A new stability criterion for bidirectional associative memory neural networks of neutral-type

Ju H. Park; C. H. Park; O. M. Kwon; S. M. Lee

doi:10.1016/j.amc.2007.10.032

A new stability criterion for bidirectional associative memory neural networks of neutral-type

Ju H. Park, C. H. Park, O. M. Kwon, S. M. Lee

School of Electronics Engineering

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

182 Scopus citations

Abstract

In the paper, the global asymptotic stability of equilibrium is considered for continuous bidirectional associative memory (BAM) neural networks of neutral type by using the Lyapunov method. A new stability criterion is derived in terms of linear matrix inequality (LMI) to ascertain the global asymptotic stability of the BAM. The LMI can be solved easily by various convex optimization algorithms. A numerical example is illustrated to verify our result.

Original language	English
Pages (from-to)	716-722
Number of pages	7
Journal	Applied Mathematics and Computation
Volume	199
Issue number	2
DOIs	https://doi.org/10.1016/j.amc.2007.10.032
State	Published - 1 Jun 2008

Keywords

BAM neural network
Delay
Global stability
Linear matrix inequality
Lyapunov method

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10.1016/j.amc.2007.10.032

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abstract = "In the paper, the global asymptotic stability of equilibrium is considered for continuous bidirectional associative memory (BAM) neural networks of neutral type by using the Lyapunov method. A new stability criterion is derived in terms of linear matrix inequality (LMI) to ascertain the global asymptotic stability of the BAM. The LMI can be solved easily by various convex optimization algorithms. A numerical example is illustrated to verify our result.",

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AU - Kwon, O. M.

AU - Lee, S. M.

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AB - In the paper, the global asymptotic stability of equilibrium is considered for continuous bidirectional associative memory (BAM) neural networks of neutral type by using the Lyapunov method. A new stability criterion is derived in terms of linear matrix inequality (LMI) to ascertain the global asymptotic stability of the BAM. The LMI can be solved easily by various convex optimization algorithms. A numerical example is illustrated to verify our result.

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KW - Delay

KW - Global stability

KW - Linear matrix inequality

KW - Lyapunov method

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A new stability criterion for bidirectional associative memory neural networks of neutral-type

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Keywords

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