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Exponential Stability for Impulsive BAM Neural Networks with Time-Varying Delays and Reaction-Diffusion Terms

Advances in Difference Equations volume 2007, Article number: 078160 (2007) Cite this article

Abstract

Impulsive bidirectional associative memory neural network model with time-varying delays and reaction-diffusion terms is considered. Several sufficient conditions ensuring the existence, uniqueness, and global exponential stability of equilibrium point for the addressed neural network are derived by M-matrix theory, analytic methods, and inequality techniques. Moreover, the exponential convergence rate index is estimated, which depends on the system parameters. The obtained results in this paper are less restrictive than previously known criteria. Two examples are given to show the effectiveness of the obtained results.

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Authors and Affiliations

  1. Department of Mathematics, Chongqing Jiaotong University, Chongqing, 400074, China

    Qiankun Song

  2. Department of Mathematics, Southeast University, Nanjing, 210096, China

    Jinde Cao

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  1. Qiankun Song
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  2. Jinde Cao
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Correspondence to Qiankun Song.

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Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License (https://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Song, Q., Cao, J. Exponential Stability for Impulsive BAM Neural Networks with Time-Varying Delays and Reaction-Diffusion Terms. Adv Differ Equ 2007, 078160 (2007). https://doi.org/10.1155/2007/78160

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  • DOI: https://doi.org/10.1155/2007/78160

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