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

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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Correspondence to Qiankun Song.

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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

Keywords

  • Neural Network
  • Partial Differential Equation
  • Ordinary Differential Equation
  • Functional Equation
  • Equilibrium Point