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.
Highlights
The bidirectional associative memory (BAM) neural network model was first introduced by Kosko [1]
Some results concerning the dynamical behavior of BAM neural networks with
To the best of our knowledge, few authors have studied the stability of impulsive BAM neural network model with both time-varying delays and reaction-diffusion terms
Summary
The bidirectional associative memory (BAM) neural network model was first introduced by Kosko [1] This class of neural networks has been successfully applied to pattern recognition, signal and image processing, artificial intelligence due to its generalization of the single-layer auto-associative Hebbian correlation to two-layer pattern-matched heteroassociative circuits. To the best of our knowledge, few authors have studied the stability of impulsive BAM neural network model with both time-varying delays and reaction-diffusion terms. Motivated by the above discussions, the objective of this paper is to give some sufficient conditions ensuring the existence, uniqueness, and global exponential stability of equilibrium point for impulsive BAM neural networks with time-varying delays and reactiondiffusion terms, without assuming the boundedness, monotonicity, and differentiability on these activation functions. Our methods, which do not make use of Lyapunov functional, are simple and valid for the stability analysis of impulsive BAM neural networks with time-varying or constant delays
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
