Stability for a retarded impulsive Cohen–Grossberg BAM neural network system

ABSTRACT

In this paper, an impulsive Cohen-Grossberg bidirectional associative neural network with both time-varying and distributed delays is examined. Novel sufficient conditions for deriving stability with a desired rate, including the exponential one, are obtained. We consider a large class of admissible kernels encompassing the existing ones. Our findings cover the existing stability results in the literature. Finally, a numerical example is given for the validation of the theoretical outcomes.

KEYWORDS:

• General stability
• Cohen-Grossberg
• bidirectional associative memory
• time-varying delay
• distributed delay
• impulse

Data availability

The data supporting the results of this study in the example is incorporated.

Acknowledgments

The second author would like to thank King Fahd University of Petroleum and Minerals for its continuous support through project SB 181008.

The authors would like to thank the anonymous reviewers and the editor for their constructive comments, which significantly improved the quality of this manuscript.

Disclosure statement

No potential conflict of interest was reported by the author(s).