doi: 10.7763/IJAPM.2014.V4.282
Global Exponential Stability of Impulsive Cohen-Grossberg-Type BAM Neural Networks with Time-Varying and Distributed Delays
Haydar Akça
1
,
Jamal Benbourenane
1
,
Valéry Covachev
2
- 1 the Applied Sciences and
- 2 the Bulgarian Academy of Sciences, Sofia, Bulgaria
Abstract
The purpose of this paper is to investigate the global exponential stability of a class of impulsive bidirectional associative memories (BAM) neural networks that possesses Cohen-Grossberg dynamics. By constructing and using some inequality techniques and a fixed point theorem sufficient conditions are obtained to ensure the existence and global exponential stability of the solutions for impulsive Cohen-Grossberg neural networks with time delays and distributed delays.
Keywords
- Cohen-grossberg neural networks
- impulses
- globally exponential stability
- time delay
- distributed delay
How to Cite
Haydar Akça, Jamal Benbourenane, and Valéry Covachev, "Global Exponential Stability of Impulsive Cohen-Grossberg-Type BAM Neural Networks with Time-Varying and Distributed Delays," International Journal of Applied Physics and Mathematics, vol. 4, no. 3, pp. 196-200, 2014. https://doi.org/ 10.7763/IJAPM.2014.V4.282
Copyright & License
Copyright © 2014 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).