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.

Index Terms—Cohen-grossberg neural networks, impulses, globally exponential stability, time delay, distributed delay.

H. Akça and J. Benbourenane are with the Applied Sciences and Mathematics Department, College of Arts and Sciences, Abu Dhabi University, P.O. Box 59911, Abu Dhabi, UAE (e-mail: Haydar.Akca@adu.ac.ae, Jamal.Benbourenane@adu.ac.ae).
V. Covachev is with the Bulgarian Academy of Sciences, Sofia, Bulgaria (e-mail: covachev@hotmail.com).

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.