BAM-type Cohen–Grossberg neural networks with time delays

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Abstract

In this paper, we investigate bidirectional associative memory Cohen–Grossberg neural networks with time delays. By applying the Young inequality technique, Dini derivative, and introducing many real parameters, a series of new and useful criteria on the existence and uniqueness of an equilibrium point and its global asymptotical stability are established. It is shown that in some special cases of the results, the stability criteria can be easily checked. Finally, an example is given to illustrate the result obtained in this paper.

Keywords

Bidirectional associative memory Cohen–Grossberg neural networks
Lyapunov function
Time delay
Global asymptotical stability
Equilibrium point

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This work was supported by the National Natural Science Foundation of China under Grants 60574043 and 10361004, the Major Project of The Ministry of Education of P.R. China and was Funded by Scientific Research Program of the Higher Education Institution of Xinjiang (XJEDU2004I12 and XJEDU2006I05), and the Doctoral Foundation of Xinjiang University under Grants 070171.