Global exponential stability of Cohen-Grossberg neural networks with variable delays. (English) Zbl 1136.34347

Zhang, Jiye; Suda, Yoshihiro; Komine, Hisanao

Phys. Lett., A 338, No. 1, 44-50 (2005).

Summary: In this Letter, the conditions ensuring existence, uniqueness of the equilibrium point of Cohen-Grossberg neural networks with variable delays are obtained under more general assumption about activation functions. Applying idea of vector Lyapunov function, and M-matrix theory, the sufficient conditions for global exponential stability of Cohen-Grossberg neural networks are obtained. These results generalize a few previous known results and remove some restrictions on the neural networks.

MSC:

34K60	Qualitative investigation and simulation of models involving functional-differential equations
34K20	Stability theory of functional-differential equations
68T05	Learning and adaptive systems in artificial intelligence

Keywords:

neural network; Cohen-Grossberg neural networks; time delay; global asymptotical stability; global exponential stability; M-matrix

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