Journal
NONLINEAR DYNAMICS
Volume 48, Issue 1-2, Pages 165-174Publisher
SPRINGER
DOI: 10.1007/s11071-006-9080-6
Keywords
global asymptotical stability; time varying delay; LMI technique; Lyapunov functional method; nonsmooth analysis
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In this paper, the asymptotic stability of neural networks with time varying delay is studied by using the nonsmooth analysis, Lyapunov functional method and linear matrix inequality (LMI) technique. It is noted that the proposed results do not require smoothness of the behaved function and activation function as well as boundedness of the activation function. Several sufficient conditions are presented to show the uniqueness and the global asymptotical stability of the equilibrium point. Also, a high-dimensional matrix condition to ensure the uniqueness and the global asymptotical stability of equilibrium point can be reduced to a low-dimensional condition. The obtained results are easy to apply and improve some earlier works. Finally, we give two simulations to justify the theoretical analysis in this paper.
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