Stability criteria for Cohen–Grossberg neural networks with mixed delays and inverse Lipschitz neuron activations
作者： Cheng-De Zheng , Chao-Ke Gong , Zhanshan Wang
DOI: 10.1016/J.JFRANKLIN.2012.08.001
关键词:
摘要: Abstract In this paper, by using topological degree theory and Lyapunov–Krasovskii function method, the problem of stability is investigated for a class mixed-delayed Cohen–Grossberg neural networks with inverse Lipschitz neuron activations nonsmooth behaved functions. Several novel delay-dependent sufficient conditions are established towards existence, uniqueness global exponential equilibrium point, which shown in terms linear matrix inequalities. Besides, case activation satisfying not only but also conditions, two criteria derived virtue homeomorphism mapping principle, free-weighting method Cauchy–Schwarz inequality, generalize some previous results. Finally, examples their simulations given to show effectiveness theoretical
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