2 sonuçlar
Arama Sonuçları
Listeleniyor 1 - 2 / 2
Yayın New criteria for global robust stability of delayed neural networks with norm-bounded uncertainties(IEEE-INST Electrical Electronics Engineers Inc, 2014-06) Arık, SabriIn this paper, we study the global asymptotic robust stability of delayed neural networks with norm-bounded uncertainties. By employing the Lyapunov stability theory and homeomorphic mapping theorem, we derive some new types of sufficient conditions ensuring the existence, uniqueness, and global asymptotic stability of the equilibrium point for the class of neural networks with discrete time delays under parameter uncertainties and with respect to continuous and slope-bounded activation functions. An important aspect of our results is their low computational complexity, as the reported results can be verified by checking some properties of symmetric matrices associated with the uncertainty sets of the network parameters. The obtained results are shown to be generalizations of some of the previously published corresponding results. Some comparative numerical examples are also constructed to compare our results with some closely related existing literature results.Yayın New sufficient criteria for global robust stability of neural networks with multiple time delays(Işık University Press, 2012) Yücel, Eylem; Arık, SabriIn this paper, we study global robust asymptotic stability of the equilibrium point for neural networks with multiple time delays. By employing suitable Lyapunov functionals, we derive a set of delay independent sufficient conditions for global robust asymptotic stability of this class of neural networks. Some examples are constructed to compare the reported results with the related existing results. This comparison proves that our results establish a new set of robust stability criteria for delayed neural networks. It is also demonstrated that the reported results can be easily verified as they can be expressed in terms of the network parameters only.
