2018 Cilt 23 Sayı 2

Permanent URI for this collectionhttps://hdl.handle.net/11452/12466

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Browsing by Department "Fen Bilimleri Enstitüsü"

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    Stability analysis of a class of Takagi-Sugeno Fuzzy Cohen-Grossberg neural networks with time delays
    (Uludağ Üniversitesi, 2018-05-15) Özcan, Neyir; Barış, Samet; Fen Bilimleri Enstitüsü; Elektrik Elektronik Mühendisliği Bölümü
    This paper deals with the problem of the global asymptotic stability of the class of TakagiSugeno Fuzzy Cohen-Grossberg neural networks with multiple time delays. By constructing a suitable fuzzy Lyapunov functional, we present a new delay-independent sufficient condition for the global asymptotic stability of the equilibrium point for delayed Takagi-Sugeno Fuzzy Cohen-Grossberg neural networks with respect to the Lipschitz activation functions. The obtained condition simply relies on the network parameters of the neural system. Therefore, the equilibrium and stability properties of the neural network model considered in this paper can be easily verified by exploiting some basic properties of some certain classes of matrices.