This paper deals with the problem of the global
asymptotic stability of the class of Takagi-Sugeno 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.
Bu çalışma çoklu zaman gecikmeli Takagi-Sugeno Bulanık
Cohen-Grossberg tipi yapay sinir ağlarının global asimtotik kararlılık problemi
ile ilgilenmektedir. Uygun bulanık Lyapunov fonksiyonelleri kullanılarak ve
aktivasyon fonksiyonlarının Lipschitz olduğu dikkate alnarak, gecikmeli Takagi-Sugeno
Bulanık Cohen-Grossberg yapay sinir ağlarında denge noktasının global asimtotik
gecikme parametrelerinden bağımsız olarak, yeni yeterli bir kararlılık koşulu
sunulmuştur. Elde edilen koşul sadece sinir ağının sistem parametrelerine bağlı
olarak ifade edilmiştir. Bu nedenle, bu çalışmada çalışılan yapay sinir ağı modelinin denge ve kararlılık
özellikleri, bazı özel matris sınıflarının temel özellikleri kullanarak kolaylıkla
doğrulanabilir.
Primary Language | English |
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Subjects | Engineering |
Journal Section | Research Articles |
Authors | |
Publication Date | August 31, 2018 |
Submission Date | March 15, 2018 |
Acceptance Date | May 15, 2018 |
Published in Issue | Year 2018 Volume: 23 Issue: 2 |
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