State-dependent impulsive Cohen-Grossberg neural networks with time-varying delays

Date

2016-01-01

Author

Sayli, Mustafa
YILMAZ, ENES

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In this paper, a more general class of state-dependent impulsive Cohen-Grossberg neural networks having variable coefficients with time-varying delays is addressed. By means of B-equivalence method, we reduce this state-dependent impulsive neural networks system to a fix time impulsive neural networks system. Sufficient conditions for existence and global exponential stability of the equilibrium point as well as periodic solution are obtained by employing a suitable Lyapunov function, the Banach fixed point theorem and the Halanay-type impulsive differential inequality technique. Finally, two examples with numerical simulations to show the effectiveness of our theoretical results are illustrated.

Subject Keywords

Cohen-Grossberg neural networks; ;; , Periodicity, State-dependent impulsive systems, Global exponential stability

URI

https://hdl.handle.net/11511/64411

Journal

NEUROCOMPUTING

DOI

https://doi.org/10.1016/j.neucom.2015.07.095

Collections

Graduate School of Applied Mathematics, Article

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Citation Formats

M. Sayli and E. YILMAZ, “State-dependent impulsive Cohen-Grossberg neural networks with time-varying delays,” NEUROCOMPUTING, pp. 1375–1386, 2016, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/64411.