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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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BibTeX
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.