Title :
An improved global stability result for cellular neural networks with time delay
Author_Institution :
Dept. of Electr.-Electron. Eng., Istanbul Univ., Turkey
Abstract :
This paper presents a sufficient condition for the uniqueness and global asymptotic stability of the equilibrium point for delayed cellular neural networks, which improves the previous stability results derived in the literature.
Keywords :
asymptotic stability; cellular neural nets; delayed cellular neural networks; equilibrium point; global asymptotic stability; uniqueness; Asymptotic stability; Cellular neural networks; Delay effects; Equations; Mathematical model; Neural networks; Neurofeedback; Stability analysis; State feedback; Sufficient conditions;
Conference_Titel :
Cellular Neural Networks and Their Applications, 2002. (CNNA 2002). Proceedings of the 2002 7th IEEE International Workshop on
Print_ISBN :
981-238-121-X
DOI :
10.1109/CNNA.2002.1035034
