Title :
Global exponential stability analysis of delayed cellular neural networks
Author :
Senan, Sibel ; Arik, Sabri
Author_Institution :
Dept. of Comput. Eng., Istanbul Univ., Turkey
Abstract :
This paper presents new sufficient conditions for the global exponential stability of the equilibrium point for delayed cellular neural networks (DCNN). It is shown that the use of a more general type of Lyapunov-Krasovskii functional enables us to derive new results for exponential stability of the equilibrium point for DCNN. The results are also compared with the most recent results derived in the literature.
Keywords :
Lyapunov methods; asymptotic stability; cellular neural nets; DCNN; Lyapunov-Krasovskii functional; delayed cellular neural networks; equilibrium point; global exponential stability analysis; Asymptotic stability; Cellular neural networks; Computer networks; Eigenvalues and eigenfunctions; Equations; Neural networks; Stability analysis; Stability criteria; Sufficient conditions; Symmetric matrices;
Conference_Titel :
Circuits and Systems, 2005. ISCAS 2005. IEEE International Symposium on
Print_ISBN :
0-7803-8834-8
DOI :
10.1109/ISCAS.2005.1465673
