DocumentCode
3547463
Title
Global exponential stability analysis of delayed cellular neural networks
Author
Senan, Sibel ; Arik, Sabri
Author_Institution
Dept. of Comput. Eng., Istanbul Univ., Turkey
fYear
2005
fDate
23-26 May 2005
Firstpage
4665
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuits and Systems, 2005. ISCAS 2005. IEEE International Symposium on
Print_ISBN
0-7803-8834-8
Type
conf
DOI
10.1109/ISCAS.2005.1465673
Filename
1465673
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