Published January 2011
| Version v1
Journal article
Global exponential stability of mixed discrete and distributively delayed cellular neural network
Creators
- 1. Nonlinear Scientific Research Center, Jiangsu University, Zhenjiang 212013 (China)
Description
This paper concernes analysis for the global exponential stability of a class of recurrent neural networks with mixed discrete and distributed delays. It first proves the existence and uniqueness of the balance point, then by employing the Lyapunov—Krasovskii functional and Young inequality, it gives the sufficient condition of global exponential stability of cellular neural network with mixed discrete and distributed delays, in addition, the example is provided to illustrate the applicability of the result. (general)
Availability note (English)
Available from http://dx.doi.org/10.1088/1674-1056/20/1/010701Additional details
Identifiers
Publishing Information
- Journal Title
- Chinese Physics. B
- Journal Volume
- 20
- Journal Issue
- 1
- Journal Page Range
- [3 p.]
- ISSN
- 1674-1056
INIS
- Country of Publication
- China
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 45013030
- Subject category
- S71: CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS;
- Descriptors DEI
- FUNCTIONAL ANALYSIS; LYAPUNOV METHOD; NETWORK ANALYSIS; NEURAL NETWORKS; STABILITY
- Descriptors DEC
- CALCULATION METHODS; MATHEMATICS