Published January 2011 | Version v1
Journal article

Global exponential stability of mixed discrete and distributively delayed cellular neural network

  • 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/10.1088/1674-1056/20/1/010701

Additional details

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