Global Exponential Robust Stability of Static Interval Neural Networks with Time Delay in the Leakage Term
The stability of a class of static interval neural networks with time delay in the leakage term is investigated. By using the method of M-matrix and the technique of delay differential inequality, we obtain some sufficient conditions ensuring the global exponential robust stability of the networks....
Saved in:
Main Authors: | Guiying Chen, Linshan Wang |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2014-01-01
|
Series: | Journal of Applied Mathematics |
Online Access: | http://dx.doi.org/10.1155/2014/972608 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Robust Exponential Stability of Impulsive Stochastic Neural Networks with Leakage Time-Varying Delay
by: Chunge Lu, et al.
Published: (2014-01-01) -
Global Robust Exponential Stability Analysis for Interval Neural Networks with Mixed Delays
by: Yanke Du, et al.
Published: (2012-01-01) -
Global Robust Exponential Stability and Periodic Solutions for Interval Cohen-Grossberg Neural Networks with Mixed Delays
by: Yanke Du, et al.
Published: (2013-01-01) -
Switched Exponential State Estimation and Robust Stability for Interval Neural Networks with Discrete and Distributed Time Delays
by: Hongwen Xu, et al.
Published: (2012-01-01) -
Exponential Convergence for Cellular Neural Networks with Time-Varying Delays in the Leakage Terms
by: Zhibin Chen, et al.
Published: (2012-01-01)