Global Exponential Stability of Antiperiodic Solutions for Discrete-Time Neural Networks with Mixed Delays and Impulses
The problem on global exponential stability of antiperiodic solution is investigated for a class of impulsive discrete-time neural networks with time-varying discrete delays and distributed delays. By constructing an appropriate Lyapunov-Krasovskii functional, and using the contraction mapping princ...
Saved in:
Main Authors: | Xiaofeng Chen, Qiankun Song |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2012-01-01
|
Series: | Discrete Dynamics in Nature and Society |
Online Access: | http://dx.doi.org/10.1155/2012/168375 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Global μ-Stability of Impulsive Complex-Valued Neural Networks with Leakage Delay and Mixed Delays
by: Xiaofeng Chen, et al.
Published: (2014-01-01) -
Globally Exponential Stability of Periodic Solutions to Impulsive Neural Networks with Time-Varying Delays
by: Yuanfu Shao, et al.
Published: (2012-01-01) -
Antiperiodic Solutions to Impulsive Cohen-Grossberg Neural Networks with Delays on Time Scales
by: Yanqin Wang, et al.
Published: (2014-01-01) -
Global Exponential Stability of Discrete-Time Neural Networks with Time-Varying Delays
by: S. Udpin, et al.
Published: (2013-01-01) -
On Global Exponential Stability of Discrete-Time Hopfield Neural Networks with Variable Delays
by: Qiang Zhang, et al.
Published: (2007-01-01)