Existence and Exponential Stability of Periodic Solution for a Class of Generalized Neural Networks with Arbitrary Delays
By the continuation theorem of coincidence degree and M-matrix theory, we obtain some sufficient conditions for the existence and exponential stability of periodic solutions for a class of generalized neural networks with arbitrary delays, which are milder and less restrictive than those of previous...
Saved in:
Main Authors: | Yimin Zhang, Yongkun Li, Kuohui Ye |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2009-01-01
|
Series: | Abstract and Applied Analysis |
Online Access: | http://dx.doi.org/10.1155/2009/957475 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Existence and Global Exponential Stability of Periodic Solutions for General Neural Networks with Time-Varying Delays
by: Xinsong Yang
Published: (2008-01-01) -
Periodic Solutions and Exponential Stability of a Class of Neural Networks with Time-Varying Delays
by: Yingxin Guo, et al.
Published: (2009-01-01) -
Existence and Global Exponential Stability of Periodic Solution to Cohen-Grossberg BAM Neural Networks with Time-Varying Delays
by: Kaiyu Liu, et al.
Published: (2012-01-01) -
Global Exponential Stability of Weighted Pseudo-Almost Periodic Solutions of Neutral Type High-Order Hopfield Neural Networks with Distributed Delays
by: Lili Zhao, et al.
Published: (2014-01-01) -
Existence and Exponential Stability of Equilibrium Point for Fuzzy BAM Neural Networks with Infinitely Distributed Delays and Impulses on Time Scales
by: Yongkun Li, et al.
Published: (2014-01-01)