New results on almost periodic solutions for CNNs with time-varying leakage delays

In this paper, based on the exponential dichotomy theory and contraction mapping fixed point theorem, we obtain some sufficient conditions ensuring the global exponential stability of almost periodic solutions for a new generalized cellular neural network model with time-varying delays in leakage (o...

Full description

Saved in:
Bibliographic Details
Published in:Neural computing & applications 2014-11, Vol.25 (6), p.1293-1302
Main Author: Xu, Yanli
Format: Article
Language:English
Subjects:
Applied sciences
Artificial Intelligence
Computational Biology/Bioinformatics
Computational Science and Engineering
Computer Science
Computer science
control theory
systems
Connectionism. Neural networks
Control system analysis
Control theory. Systems
Data Mining and Knowledge Discovery
Exact sciences and technology
Image Processing and Computer Vision
Original Article
Probability and Statistics in Computer Science
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In this paper, based on the exponential dichotomy theory and contraction mapping fixed point theorem, we obtain some sufficient conditions ensuring the global exponential stability of almost periodic solutions for a new generalized cellular neural network model with time-varying delays in leakage (or forgetting) terms. Our results complement some recent ones. Moreover, an illustrative example and its numerical simulation are given to demonstrate the effectiveness of the obtained results.
ISSN:0941-0643
1433-3058
DOI:10.1007/s00521-014-1610-4