New synchronization schemes for delayed chaotic neural networks with impulses

New synchronization schemes for delayed chaotic neural networks with impulses This paper considers the exponential synchronization problem for chaotic neural networks with mixed delays and impulsive effects. The mixed delays include time-varying delays and unbounded distributed delays. Some delay-dependent schemes are designed to guarantee the exponential synchronization of the addressed systems by constructing suitable Lyapunov–Krasovskii functional and employing stability theory. The synchronization conditions are given in terms of LMIs, which can be easily checked via MATLAB LMI toolbox. Moreover, the synchronization conditions obtained are mild and more general than previously known criteria. Finally, two numerical examples and their simulations are given to show the effectiveness of the proposed chaos synchronization schemes. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Neural Computing and Applications Springer Journals

New synchronization schemes for delayed chaotic neural networks with impulses

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Publisher
Springer Journals
Copyright
Copyright © 2016 by The Natural Computing Applications Forum
Subject
Computer Science; Artificial Intelligence (incl. Robotics); Data Mining and Knowledge Discovery; Probability and Statistics in Computer Science; Computational Science and Engineering; Image Processing and Computer Vision; Computational Biology/Bioinformatics
ISSN
0941-0643
eISSN
1433-3058
D.O.I.
10.1007/s00521-016-2218-7
Publisher site
See Article on Publisher Site

Abstract

This paper considers the exponential synchronization problem for chaotic neural networks with mixed delays and impulsive effects. The mixed delays include time-varying delays and unbounded distributed delays. Some delay-dependent schemes are designed to guarantee the exponential synchronization of the addressed systems by constructing suitable Lyapunov–Krasovskii functional and employing stability theory. The synchronization conditions are given in terms of LMIs, which can be easily checked via MATLAB LMI toolbox. Moreover, the synchronization conditions obtained are mild and more general than previously known criteria. Finally, two numerical examples and their simulations are given to show the effectiveness of the proposed chaos synchronization schemes.

Journal

Neural Computing and ApplicationsSpringer Journals

Published: Feb 17, 2016

References

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