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Neural Computing and Applications
Published in: Neural Computing and Applications 7/2018

29-12-2016 | Original Article

Stability of switched neural networks with time-varying delays

Authors: Chao Liu, Zheng Yang, Dihua Sun, Xiaoyang Liu, Wanping Liu

Published in: Neural Computing and Applications | Issue 7/2018

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Abstract

This paper investigates the globally exponential stability of switched neural networks with time-varying delays. By virtue of mode-dependent average dwell time, some significant criteria of exponential stability are obtained for delayed switched neural networks with only stable subsystems or with both stable subsystems and unstable subsystems. The proposed theoretical results could be utilized not only to verify the globally exponential stability of switched neural networks, but also to design appropriate switching signal to guarantee the globally exponential stabilization. They can explicitly reflect the effect of mode-dependent average dwell time on the stability of switched neural networks. In contrast to the previous results, the proposed criteria are more straightforward and effective in the real-world application. Three numerical examples are introduced to illustrate the effectiveness of the proposed results.
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Metadata
Title
Stability of switched neural networks with time-varying delays
Authors
Chao Liu
Zheng Yang
Dihua Sun
Xiaoyang Liu
Wanping Liu
Publication date
29-12-2016
Publisher
Springer London
Published in
Neural Computing and Applications / Issue 7/2018
Print ISSN: 0941-0643
Electronic ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-016-2805-7

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