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Neural Processing Letters
Published in: Neural Processing Letters 3/2019

21-06-2019

Extended \(H_{\infty }\) Synchronization Control for Switched Neural Networks with Multi Quantization Densities Based on a Persistent Dwell-Time Approach

Authors: Zhengguo Huang, Hao Shen, Jianwei Xia, Xia Huang, Jian Wang

Published in: Neural Processing Letters | Issue 3/2019

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Abstract

This paper thoroughly investigates the synchronization control issue for the switched neural networks. The more comprehensive comparatively switching rule, persistent dwell-time, is applied to actuate the aforementioned neural networks. For tackling the problem caused by the transmission of tremendous data, the quantizer is utilized. The objective is to establish the mixed controller with multi quantization densities for the synchronization error neural networks to meet the various accuracy requirements of the transmitted data. Whereafter, the sufficient conditions of the extended \(H_{\infty }\) performance and global uniform exponential stability for the synchronization error neural networks are constructed. Conclusively, the capability of the proposed mixed controller is elucidated through a numerical example.
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Metadata
Title
Extended Synchronization Control for Switched Neural Networks with Multi Quantization Densities Based on a Persistent Dwell-Time Approach
Authors
Zhengguo Huang
Hao Shen
Jianwei Xia
Xia Huang
Jian Wang
Publication date
21-06-2019
Publisher
Springer US
Published in
Neural Processing Letters / Issue 3/2019
Print ISSN: 1370-4621
Electronic ISSN: 1573-773X
DOI
https://doi.org/10.1007/s11063-019-10064-2

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