Finite-time stabilization for stochastic delayed recurrent neural networks via nonlinear delay-feedback controller

In this paper, stochastic finite-time stability analysis and stabilization problems for stochastic delayed recurrent neural networks(SDRNNs) are investigated, and the stochastic settling time function is also estimated. The sufficient condition of stochastic finite-time stable(SFTS) for SDRNNs is pr...

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Bibliographic Details
Published in2017 Chinese Automation Congress (CAC) pp. 1411 - 1416
Main Authors Chen, Guici, Wang, Huafeng, Yang, Yali
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2017
Subjects
Automation
delay-feedback controller
finite-time
Recurrent neural networks
Stability analysis
stabilization
stochastic neural networks
Sufficient conditions
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DOI10.1109/CAC.2017.8242988

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Summary:In this paper, stochastic finite-time stability analysis and stabilization problems for stochastic delayed recurrent neural networks(SDRNNs) are investigated, and the stochastic settling time function is also estimated. The sufficient condition of stochastic finite-time stable(SFTS) for SDRNNs is proposed at first. Then the nonlinear delay-feedback controller to stochastic finite-time stabilize the SDRNNs is designed. Finally, an numerical example is given to show the corrections of the proposed results and the effectiveness of the provided controller.
DOI:10.1109/CAC.2017.8242988