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Global stability of interval recurrent neural networks 被引量：1

Global stability of interval recurrent neural networks
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摘要 The robust global exponential stability of a class of interval recurrent neural networks（RNNs） is studied,and a new robust stability criterion is obtained in the form of linear matrix inequality.The problem of robust stability of interval RNNs is transformed into a problem of solving a class of linear matrix inequalities.Thus,the robust stability of interval RNNs can be analyzed by directly using the linear matrix inequalities（LMI） toolbox of MATLAB.Numerical example is given to show the effectiveness of the obtained results. The robust global exponential stability of a class of interval recurrent neural networks（RNNs） is studied,and a new robust stability criterion is obtained in the form of linear matrix inequality.The problem of robust stability of interval RNNs is transformed into a problem of solving a class of linear matrix inequalities.Thus,the robust stability of interval RNNs can be analyzed by directly using the linear matrix inequalities（LMI） toolbox of MATLAB.Numerical example is given to show the effectiveness of the obtained results.
作者 袁铸钢 刘志远 裴润 申涛
机构地区 Department of Control Science and Engineering School of Control Science and Engineering
出处 《Journal of Beijing Institute of Technology》 EI CAS 2012年第3期382-386,共5页 北京理工大学学报（英文版）
基金 Supported by the Natural Science Foundation of Shandong Province (ZR2010FM038,ZR2010FL017)
关键词 recurrent neural networks（RNNs） interval systems linear matrix inequalities（LMI） global exponential stability recurrent neural networks（RNNs） interval systems linear matrix inequalities（LMI） global exponential stability
分类号 TP183 [自动化与计算机技术—控制理论与控制工程]
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参考文献18

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Journal of Beijing Institute of Technology
2012年 第3期

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