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New results on the robust stability analysis of neural networks with discrete and distributed time delays

New results on the robust stability analysis of neural networks with discrete and distributed time delays
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摘要 Delay-dependent robust stability of cellular neural networks with time-varying discrete and distributed time-varying delays is considered. Based on Lyapunov stability theory and the linear matrix inequality （LMIs） technique, delay-dependent stability criteria are derived in terms of LMIs avoiding bounding certain cross terms, which often leads to conservatism. The effectiveness of the proposed stability criteria and the improvement over the existing results are illustrated in the numerical examples. Delay-dependent robust stability of cellular neural networks with time-varying discrete and distributed time-varying delays is considered. Based on Lyapunov stability theory and the linear matrix inequality （LMIs） technique, delay-dependent stability criteria are derived in terms of LMIs avoiding bounding certain cross terms, which often leads to conservatism. The effectiveness of the proposed stability criteria and the improvement over the existing results are illustrated in the numerical examples.
作者 Su Weiwei Chen Yiming
机构地区 Coll. of Science
出处 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2008年第3期592-597,共6页 系统工程与电子技术（英文版）
关键词 neural networks delay-dependent robust stability Lyapunov stability theory linear matrix inequality（LMI） distributed delay norm-bounded uncertainties. neural networks, delay-dependent robust stability, Lyapunov stability theory, linear matrix inequality（LMI）, distributed delay, norm-bounded uncertainties.
分类号 TP11 [自动化与计算机技术—控制理论与控制工程]
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Journal of Systems Engineering and Electronics
2008年 第3期

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