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New Globally Asymptotic Stability Criteria for Delayed Cellular Neural Networks

  作者 Xiao, SP; Zhang, XM  
  选自 期刊  IEEE Transactions on Circuits and Systems II;  卷期  2009年56-8;  页码  659-663  
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[摘要]This brief is concerned with the stability analysis for cellular neural networks with time-varying delays. First, an appropriate Lyapunov-Krasovskii functional is introduced to form some new delay-dependent stability conditions in terms of linear matrix inequalities (LMIs). Quite differently, these stability criteria are derived by using the convex combination property, which equivalently converts the original LMI containing a convex combination on the time-varying delay into two boundary LMIs. Second, this newly proposed approach is then extended to a class of uncertain neural networks with time-varying delays, from which new delay-dependent robust stability criteria are formulated. Finally, two numerical examples are given to show that the proposed criteria are of much less conservatism than the existing ones in the literature.

 
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