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This paper studies delay-dependent asymptotical stability
problems for the neural system with time-varying delay. By dividing the
whole interval into multiple segments such that each segment has a
different Lyapunov matrix, some improved delay-dependent stability
conditions are derived by employing an integral equality technique. A
numerical example is given to demonstrate the effectiveness and
less conservativeness of the proposed methods. 相似文献
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Improved delay-dependent globally asymptotic stability of delayed uncertain recurrent neural networks with Markovian jumping parameters 下载免费PDF全文
In this paper, we have improved delay-dependent stability
criteria for recurrent neural networks with a delay varying over a
range and Markovian jumping parameters. The criteria improve over
some previous ones in that they have fewer matrix variables yet less
conservatism. In addition, a numerical example is provided to
illustrate the applicability of the result using the linear matrix
inequality toolbox in MATLAB. 相似文献
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