Delay-dependent robust stability criteria for delay neural networks with linear fractional uncertainties

被引:0
|
作者
Tao Li
Lei Guo
Lingyao Wu
Changyin Sun
机构
[1] Nanjing University of Information Science and Technology,Department of Information Communication
[2] Beihang University,School of Instrument Science and Opto
[3] Southeast University,Electronics Engineering
关键词
Delay-dependent; linear matrix inequality; neural networks; robust stability;
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学科分类号
摘要
This article investigates the problem of robust stability for neural networks with time-varying delays and parameter uncertainties of linear fractional form. By introducing a new Lyapunov-Krasovskii functional and a tighter inequality, delay-dependent stability criteria are established in term of linear matrix inequalities (LMIs). It is shown that the obtained criteria can provide less conservative results than some existing ones. Numerical examples are given to demonstrate the applicability of the proposed approach.
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页码:281 / 287
页数:6
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