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Improved results on h∞ state estimation of static neural networks with time delay
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نویسنده
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wen b. ,li h. ,zhong s.
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منبع
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journal of control science and engineering - 2016 - دوره : 2016 - شماره : 0
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چکیده
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This paper studies the problem of h∞ state estimation for a class of delayed static neural networks. the purpose of the problem is to design a delay-dependent state estimator such that the dynamics of the error system is globally exponentially stable and a prescribed h∞ performance is guaranteed. some improved delay-dependent conditions are established by constructing augmented lyapunov-krasovskii functionals (lkfs). the desired estimator gain matrix can be characterized in terms of the solution to lmis (linear matrix inequalities). numerical examples are provided to illustrate the effectiveness of the proposed method compared with some existing results. © 2016 bin wen et al.
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آدرس
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school of aeronautics and astronautics,university of electronic science and technology of china,chengdu,sichuan, China, school of aeronautics and astronautics,university of electronic science and technology of china,chengdu,sichuan, China, school of mathematical sciences,university of electronic science and technology of china,chengdu,sichuan,china,key laboratory for neuroinformation of ministry of education,university of electronic science and technology of china,chengdu, China
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Authors
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