کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
409502 679074 2015 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
L2-L∞ Filtering for Takagi–Sugeno fuzzy neural networks based on Wirtinger-type inequalities
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
L2-L∞ Filtering for Takagi–Sugeno fuzzy neural networks based on Wirtinger-type inequalities
چکیده انگلیسی

This paper deals with the L2–L∞L2–L∞ filtering problem for continuous-time Takagi–Sugeno fuzzy delayed Hopfield neural networks based on Wirtinger-type inequalities. A new set of delay-dependent conditions is established to estimate the state variables of fuzzy neural networks through the observed input and output variables. This ensures that the state estimation error system is asymptotically stable with a guaranteed L2–L∞L2–L∞ performance. The presented criterion is formulated in terms of linear matrix inequalities (LMIs). An example with simulation results is given to illustrate the effectiveness of the proposed fuzzy neural state estimator.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 153, 4 April 2015, Pages 117–125
نویسندگان
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