کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
390417 661253 2011 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Some new results on stability of Takagi–Sugeno fuzzy Hopfield neural networks
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Some new results on stability of Takagi–Sugeno fuzzy Hopfield neural networks
چکیده انگلیسی

In this paper, we propose some new results on stability properties of Takagi–Sugeno fuzzy Hopfield neural networks with time-delay. Based on Lyapunov stability theory, a new learning law is derived to guarantee passivity and asymptotical stability of Takagi–Sugeno fuzzy Hopfield neural networks. Furthermore, a new condition for input-to-state stability (ISS) is established. Illustrative examples are given to demonstrate the effectiveness of the proposed results.


► A new learning law for Takagi–Sugeno fuzzy neural networks is proposed.
► This learning law guarantees passivity and asymptotical stability.
► A new condition for input-to-state stability is proposed under this learning law.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Fuzzy Sets and Systems - Volume 179, Issue 1, 16 September 2011, Pages 100–111
نویسندگان
,