کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
404795 677452 2007 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
An LMI approach to global asymptotic stability of the delayed Cohen–Grossberg neural network via nonsmooth analysis
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
An LMI approach to global asymptotic stability of the delayed Cohen–Grossberg neural network via nonsmooth analysis
چکیده انگلیسی

In this paper, a linear matrix inequality (LMI) to global asymptotic stability of the delayed Cohen–Grossberg neural network is investigated by means of nonsmooth analysis. Several new sufficient conditions are presented to ascertain the uniqueness of the equilibrium point and the global asymptotic stability of the neural network. It is noted that the results herein require neither the smoothness of the behaved function, or the activation function nor the boundedness of the activation function. In addition, from theoretical analysis, it is found that the condition for ensuring the global asymptotic stability of the neural network also implies the uniqueness of equilibrium. The obtained results improve many earlier ones and are easy to apply. Some simulation results are shown to substantiate the theoretical results.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neural Networks - Volume 20, Issue 7, September 2007, Pages 810–818
نویسندگان
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