کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8900858 | 1631723 | 2018 | 24 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Exponential stability and extended dissipativity criteria for generalized discrete-time neural networks with additive time-varying delays
ترجمه فارسی عنوان
پایداری مؤلفه و معیار تمایز گسترده ای برای شبکه های عصبی زمان گسسته به طور مجزا با تاخیرهای متفاوت متغیر زمان
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
ریاضیات
ریاضیات کاربردی
چکیده انگلیسی
This paper is concerned with exponential stability and extended dissipativity criteria for generalized discrete-time neural networks (GDNNs) with additive time-varying delays. The generalized dissipativity analysis combines a few previous results into a framework, such as l2âlâ performance, Hâ performance, passivity performance, strictly (Q,S,R)âγâdissipative and strictly (Q,S,R)âdissipative. The definition of exponential stability for GDNNs is given with a new and more appropriate expression. A novel augmented Lyapunov-Krasovskii functional (LKF) which involves more information about the additive time-varying delays is constructed. By introducing more zero equalities and using a new double summation inequality together with Finsler's lemma, an improved delay-dependent exponential stability and extended dissipativity criterion are derived in terms of convex combination technique (CCT). Finally, numerical examples are given to illustrate the usefulness and advantages of the proposed methods.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Applied Mathematics and Computation - Volume 333, 15 September 2018, Pages 145-168
Journal: Applied Mathematics and Computation - Volume 333, 15 September 2018, Pages 145-168
نویسندگان
Yaonan Shan, Kun She, Shouming Zhong, Qishui Zhong, Kaibo Shi, Can Zhao,