کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1704549 | 1012410 | 2013 | 8 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Comparison on neural solvers for the Lyapunov matrix equation with stationary && nonstationary coefficients
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
مکانیک محاسباتی
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
In this paper, two types of recurrent neural network (RNN) are comparatively developed and exploited for the online solution of the well-known Lyapunov matrix equation with the stationary and nonstationary coefficients. Based on a new design method, the resultant Zhang neural networks (ZNN) are generalized and presented to solve the stationary and nonstationary problems with accuracy and efficiency. For comparison, the conventional gradient-based neural networks (GNN) are also used for the same problems. Computer simulation results show that, when used to solve the whether stationary or nonstationary problems, the convergence performance of ZNN solvers are superior than that of GNN solvers.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Applied Mathematical Modelling - Volume 37, Issue 4, 15 February 2013, Pages 2495–2502
Journal: Applied Mathematical Modelling - Volume 37, Issue 4, 15 February 2013, Pages 2495–2502
نویسندگان
Chenfu Yi, Yuhuan Chen, Xinhua Lan,