کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
9868205 | 1530683 | 2005 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Globally exponential stability condition of a class of neural networks with time-varying delays
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
فیزیک و نجوم
فیزیک و نجوم (عمومی)
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Globally exponential stability condition of a class of neural networks with time-varying delays Globally exponential stability condition of a class of neural networks with time-varying delays](/preview/png/9868205.png)
چکیده انگلیسی
In this Letter, the globally exponential stability for a class of neural networks including Hopfield neural networks and cellular neural networks with time-varying delays is investigated. Based on the Lyapunov stability method, a novel and less conservative exponential stability condition is derived. The condition is delay-dependent and easily applied only by checking the Hamiltonian matrix with no eigenvalues on the imaginary axis instead of directly solving an algebraic Riccati equation. Furthermore, the exponential stability degree is more easily assigned than those reported in the literature. Some examples are given to demonstrate validity and excellence of the presented stability condition herein.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Physics Letters A - Volume 339, Issues 3â5, 23 May 2005, Pages 333-342
Journal: Physics Letters A - Volume 339, Issues 3â5, 23 May 2005, Pages 333-342
نویسندگان
Teh-Lu Liao, Jun-Juh Yan, Chao-Jung Cheng, Chi-Chuan Hwang,