کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
408058 | 678242 | 2011 | 8 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Stability and synchronization for Markovian jump neural networks with partly unknown transition probabilities
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Stability and synchronization for Markovian jump neural networks with partly unknown transition probabilities Stability and synchronization for Markovian jump neural networks with partly unknown transition probabilities](/preview/png/408058.png)
چکیده انگلیسی
This paper addresses the problems of stability and synchronization for a class of Markovian jump neural networks with partly unknown transition probabilities. We first study the stability analysis problem for a single neural network and present a sufficient condition guaranteeing the mean square asymptotic stability. Then based on the Lyapunov functional method and the Kronecker product technique, the chaos synchronization problem of an array of coupled networks is considered. Both the stability and the synchronization conditions are delay-dependent, which are expressed in terms of linear matrix inequalities. The effectiveness of the developed methods is shown by simulation examples.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 74, Issue 17, October 2011, Pages 3404–3411
Journal: Neurocomputing - Volume 74, Issue 17, October 2011, Pages 3404–3411
نویسندگان
Qian Ma, Shengyuan Xu, Yun Zou,