کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
406399 | 678083 | 2013 | 5 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Exponential stabilization of delayed recurrent neural networks: A state estimation based approach
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
پیش نمایش صفحه اول مقاله

چکیده انگلیسی
This paper is concerned with the stabilization problem of delayed recurrent neural networks. As the states of neurons are usually difficult to be fully measured, a state estimation based approach is presented. First, a sufficient condition is derived such that the augmented system under consideration is globally exponentially stable. Then, by employing a decoupling technique, the gain matrices of the controller and state estimator are achieved by solving some linear matrix inequalities. Finally, a delayed neural network with chaotic behaviors is exploited to demonstrate the applicability of the developed result.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neural Networks - Volume 48, December 2013, Pages 153–157
Journal: Neural Networks - Volume 48, December 2013, Pages 153–157
نویسندگان
He Huang, Tingwen Huang, Xiaoping Chen, Chunjiang Qian,