کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1865261 | 1530646 | 2007 | 9 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Discrete-time recurrent neural networks with time-varying delays: Exponential stability analysis
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
فیزیک و نجوم
فیزیک و نجوم (عمومی)
پیش نمایش صفحه اول مقاله
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چکیده انگلیسی
This Letter is concerned with the analysis problem of exponential stability for a class of discrete-time recurrent neural networks (DRNNs) with time delays. The delay is of the time-varying nature, and the activation functions are assumed to be neither differentiable nor strict monotonic. Furthermore, the description of the activation functions is more general than the recently commonly used Lipschitz conditions. Under such mild conditions, we first prove the existence of the equilibrium point. Then, by employing a Lyapunov-Krasovskii functional, a unified linear matrix inequality (LMI) approach is developed to establish sufficient conditions for the DRNNs to be globally exponentially stable. It is shown that the delayed DRNNs are globally exponentially stable if a certain LMI is solvable, where the feasibility of such an LMI can be easily checked by using the numerically efficient Matlab LMI Toolbox. A simulation example is presented to show the usefulness of the derived LMI-based stability condition.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Physics Letters A - Volume 362, Issues 5â6, 12 March 2007, Pages 480-488
Journal: Physics Letters A - Volume 362, Issues 5â6, 12 March 2007, Pages 480-488
نویسندگان
Yurong Liu, Zidong Wang, Alan Serrano, Xiaohui Liu,