کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
411842 | 679593 | 2015 | 6 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
New stability condition for discrete-time fully coupled neural networks with multivalued neurons
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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: New stability condition for discrete-time fully coupled neural networks with multivalued neurons New stability condition for discrete-time fully coupled neural networks with multivalued neurons](/preview/png/411842.png)
چکیده انگلیسی
This paper discusses the stability condition for discrete-time multi-valued recurrent neural networks (MVNRNNs) in asynchronous update mode. In the existing research literature, an MVNRNN in asynchronous update mode has been found convergent if its weight matrix is Hermitian with nonnegative diagonal entries. However, our finding has been that the weight matrix with zero diagonal entries cannot guarantee the network stability. Furthermore, the new stability condition and proof is offered to allow diagonal entries to be complex-valued, which extends previous theoretical result. Simulation results are used to illustrate the theory.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 166, 20 October 2015, Pages 38–43
Journal: Neurocomputing - Volume 166, 20 October 2015, Pages 38–43
نویسندگان
Wei Zhou, Jacek M. Zurada,