کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4633154 | 1340663 | 2008 | 8 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A hybrid learning algorithm combined with generalized RLS approach for radial basis function neural networks
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
ریاضیات
ریاضیات کاربردی
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
In this paper, a new hybrid learning method for radial basis function neural networks based on generalized recursive least square algorithm is proposed. Firstly the generalized recursive least square (GRLS) model including a general quadratic weight decay term in the energy function for the training of RBF neural networks is described. Then combined with the GRLS approach, a new hybrid learning method is proposed to meet the design goals: improving the generalization ability of the trained network. Finally experimental results demonstrate that our approach can achieve a significantly improved generalization performance of the RBF networks.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Applied Mathematics and Computation - Volume 205, Issue 2, 15 November 2008, Pages 908–915
Journal: Applied Mathematics and Computation - Volume 205, Issue 2, 15 November 2008, Pages 908–915
نویسندگان
Ji-Xiang Du, Chuan-Min Zhai,