Application of RBF for strip shape recognition - 文章详情页

作者：

Lu, Yanling (Lu, Yanling.) | Xu, Zhe (Xu, Zhe.) | Qiao, Junfei (Qiao, Junfei.) (学者：乔俊飞) | Duan, Jianmin (Duan, Jianmin.) (学者：段建民)

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摘要：

Based　on　radial　basis　function　neural　network　(RBF　NN),　the　paper　proposed　a　new　algorithm　for　strip　shape　recognition.　Compared　with　back　propagation　(BP)　algorithm　and　improved　least　squares　method　(LSM),　RBF　NN　shows　excellent　overall　performance,　such　as　learning　speed,　recognition　precision　and　anti-interference　capability.　Copyright　©　2005　IFAC.

关键词：

Backpropagation Least squares approximations Pattern recognition Radial basis function networks Strip metal

作者机构：

[ 1 ] [Lu, Yanling]College of Electronics and Information Engineering, Beijing University of Technology, Beijing, 100022, China
[ 2 ] [Xu, Zhe]College of Electronics and Information Engineering, Beijing University of Technology, Beijing, 100022, China
[ 3 ] [Qiao, Junfei]College of Electronics and Information Engineering, Beijing University of Technology, Beijing, 100022, China
[ 4 ] [Duan, Jianmin]College of Electronics and Information Engineering, Beijing University of Technology, Beijing, 100022, China

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xiaolunihao@emails.bjut.edu.cn

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