Application of RBF for strip shape recognition - Details

Author：

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

Indexed by：

Abstract：

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.

Keyword：

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

Author Community：

[ 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