基于RBF神经网络NURBS的散乱数据点自由曲面重建  

Approach of NURBS Free-form Surface Reconstruction from Scattered Data Based on RBFNN

作　　者：范彦革[1] 刘旭敏[1] 陈婧[1] 

机构地区：[1]首都师范大学信息工程学院,北京100037

出　　处：《计算机工程与应用》2005年第11期66-69,共4页Computer Engineering and Applications

基　　金：北京市教育委员会项目(编号:KM200410028013)

摘　　要：根据径向基函数(RBF)神经网络可以用任意精度逼近任何非线性函数,以及强大的抗噪、修复能力等优点,该文采用RBF神经网络模型进行自由曲面重构,建立了适合曲面重构的径向基函数网络模型。进行了理论分析,并在非均匀有理B样条(NURBS)曲面上做了仿真试验。结果表明:该模型不仅能够有效地逼近不完善的、带有噪声的曲面,而且学习速度很快,提高了对破损、不完全曲面重建的效率和精度,得到的曲面光顺性好。Based on RBFNN' s advantages of approaching any no -linear function by arbitrary precision,powerful antinoise and the capability of repair and so on,this paper adopts RBFNN model to reconstruct free-form surface,and constitutes RBFNN model fitting to surface reconstruction.The paper makes theoretical analysis and makes experiment on the NURBS surface.The result indicates that this model not only can efficiently approach the surface which is not perfect and has noise,but also the speed of learning is very quick.This can improve efficiency and precision of dirty,imperfect surface reconstruction,and the smooth of surface which is got is good.

关 键 词：逆向工程 曲面重构 非均匀有理B样条 神经网络 径向基函数 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]