A Novel Multi-resolution Kernel Principle Component Analysis Method

摘要：

　　Focusing on the traditional kernel principle component analysis(KPCA)can not provide principle component information under the condition of multi-resolution,this paper proposes a novel multi-resolution kernel principle component analysis(MKPCA)method,by combining KPCA with high dimensional multi-resolution analysis theory.MKPCA can explore sample datas characters and principle component information on the different resolution.The experiments demonstrate the feasibility of the proposed method.

关键词： Multi-resolution principle component analysis kernel machine learning

作者: Jianjun Wu Weijun Gong Zhen Shang

作者单位: College of Information Technology and Communication,Hexi University,Zhangye,734000,China

会议类型: 国际会议

会议名称: 2019 2nd International Conference on Mechanical Engineering, Industrial Materials and Industrial Electronics (MEIMIE 2019)2019年第二届机械工程、工业材料和工业电子国际会议(Meimie 2019)

会议地点: 大连

会议语种:英文

页码: 54-57

在线出版日期: 2019-03-29（万方平台首次上网日期，不代表论文的发表时间）