J4 ›› 2010, Vol. 40 ›› Issue (1): 222-226.

• 地球探测与信息技术 • 上一篇    

求解大样本核主成分分析模型的Lanczos算法

陈永良,林楠,李学斌   

  1. 吉林大学 |综合信息矿产预测研究所|长春 130026
  • 收稿日期:2009-03-12 出版日期:2010-01-26 发布日期:2010-01-26
  • 作者简介:陈永良(1965-)|男|辽宁朝阳人|教授|主要从事矿产资源评价、数学地质方法、遥感图像处理和GIS应用等方面的研究|E-mail:chenyongliang2009@hotmail.com
  • 基金资助:

    国家自然科学基金项目(40872193)

Lanczos Algorithm for Kernel Principle Component Analysis on Large Scale Samples

 CHEN Yong-liang, LIN Nan, LI Xue-bin   

  1. Institute of Mineral Resources Prognosis Synthetic Information, Jilin University, Changchun 130026,China
  • Received:2009-03-12 Online:2010-01-26 Published:2010-01-26

摘要:

求解核主成分分析模型的技术关键是确定核矩阵端部的较大特征对。把求解大规模对称矩阵端部特征对问题的基本方法--Lanczos算法应用于核主成分分析模型的求解,设计了大样本核主成分分析模型求解的实用算法。在clapack和nuTRLan两个软件包的基础上,开发了大样本核主成分分析模型求解算法的VC++程序。用高光谱遥感图像数据进行模型求解算法的应用试验研究,证明了大样本核主成分分析模型求解算法的实用性。

关键词: 大样本, 核主成分分析, Lanczos算法, Thick-重启动策略

Abstract:

The key technique for solving the problem of kernel principle component analysis is to determine the several biggest eigenpairs of the kernel matrix. Lanczos algorithm is applied to the problem. Basing on the method, along with the thick-restart strategy, a highly effective algorithm is laid out. A corresponding visual C++ program for computing the parameters of a kernel component analysis model on large scale samples is developed on clapack and nu-TRLan software packages. Experiments are conducted to process hyperspectral remote sensing images to get the kernel principle components. The results illustrate the practicability of the algorithm in computing the parameters of a kernel principle component analysis model for large scale samples.

Key words: large scale samples, kernel principle component analysis, Lanczos algorithm, Thick-restart strategy

中图分类号: 

  • P628
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[2] 余先川, 刘立文, 胡丹, 王仲妮. 基于稳健有序独立成分分析(ROICA)的矿产预测[J]. J4, 2012, 42(3): 872-880.
[3] 李春华, 路来君, 王抵修. 地球化学元素空间定量组合求异模型及其应用[J]. J4, 2010, 40(2): 461-468.
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