计算机工程与应用 ›› 2011, Vol. 47 ›› Issue (29): 168-170.

• 图形、图像、模式识别 • 上一篇    下一篇

基于几何距离摄动的局部切空间排列算法

杨安平1,2,陈松乔1,胡 鹏2   

  1. 1.中南大学 信息科学与工程学院,长沙 410083
    2.长沙理工大学 电气与信息工程学院,长沙 410004
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2011-10-11 发布日期:2011-10-11

LTSA algorithm based on geometric distance perturbation

YANG Anping1,2,CHEN Songqiao1,HU Peng2   

  1. 1.School of Information Science and Engineering,Central South University,Changsha 410083,China
    2.School of Electrical & Information Engineering,Changsha University of Science and Technology,Changsha 410004,China
  • Received:1900-01-01 Revised:1900-01-01 Online:2011-10-11 Published:2011-10-11

摘要: 局部切空间排列算法(Local Tangent Space Alignment)是一种具有严格数学推理的流形学习算法,能有效地学习出高维数据的低维嵌入坐标,但也存在一些不足,如对近邻点的选取依赖性较强、不适应处理高曲率分布、稀疏分布数据源。针对这些缺点,提出了一种基于几何距离摄动的局部切空间排列算法。利用几何摄动条件把样本空间划分为一组线性分块的组合,在每一个线性块上应用LTSA算法完成降维。实验结果表明了该算法的有效性。

关键词: 降维, 局部切空间排列, 流形, 几何摄动, 最大线性块

Abstract: LTSA(Local Tangent Space Alignment) is a manifold learning algorithm with strict mathematical reasoning.It is efficient for many nonlinear dimension reduction problems but unfit for sparse and high curvature source data.In order to solve the problem,an LTSA algorithm based on geometric distance perturbation is presented.The original datasets have been set into some maximal linear patch according to the geometric distance perturbation.The LTSA will be applied to this maximal linear patch to complete the embedding dimensional-reduction.Experiment result validates the effectiveness of the algorithm.

Key words: dimensional-reduction, Local Tangent Space Alignment(LTSA), manifold, geometric perturbation, maximal linear patch