一种快速的零空间算法

卢桂馥 1; 2; 王勇 1; 邹健 1; 2

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一种快速的零空间算法

更新时间：2025-07-09

- 一种快速的零空间算法
- A Fast Implementation of Null Space Based Algorithm
- 西安交通大学学报 2012年46卷第2期页码：59-63
- 作者机构：
  
  1. 安徽工程大学计算机与信息学院,安徽,芜湖,241000
  2. 南京理工大学计算机科学与技术学院,南京,210094
- 作者简介：
- 基金信息：
  
  : 2011-07-02. 作者简介: 卢桂馥(1976-),男,博士生,安徽工程大学副教授. 基金项目: 国家自然科学基金资助项目(60873151)
- DOI：
  中图分类号： TP391
- 网络首发：2012-02-10，
  
  纸质出版：2012
- 稿件说明：
移动端阅览
卢桂馥 1, 2, 王勇 1, 等. 一种快速的零空间算法[J]. 西安交通大学学报, 2012,46(2):59-63.

A Fast Implementation of Null Space Based Algorithm[J]. 2012, 46(2): 59-63.
卢桂馥 1, 2, 王勇 1, 等. 一种快速的零空间算法[J]. 西安交通大学学报, 2012,46(2):59-63. DOI：

A Fast Implementation of Null Space Based Algorithm[J]. 2012, 46(2): 59-63. DOI：

摘要

为了进一步提高零空间算法的运行效率

提出了一种新的快速的零空间算法(FINBSA).FINBSA不需要进行特征值分解或奇异值分解

而只需一次正交三角(QR)分解就可以求得最佳投影矩阵

使得FINBSA的算法复杂度比现有的零空间算法要低.在PIE人脸库上的实验结果表明

FINBSA的识别率与现有的零空间算法相同

但是远比现有的零空间算法要高效

尤其是在训练样本数较多时

FINBSA的运行时间比现有零空间算法节省了100%以上.

Abstract

To improve the efficiency of null space based algorithm

a new fast implementation of null space based algorithm(FINBSA)is presented. FINBSA is carried out without any eigen-decomposition computing and singular value decomposition

by only one step of orthogonal-triangular(QR)decomposition to obtain the optimal projection matrix. Thus the computational complexity of this algorithm gets much lower than that of the other null space based ones. The experiments on PIE face database demonstrate that the recognition accuracy of FINBSA is equivalent to the other null space based algorithms

but FINBSA is more efficient especially for large size of training samples

and the running period of FINBSA is over 100% lower than that of the other existing null space based algorithms.

关键词

Keywords

references

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