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Foley-Sammon鉴别矢量集理论分析及优化模型 被引量：1

The Theory Analysis on FSDVS and an Optimal Model
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摘要 1引言 Fisher线性变换方法在模式识别中有着重要的作用,其基本思想是寻找一个"最佳"投影方向,使模式投影到该方向后具有最大类间距离与最小类内距离,该方向对应的矢量称为Fisher最佳鉴别矢量.Sammon在模式识别研究中使用的鉴别平面是这一思想的发展[1]. The attribute of the maximum of R(ξ) in arbitrary subspace of Rn is discussed dedicatedly. The theory analysis indicates that every F.S discriminant vector is better than respective vector in other discriminant vectors sets, which consist of eigenvectors of sbζ = λSwξ. But,the fact that the F.S vectors are statistically correlated degrade the F. S vectors set. Two ways are used to obtain'good' F-S vectors set. The experiments on Concordia University CEN-PARMI handwritten numeral database suggest that the new vectors set is better than the origin. A new problem model on F-S discriminant vectors set is proposed in this paper. It's easily understanding that the problem model is superior to the original F-S discriminant vectors set problem model.
作者 徐勇 杨强 杨静宇
机构地区 南京理工大学计算机科学系
出处 《计算机科学》 CSCD 北大核心 2003年第9期64-66,182,共4页 Computer Science
关键词 模式识别 矢量集 FOLEY-SAMMON 鉴别 理论分析 优化模型 Pattern recognition,F-S discriminant vectors set,Feature extraction,Optimal model
分类号 TP391.4 [自动化与计算机技术—计算机应用技术]
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参考文献10

  • 1Sammon J W. An optimal discrirninant plane. IEEE Trans Comput,1970,19(9) :826-829.
  • 2Foley D H,Sammon J W. An optimal set of discriminant vectors. IEEE Trans Comput,1975,24(3) :281-289.
  • 3Duchene J ,Leclercq S. An optimal transformation for discriminant and principal component analysis. IEEE Trans on pattern analysis and machine intelligence, 1988,10(6) : 978- 983.
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同被引文献7

  • 1Sammon J W. An optimal discriminant plane [J]. IEEE Transaction on Computer, 1970, 19 (9): 826-829.
  • 2Foley D H, Sammon J W. An optimal set of discriminant vectors [J]. IEEE Transaction on Computer, 1975, 24 (3): 281-289.
  • 3Duchene J, Leclercq S. An optimal transformation for discriminant and principal component analysis. IEEE Trans on pattern analysis and machine intelligence, 1988, 10 (6): 978-983.
  • 4Jin Z, Yang J Y, Hu Z S, et al. Face recognition based on the uncorrelated discriminant transformation [J]. Pattern Recognition, 2001, 34 (7): 1 405-1 416.
  • 5Xu Y, Yang J Y, Jin Z. Theory analysis on FSLDA and ULDA [J]. Pattern Recognition, 2003, 36 (12): 3 031-3 033.
  • 6Yang J, Yang J Y, Zhang D. What's wrong with Fisher criterion? [J]. Pattern Recognition, 2002, 35 (12): 2 665-2 668.
  • 7边肇祺 张学工.模式识别[M].北京：清华大学出版社,2002..

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计算机科学
2003年 第9期

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