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Science in China Series E: Technological Sciences

, Volume 40, Issue 6, pp 597–604 | Cite as

Convergence of algorithms used for principal component analysis

  • Junhua Zhang
  • Hanfu Chen
Article

Abstract

The convergence of algorithms used for principal component analysis is analyzed. The algorithms are proved to converge to eigenvectors and eigenvalues of a matrixA which is the expectation of observed random samples. The conditions required here are considerably weaker than those used in previous work.

Keywords

principal component analysis stochastic approximation algorithms convergence 

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Copyright information

© Science in China Press 1997

Authors and Affiliations

  • Junhua Zhang
    • 1
  • Hanfu Chen
    • 2
  1. 1.Institute of Applied MathematicsChinese Academy of SciencesBeijingChina
  2. 2.Institute of Systems ScienceChinese Academy of SciencesBeijingChina

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