Fast incremental algorithm of simple principal component analysis

Tadahiro Oyama, Stephen Githinji Karungaru, Satoru Tsuge, Yasue Mitsukura, Minoru Fukumi

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

This paper presents a new algorithm for incremental learning, which is named Incremental Simple-PCA. This algorithm adds an incremental learning function to the Simple-PCA that is an approximation algorithm of the principal component analysis where an eigenvector can be calculated by a simple repeated calculation. Using the proposed algorithm, it is possible to update the eigenvector faster by using incremental data. We carry out computer simulations on personal authentication that uses face images and wrist motion recognition that uses wrist EMG by incremental learning to verify the effectiveness of this algorithm. These results were compared with the results of Incremental PCA that introduced incremental learning function to the conventional PCA.

Original languageEnglish
JournalIEEJ Transactions on Electronics, Information and Systems
Volume129
Issue number1
DOIs
Publication statusPublished - 2009
Externally publishedYes

Fingerprint

Principal component analysis
Eigenvalues and eigenfunctions
Approximation algorithms
Authentication
Computer simulation

Keywords

  • Incremental learning
  • Incremental PCA
  • Incremental Simple-PCA
  • PCA
  • Simple-PCA

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

Cite this

Fast incremental algorithm of simple principal component analysis. / Oyama, Tadahiro; Karungaru, Stephen Githinji; Tsuge, Satoru; Mitsukura, Yasue; Fukumi, Minoru.

In: IEEJ Transactions on Electronics, Information and Systems, Vol. 129, No. 1, 2009.

Research output: Contribution to journalArticle

Oyama, Tadahiro ; Karungaru, Stephen Githinji ; Tsuge, Satoru ; Mitsukura, Yasue ; Fukumi, Minoru. / Fast incremental algorithm of simple principal component analysis. In: IEEJ Transactions on Electronics, Information and Systems. 2009 ; Vol. 129, No. 1.
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