Incremental learning method of simple-PCA

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)


In this paper, we propose an incremental learning algorithm named Incremental Simple-PCA. This algorithm is added 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 allows to update faster the eigenvector by using incremental data. To verify the effectiveness of this algorithm, we carry out computer simulations on personal authentication that uses face images and wrist motion discrimination using wrist EMG by incremental learning. As a result, we can confirm the effectiveness from the aspects of accuracy and a computing time by comparing the Incremental PCA that gave the incremental learning function to the conventional PCA.

Original languageEnglish
Title of host publicationKnowledge-Based Intelligent Information and Engineering Systems - 12th International Conference, KES 2008, Proceedings
PublisherSpringer Verlag
Number of pages8
EditionPART 2
ISBN (Print)3540855645, 9783540855644
Publication statusPublished - 2008
Externally publishedYes
Event12th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2008 - Zagreb, Croatia
Duration: 2008 Sept 32008 Sept 5

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume5178 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other12th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2008


  • Face recognition
  • Incremental PCA
  • Incremental learning
  • Incremental simple-PCA
  • PCA
  • Simple-PCA

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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