Fast incremental algorithm of simple principal component analysis

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

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)


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
Pages (from-to)112-117+15
JournalIEEJ Transactions on Electronics, Information and Systems
Issue number1
Publication statusPublished - 2009
Externally publishedYes


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

ASJC Scopus subject areas

  • Electrical and Electronic Engineering


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