Incremental Learning Method of Simple-PCA

  • Authors:

  • Tadahiro Oyama;Stephen Karungaru;Satoru Tsuge;Yasue Mitsukura;Minoru Fukumi

  • Affiliations:

  • Department of Information Science and Intelligent Systems, University of Tokushima, Tokushima, Japan 770-8506;Department of Information Science and Intelligent Systems, University of Tokushima, Tokushima, Japan 770-8506;Department of Information Science and Intelligent Systems, University of Tokushima, Tokushima, Japan 770-8506;Graduate School of Bio-Applications and Systems Engineering, Tokyo University of Agriculture and Technology, Tokyo, Japan 184-8588;Department of Information Science and Intelligent Systems, University of Tokushima, Tokushima, Japan 770-8506

  • Venue:
  • KES '08 Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part II
  • Year:
  • 2008

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Abstract

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.