Fast Incremental Algorithm of Simple Principal Component Analysis

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  • Oyama Tadahiro
    Department of Information & Science Intelligent Systems, The University of Tokushima
  • Karungaru Stephen Githinji
    Department of Information & Science Intelligent Systems, The University of Tokushima
  • Tsuge Satoru
    Department of Information & Science Intelligent Systems, The University of Tokushima
  • Mitsukura Yasue
    Graduate School of Bio-Applications and Systems Engineering, Tokyo University of Agriculture and Technology
  • Fukumi Minoru
    Department of Information & Science Intelligent Systems, The University of Tokushima

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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.

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