Fast principal component analysis using fixed-point algorithm
نویسندگان
چکیده
In this paper we present an efficient way of computing principal component analysis (PCA). The algorithm finds the desired number of leading eigenvectors with a computational cost that is much less than that from the eigenvalue decomposition (EVD) based PCA method. The mean squared error generated by the proposed method is very similar to the EVD based PCA method. 2007 Elsevier B.V. All rights reserved.
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عنوان ژورنال:
- Pattern Recognition Letters
دوره 28 شماره
صفحات -
تاریخ انتشار 2007