The modified natural power method for principal component computation |
| |
Authors: | Tian-ping Chen Shi-zhao Ma |
| |
Institution: | (1) Department of Mathematics, Fudan University, Shanghai, 200433, China;(2) Institute of Mathematics, Fudan University, Shanghai, 200433, China |
| |
Abstract: | A modified version of the natural power method (NP) for fast estimation and tracking of the principal eigenvectors of a vector
sequence is Presented. It is an extension of the natural power method because it is a solution to obtain the principal eigenvectors
and not only for tracking of the principal subspace. As compared with some power-based methods such as Oja method, the projection
approximation subspace tracking (PAST) method, and the novel information criterion (NIC) method, the modified natural power
method (MNP) has the fastest convergence rate and can be easily implemented with only O(np) flops of computation at each iteration, where n is the dimension of the vector sequence and p is the dimension of the principal subspace or the number of the principal eigenvectors. Furthermore, it is guaranteed to
be globally and exponentially convergent in contrast with some non-power-based methods such as MALASE and OPERA.
Selected from Journal of Fudan University (Natural Science), 2004, 43(3): 275–284 |
| |
Keywords: | PCA MCA power-based exponentially convergent |
本文献已被 万方数据 SpringerLink 等数据库收录! |
|