期刊
JOURNAL OF PROCESS CONTROL
卷 10, 期 2-3, 页码 245-250出版社
ELSEVIER SCI LTD
DOI: 10.1016/S0959-1524(99)00043-8
关键词
principal component analysis; missing values; sensor reconstruction; principal component subspace; residual subspace
A well-defined variance of reconstruction error (VRE) is proposed to determine the number of principal components in a PCA model for best reconstruction. Unlike most other methods in the literature, this proposed VRE method has a guaranteed minimum over the number of PC's corresponding to the best reconstruction. Therefore, it avoids the arbitrariness of other methods with monotonic indices. The VRE can also be used to remove variables that ape little correlated with others and cannot be reliably reconstructed from the correlation-based PCA model. The effectiveness of this method is demonstrated with a simulated process. (C) 2000 IFAC. Published by Elsevier Science Ltd. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据