Determining the number of principal components for best reconstruction

被引:150
作者
Qin, SJ [1 ]
Dunia, R [1 ]
机构
[1] Univ Texas, Dept Chem Engn, Austin, TX 78712 USA
基金
美国国家科学基金会;
关键词
principal component analysis; missing values; sensor reconstruction; principal component subspace; residual subspace;
D O I
10.1016/S0959-1524(99)00043-8
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:245 / 250
页数:6
相关论文
共 15 条
[1]  
[Anonymous], 1989, MULTIVARIATE CALIBRA
[2]   SCREE TEST FOR NUMBER OF FACTORS [J].
CATTELL, RB .
MULTIVARIATE BEHAVIORAL RESEARCH, 1966, 1 (02) :245-276
[3]   Identification of faulty sensors using principal component analysis [J].
Dunia, R ;
Qin, SJ ;
Edgar, TF ;
McAvoy, TJ .
AICHE JOURNAL, 1996, 42 (10) :2797-2812
[4]  
DUNIA R, IN PRESS COMPUT CHEM
[5]  
HARMON JL, 1995, COMPUT CHEM ENG, V19, P1287
[6]  
JORESKOG KG, 1976, GEOLOGICAL FACTOR AN
[7]   Disturbance detection and isolation by dynamic principal component analysis [J].
Ku, WF ;
Storer, RH ;
Georgakis, C .
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, 1995, 30 (01) :179-196
[8]   STATISTICAL PROCESS-CONTROL OF MULTIVARIATE PROCESSES [J].
MACGREGOR, JF ;
KOURTI, T .
CONTROL ENGINEERING PRACTICE, 1995, 3 (03) :403-414
[9]  
Malinowski E.R., 1991, FACTOR ANAL CHEM
[10]   MULTIVARIATE SPC CHARTS FOR MONITORING BATCH PROCESSES [J].
NOMIKOS, P ;
MACGREGOR, JF .
TECHNOMETRICS, 1995, 37 (01) :41-59