Authors:
Vittorio Lippi
1
and
Giacomo Ceccarelli
2
Affiliations:
1
Fachgebiet Regelungssysteme Sekretariat EN11, Technische Universität Berlin, Einsteinufer 17, Berlin and Germany
;
2
Dipartimento di Fisica, Università di Pisa, Largo Bruno Pontecorvo 2, I-56127 Pisa and Italy
Keyword(s):
PCA, On-line, Incremental, Dimensionality Reduction.
Related
Ontology
Subjects/Areas/Topics:
Informatics in Control, Automation and Robotics
;
Modeling, Analysis and Control of Discrete-event Systems
;
Sensors Fusion
;
Signal Processing, Sensors, Systems Modeling and Control
;
Signal Reconstruction
Abstract:
This paper describes some applications of an incremental implementation of the principal component analysis (PCA). The algorithm updates the transformation coefficients matrix on-line for each new sample, without the need to keep all the samples in memory. The algorithm is formally equivalent to the usual batch version, in the sense that given a sample set the transformation coefficients at the end of the process are the same. The implications of applying the PCA in real time are discussed with the help of data analysis examples. In particular we focus on the problem of the continuity of the PCs during an on-line analysis.