A Review of Distributed Algorithms for Principal Component Analysis

Principal component analysis (PCA) is a fundamental primitive of many data analysis, array processing, and machine learning methods. In applications where extremely large arrays of data are involved, particularly in distributed data acquisition systems, distributed PCA algorithms can harness local c...

Full description

Saved in:

Bibliographic Details
Published in:	Proceedings of the IEEE Vol. 106; no. 8; pp. 1321 - 1340
Main Authors:	Wu, Sissi Xiaoxiao, Wai, Hoi-To, Li, Lin, Scaglione, Anna
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.08.2018 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Algorithms Arrays Clustering algorithms Communication Covariance Data acquisition systems Data analysis data mining Distributed algorithms Distributed databases Machine learning Machine learning algorithms Mathematical analysis Principal component analysis Principal components analysis radar signal processing Signal processing algorithms Statistical analysis
ISSN:	0018-9219, 1558-2256
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!