DocumentCode
1416328
Title
Independent component analysis: source assessment and separation, a Bayesian approach
Author
Roberts, S.J.
Author_Institution
Neural Res. Group, Imperial Coll. of Sci., Technol. & Med., London, UK
Volume
145
Issue
3
fYear
1998
fDate
6/1/1998 12:00:00 AM
Firstpage
149
Lastpage
154
Abstract
The author presents a method of independent component analysis which assesses the most probable number of source sequences from a larger number of observed sequences and estimates the unknown source sequences and mixing matrix. The estimation of the number of true sources is regarded as a model-order estimation problem and is tackled under a Bayesian paradigm. The method is shown to give good results on both synthetic and real data
Keywords
Bayes methods; estimation theory; matrix algebra; sequences; signal processing; Bayesian approach; independent component analysis; mixing matrix; model-order estimation problem; separation; source assessment; source sequences; true sources;
fLanguage
English
Journal_Title
Vision, Image and Signal Processing, IEE Proceedings -
Publisher
iet
ISSN
1350-245X
Type
jour
DOI
10.1049/ip-vis:19981928
Filename
707555
Link To Document