DocumentCode
2533720
Title
Decomposition of MEG signals with sparse representations
Author
Özkurt, Tolga E. ; Sun, Mingui ; Sclabassi, Robert J.
Author_Institution
Univ. of Pittsburgh, Pittsburgh
fYear
2007
fDate
10-11 March 2007
Firstpage
112
Lastpage
113
Abstract
We suggest an iterative method for the decomposition of MEG signals into some user-specified parts. It is based on a technique called morphological component analysis (MCA), which seeks sparse representations. A numerical simulation is carried out to reveal the performance characteristics of this method.
Keywords
iterative methods; magnetoencephalography; medical signal processing; signal representation; MEG; iterative method; morphological component analysis; signal decomposition; sparse representations; Bayesian methods; Electroencephalography; Gaussian distribution; Independent component analysis; Iterative methods; Magnetic separation; Maximum likelihood estimation; Numerical simulation; Source separation; Surges;
fLanguage
English
Publisher
ieee
Conference_Titel
Bioengineering Conference, 2007. NEBC '07. IEEE 33rd Annual Northeast
Conference_Location
Long Island, NY
Print_ISBN
978-1-4244-1033-0
Electronic_ISBN
978-1-4244-1033-0
Type
conf
DOI
10.1109/NEBC.2007.4413304
Filename
4413304
Link To Document