DocumentCode
1668382
Title
Feature selection via orthogonal expansion of MEG signals
Author
Angelidou, A. ; Strintzis, M.G. ; Anas, S.F. ; Anogianakis, G.
Author_Institution
Dept. of Electr. Eng., Aristotelian Univ. of Thessaloniki, Greece
fYear
1991
Firstpage
786
Abstract
The processing of magnetoencephalogram (MEG) signals via orthogonal expansion is examined. The Karhunen-Loeve expansion is used as a tool for feature selection in order to lower the dimensionality of the data and achieve data compression. Data reduction achieved through this method is approximately 6:1. A comparison with the data reduction achieved via autoregressive modeling is made, and the advantages and disadvantages of the Karhunen-Loeve method are discussed
Keywords
biomagnetism; biomedical measurement; brain; data compression; data reduction; signal processing; Karhunen-Loeve expansion; autoregressive modeling; brain magnetism; data compression; data dimensionality; data reduction; feature selection; magnetoencephalogram signals processing; orthogonal expansion; Autocorrelation; Brain modeling; Calibration; Data analysis; Data compression; Eigenvalues and eigenfunctions; Magnetic fields; Scalp; Signal processing; Vectors;
fLanguage
English
Publisher
ieee
Conference_Titel
Electrotechnical Conference, 1991. Proceedings., 6th Mediterranean
Conference_Location
LJubljana
Print_ISBN
0-87942-655-1
Type
conf
DOI
10.1109/MELCON.1991.161956
Filename
161956
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