DocumentCode
3463563
Title
ARMA model estimation for EEG using canonical correlation analysis
Author
Gannabathula, Prasad S S D ; Murthy, I.S.N.
Author_Institution
Dept. of Electr. Eng., Indian Inst. of Sci., Bangalore, India
fYear
1988
fDate
4-7 Nov. 1988
Firstpage
1204
Abstract
The EEG signal is modeled as an autoregressive moving-average (ARMA) process. The performance of the canonical correlation analysis algorithm to estimate the order of the AR and MA polynomials for real and simulated EEG signals is investigated. It is shown that for records of 5-s duration or more the algorithm gives good and consistent estimates of the model order and AR coefficients and is insensitive to the location of the poles relative to the unit circle. The method is also insensitive to the percentage energy in the component waves.<>
Keywords
electroencephalography; physiological models; autoregressive moving-average process; canonical correlation analysis; percentage energy; polynomials; unit circle;
fLanguage
English
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology Society, 1988. Proceedings of the Annual International Conference of the IEEE
Conference_Location
New Orleans, LA, USA
Print_ISBN
0-7803-0785-2
Type
conf
DOI
10.1109/IEMBS.1988.94875
Filename
94875
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