Motor imaginary signal classification using adaptive recursive bandpass filter and adaptive autoregressive models for brain machine interface designs
The noteworthy point in the advancement of Brain Machine Interface (BMI) research is the ability to accurately extract features of the brain signals and to classify them into targeted control action with the easiest procedures since the expected beneficiaries are of disabled. In this paper, a new fe...
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Main Authors: | Jeyabalan, V., Samraj, A., Kiong, L.C. |
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Format: | Article |
Published: |
2008
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Subjects: | |
Online Access: | http://eprints.um.edu.my/5162/ http://oaj.unsri.ac.id/files/waset/v3-4-32-1.pdf |
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