Eeg siniflama i̇çi̇n bi̇r özni̇teli̇k fi̇ltreleme uygulamasi

Translated title of the contribution: A feature filtering method for eeg data classification

Yasemin Alban*, Tuba Ayhan, Onur Varol, Müştak Erhan Yalçin

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper, a feature filtering algorithm for braincomputer interface which includes classification of EEG data is proposed. By this method, the features are evaluated according to a criterion based on the Mahalanobis distance between the classes. For some EEG data classification problems, the problem may be determining the features to be extracted, however for the problem of distinguishing between right, left and forward movement imagination, the features that most benefits in classification cannot be determined beforehand. Therefore, features are selected method from a set of all possible features by the proposed filtering to increase the performance and speed of the classifier.

Translated title of the contributionA feature filtering method for eeg data classification
Original languageTurkish
Title of host publication2011 IEEE 19th Signal Processing and Communications Applications Conference, SIU 2011
Pages442-445
Number of pages4
DOIs
Publication statusPublished - 2011
Event2011 IEEE 19th Signal Processing and Communications Applications Conference, SIU 2011 - Antalya, Turkey
Duration: 20 Apr 201122 Apr 2011

Publication series

Name2011 IEEE 19th Signal Processing and Communications Applications Conference, SIU 2011

Conference

Conference2011 IEEE 19th Signal Processing and Communications Applications Conference, SIU 2011
Country/TerritoryTurkey
CityAntalya
Period20/04/1122/04/11

Funding

FundersFunder number
Qatar National Research FundNPRP 08 - 152 - 2 - 043

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