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Artifacts Extraction from EEG Data Using the Infomax Approach

Paper ID Volume ID Publish Year Pages File Format Full-Text
5296 362 2011 16 PDF Available
Title
Artifacts Extraction from EEG Data Using the Infomax Approach
Abstract

The aim of the research is to detect and remove undesired components from EEG data by means of ICA approach. Besides classical signal analysis tools such as adaptive supervised filtering, parametric or non-parametric spectral estimation, time-frequency analysis, the proposed ICA technique can be used for detection of a wide group of artifacts from EEG data. In this paper a new form of nonlinearity implemented in the infomax approach is presented. As it has been proven experimentally, the proposed new sigmoidal function can effectively detect the selected group of artifacts from EEGs and is an useful approach to speed up computations.

Keywords
Independent Component Analysis; infomax algorithm; sigmoidal function; EEG data; artifacts
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Artifacts Extraction from EEG Data Using the Infomax Approach
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Publisher
Database: Elsevier - ScienceDirect
Journal: Biocybernetics and Biomedical Engineering - Volume 31, Issue 4, 2011, Pages 59–74
Authors
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Subjects
Physical Sciences and Engineering Chemical Engineering Bioengineering
Get Full-Text Now
Don't Miss Today's Special Offer
Price was $35.95
You save - $31
Price after discount Only $4.95
100% Money Back Guarantee
Full-text PDF Download
Online Support
Any Questions? feel free to contact us