EEG signal compression based on classified signature and envelope vector sets

International Journal of Circuit Theory and Applications

Volumn 37, Issue 2, 2009, Pages 351-363

  Gürkan, Hakan ^a   Guz, Umit ^a,b   Yarman, B Siddik ^c  

^a ISIK UNIVERSITY   (Turkey)

^b INTERNATIONAL COMPUTER SCIENCE INSTITUTE   (United States)

^c ISTANBUL UNIVERSITY   (Turkey)

Author keywords

Compression; EEG; Modeling

Indexed keywords

CLUSTERING ALGORITHMS; VECTORS; VISUAL COMMUNICATION;

A-FRAMES; COMPRESSION; DIAGNOSTIC INFORMATIONS; EEG; EEG SIGNALS; EVALUATION METRICS; GAIN COEFFICIENTS; GENERATION PROCESS; HIGH COMPRESSION RATIOS; K-MEANS CLUSTERING ALGORITHMS; MODELING; NOVEL METHODS; PERCENTAGE ROOT-MEAN-SQUARE DIFFERENCES; RECONSTRUCTION ERRORS; ROOT-MEAN-SQUARE ERRORS; SIGNATURE VECTORS; VISUAL INSPECTIONS;

ELECTROENCEPHALOGRAPHY;

EID: 61349157343     PISSN: 00989886     EISSN: 1097007X     Source Type: Journal    
DOI: 10.1002/cta.548     Document Type: Conference Paper

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