Spectral entropy of dyslexic ERP signal by means of Adaptive Optimal Kernel

Giannakakis, GA; Tsiaparas, NN; Papageorgiou, C; Nikita, KS

dc.contributor.author	Giannakakis, GA	en
dc.contributor.author	Tsiaparas, NN	en
dc.contributor.author	Papageorgiou, C	en
dc.contributor.author	Nikita, KS	en
dc.date.accessioned	2014-03-01T02:46:32Z
dc.date.available	2014-03-01T02:46:32Z
dc.date.issued	2009	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/32700
dc.subject	Adaptive optimal kernel	en
dc.subject	EEG	en
dc.subject	ERP	en
dc.subject	Spectral entropy	en
dc.subject	Time-frequency representation	en
dc.subject.other	Adaptive optimal kernel	en
dc.subject.other	EEG	en
dc.subject.other	ERP	en
dc.subject.other	Spectral entropy	en
dc.subject.other	Time-frequency representation	en
dc.subject.other	Digital signal processing	en
dc.subject.other	Digital signal processors	en
dc.subject.other	Electroencephalography	en
dc.subject.other	Enterprise resource planning	en
dc.subject.other	Online searching	en
dc.subject.other	Optimization	en
dc.subject.other	Signal processing	en
dc.subject.other	Entropy	en
dc.title	Spectral entropy of dyslexic ERP signal by means of Adaptive Optimal Kernel	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/ICDSP.2009.5201265	en
heal.identifier.secondary	http://dx.doi.org/10.1109/ICDSP.2009.5201265	en
heal.identifier.secondary	5201265	en
heal.publicationDate	2009	en
heal.abstract	In this paper, subband spectral entropy (SSE) and its relative form was used for the analysis of rest electroencephalogram (EEG) and Event Related Potentials (ERP). The recorded signals were taken from control children and children with dyslexia. Adaptive-OptimalKernel (AOK) time-frequency representation was used to produce high resolution spectrogram. Then, SSE and relative subband spectral entropy (RSSE) were calculated. The entropic patterns of both controls and dyslexics were investigated showing differences in specific electrode recordings. © 2009 IEEE.	en
heal.journalName	DSP 2009: 16th International Conference on Digital Signal Processing, Proceedings	en
dc.identifier.doi	10.1109/ICDSP.2009.5201265	en