Feature extraction in epilepsy using a cellular neural network based device first results
Publikation: Beitrag in Fachzeitschrift › Konferenzartikel › Beigetragen › Begutachtung
Beitragende
Abstract
In this paper the bioelectrical activity of a human brain in epilepsy will be analyzed using a Cellular Neural Network - Universal Machine (CNN-UM) proposed by Roska. Therefore a feature extraction method based on binary input-output patterns and boolean CNN with linear weight functions called pattern detection algorithm is used. First results of a hardware application with a CNN-UM realized as a mixed-mode array processor will be presented.
Details
Originalsprache | Englisch |
---|---|
Seiten (von - bis) | III850-III853 |
Fachzeitschrift | Proceedings - IEEE International Symposium on Circuits and Systems |
Jahrgang | 3 |
Publikationsstatus | Veröffentlicht - 2003 |
Peer-Review-Status | Ja |
Konferenz
Titel | Proceedings of the 2003 IEEE International Symposium on Circuits and Systems |
---|---|
Dauer | 25 - 28 Mai 2003 |
Stadt | Bangkok |
Land | Thailand |
Externe IDs
ORCID | /0000-0001-7436-0103/work/173513969 |
---|