Prediction of brain electrical activity in epilepsy using a higher-dimensional prediction algorithm for discrete time cellular neural networks (DTCNN)
Research output: Contribution to journal › Conference article › Contributed › peer-review
Contributors
Abstract
Several investigations have shown, that a higher-dimensional nonlinear signal analysis can contribute to the problem of detecting precursors for impending epileptic seizures in electroencephalographic recordings. In previous work we analyzed brain electrical activity using Volterra-Systems and CNN. The outline of this paper is to propose a new higher-dimensional DTCNN prediction algorithm. First results will be given for a long term recording of brain electrical activity.
Details
Original language | English |
---|---|
Pages (from-to) | V-720-V-723 |
Journal | Proceedings - IEEE International Symposium on Circuits and Systems |
Volume | 5 |
Publication status | Published - 2004 |
Peer-reviewed | Yes |
Conference
Title | 2004 IEEE International Symposium on Cirquits and Systems - Proceedings |
---|---|
Duration | 23 - 26 May 2004 |
City | Vancouver, BC |
Country | Canada |
External IDs
ORCID | /0000-0001-7436-0103/work/173513964 |
---|