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 |
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| 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 |
| Externally published | Yes |
Conference
| Title | IEEE International Symposium on Circuits and Systems 2004 |
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| Abbreviated title | ISCAS 2004 |
| Duration | 23 - 26 May 2004 |
| Location | Sheraton Vancouver Wall Centre Hotel |
| City | Vancouver |
| Country | Canada |
External IDs
| ORCID | /0000-0001-7436-0103/work/173513964 |
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