DocumentCode
3379921
Title
Prediction of brain electrical activity in epilepsy using a higher-dimensional prediction algorithm for discrete time cellular neural networks (DTCNN)
Author
Gollas, F. ; Niederhöfer, C. ; Tetzlaff, R.
Author_Institution
Inst. of Appl. Phys., Johann Wolfgang Goethe Univ., Frankfurt, Germany
Volume
5
fYear
2004
fDate
23-26 May 2004
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 as stated in M. Schetzen (1980) and CNN in L. O. Chua (1998). The outline of this paper is to propose a higher-dimensional DTCNN prediction algorithm. First results are given for the long term recording of brain electrical activity.
Keywords
discrete time systems; electroencephalography; prediction theory; signal detection; Volterra systems; brain electrical activity; discrete time cellular neural networks; electroencephalographic recordings; epilepsy; epileptic seizures; higher-dimensional prediction; nonlinear signal analysis; precursors detection; Brain; Cellular neural networks; Disk recording; Electrodes; Epilepsy; Intelligent networks; Nervous system; Physics; Prediction algorithms; Signal analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuits and Systems, 2004. ISCAS '04. Proceedings of the 2004 International Symposium on
Print_ISBN
0-7803-8251-X
Type
conf
DOI
10.1109/ISCAS.2004.1329909
Filename
1329909
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