In this contribution simple RD-CNN models are determined in numerical optimization procedures in order to approximate short segments of EEG signals. Thereby ...
Abstract—Cellular Nonlinear Networks (CNN) are charac- terized by local couplings of comparatively simple dynamical systems.
EEG. Conference Paper. Identification of EEG signals in epilepsy by cell outputs of Reaction-Diffusion Networks. January 2006. DOI:10.1109/IJCNN.2006.1716821.
Identification of EEG signals in epilepsy by cell outputs of Reaction-Diffusion Networks. In Proceedings of the International Joint Conference on Neural ...
Identification of EEG signals in epilepsy by cell outputs of Reaction-Diffusion Networks · Frank Gollas · Ronald Tetzlaff.
Jun 3, 2023 · The brain's electrical signals can be analyzed through the five frequency bands produced by the EEG [7]: delta, alpha, theta, gamma and beta.
Missing: Reaction- Diffusion
Sep 12, 2023 · In this paper we study the Cellular Neural Networks (CNN) computing for spatiotemporal analysis of EEG. CNN are programmable processors with spatial structures.
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Aug 20, 2008 · Tetzlaff. Identification of eeg signals in epilepsy by cell outputs of reaction-diffusion networks. In Proceedings of the IEEE World ...
Epileptic networks are characterized by two outputs: brief interictal spikes and rarer, more prolonged seizures. Although either output state is readily ...
Identification of EEG signals in epilepsy by cell outputs of Reaction-Diffusion Networks · F. GollasR. Tetzlaff. Computer Science, Medicine. The 2006 IEEE ...