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We propose a feature extraction method based on the Volterra autoregressive model's prediction power and the data's predictability for the EEG signals to automatically detect the epileptic EEG signals from the EEG recordings. The method of determining the embedding dimension based on nonlinear prediction is applied to choose the embedding dimension of the EEG data. The proposed feature extraction...
Topology identification of a network has received great interest for the reason that the study on many key properties of a network assumes a special known topology. Different from recent similar works in which the evolution of all the nodes in a complex network need to be received, this brief presents a novel criterion to identify the topology of a coupled FitzHugh-Nagumo (FHN) neurobiological network...
The electroencephalogram (EEG) is a set of data measured by electrodes placed on the scalp and is often under the influences of artifacts. Mental EEG is recorded when a person performs different mental tasks. In this article, we separated the mental EEG signals into independent components with individual meanings based on independent component analysis (ICA) method, and the EEG was reconstructed by...
The presence of different artifacts has long been a problem for the analysis and interpretation of electroencephalographic (EEG) recordings. Independent component analysis (ICA) is a technique for blind source separation (BSS) and has been used to remove biomedical artifacts. In order to subtract the power line noise effectively and robustly, we use two additional channels of artificial power line...
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