Our framework offers a holistic approach for capturing both frequency-domain characteristics and temporal dynamics of EEG signals. We evaluate four DL architectures, namely multilayer perceptron (MLP) ...

A research team led by Prof. Xie Pinhua from the Hefei Institutes of Physical Science of the Chinese Academy of Sciences has ...

This article introduces the Autoencoder Graph Ensemble Model (AEGEM), a novel ensemble-based framework ... A Graph Convolutional Network (GCN) processes stacked input-abundance maps, senders, and ...

Emotion analysis using EEG signals is one such problem that has been studied ... state of the art neural architecture for the classification task. A merged LSTM model has been proposed for binary ...

It is this brain wave model that is used to estimate the dynamic electric field potential from the measurements made by the EEG electrode array. The standard model that ignores these tissue details ...

S. Hochreiter and J. Schmidhuber, Long short-term memory, Neural Computation 9 (8) (1997) 1735–1780. Crossref, Web of Science, Google Scholar 48. M. Schuster and K. K. Paliwal, Bidirectional recurrent ...