Advanced series decomposition with a gated recurrent unit and graph convolutional neural network for non-stationary data patterns

In this study, we present the EEG-GCN, a novel hybrid model for the prediction of time series data, adept at address ing the inherent challenges posed by the data’s complex, non-linear, and periodic nature, as well as the noise that fre quently accompanies it. This model synergizes signal decomposit...