Introduction: I have encephalogram (EEG) data recorded from 32 electrodes. I already did preprocess and epoch extraction. My motivation is segmenting the data for pattern recognition task. I used R-package MLP DNN in MXNet which I am not sure about the quality of the results.
The question: I want to do segmentation(clustering in this case) or classification on this time domain data. For example, the data structure is the matrix with 1200 time samples rows x 32 electrodes columns. If the number of classes is for example 6 (i.e. according to the 10-fold cross-validation method), which Deep learning NNs can be useful and applicable for this task? (could you introduce networks in Matlab or R-packages)