In MNE time frequency is improtant for any further analysis for MEG EEG and fMRI here I address some from the toturials just for a remark. 1. Time Frequency functions in MNE all the output data will be the following

you will be surprised by this error in keras it is just beause you do not make the last layer as Dense(output_dim) or it will give this error, I’m so upset about this . model.add(Dense(4, activation=’softmax’)) here 4 is the

In Keras we could use LSTM,GRU,SimpleRNN just as simple as in sklearn. here we mainly wonder to share some thing about LSTM,which could be divied into two subclass LSTM with statful or without stateful Input_shape, [samples，timesteps，input_dim] here, samples is the

Gets to 99.25% test accuracy after 12 epochs (there is still a lot of margin for parameter tuning). 16 seconds per epoch on a GRID K520 GPU. ”’ from __future__ import print_function import keras from keras.datasets import mnist from keras.models

from keras.models import Sequential from keras.layers import Dense,Activation,Dropout from keras.optimizers import RMSprop import keras from keras.datasets import mnist batch_size = 128 %% 批量训练的值 num_classes = 10 %%标签种类 epochs = 20 %% 重复训练的次数 # the data, split between train and test