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 I 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

The Multiple Comparisons Problem fMRI An important issue in fMRI data analysis is the specification of an appropriate threshold for statistical maps. If there would be only a single voxel’s data, a conventional threshold of p < 0.05 (or p

Last month after the chinese new year, three guys from IMP went to the Gottingen for NWG worskhop, Thanks to much to Prof.Antal wavied the registration fee ,we have learnt lot of things about TDCS/TACS/TMS, there is no very clear

most of time when we finish the source reconstruction or connecivity, we are always facing the problem how we know which grid pioint belonging to which part of brain, even you have all the matrix or source model on hand.

with MNE in python, we have more opportunities to handle the eeg . on official website you could get lot of toturials , but for the resting state of data, there are but covered . 1. read the data import

I ‘m working on the motor imagery data from BBCI2A we have 9 subjects and four kinds of imagery movement, in order to make a better classification with deep learning I decide to resource it to check what’s really going

for the classification problem , the bbci 2a dataset is a very good example to test any algorithm, consider the mne with python and tensorflow I try to deconding this dataset with MNE however  mne.find_event() has some  crutical error finding