This repository contains 3 part. Including PYTHON codes and MATLAB codes.

P300_CNN_1_GRU_A.py: A Python File in which is the model of a combination of CNN and GRU to determine if the EEG signal sequence contains P300 wave.

The brief of the model-1 (Stacked CNN & RNN): 1, A CNN is responsbile for spatial domain feature extraction. 2, A GRU is repsonsible for temporal domain feature extraction. 3, Dropout is introduced to prevent overfitting and to improve the accuracy.

The brief of model-2 (Stacked CNN)-not contained in repository: 1, A CNN is responsbile for spatial domain feature extraction. 2, A CNN is repsonsible for temporal domain feature extraction. 3, Dropout is introduced to prevent overfitting and to improve the accuracy.

List and brief description: 1, EEG_Preprocessor.py: A python file where the code for a series of EEG Signals preprocessing procedure is included. Including: load_data, extract_eegdata, extract_feature, etc.

Operations before classification:

   1) band-pass butter-6 filter to remove the noises irrelevant to classification;          
   2) using sliding averaging window to downsample signal data;

(the file below please see in the common folder)
2, classifier.py: A python file where the code for several simple classifiers for P300 classification is included. Including:

1. Fisher's Linear Discirminant Analysis;
2. Logistic Regression (Iterative reweighted least square (IRLS) by Newton-Raphson);
3. Logistic regression for binary classification using SGD algorithm;
4. Softmax Regression using SGD;

3, optimizer.py: A python file where the code for some classic optimizers is included. Including:

1. AdamOptimizer;
2. LbfgsOptimizaer;

4, regressor.py: A python file where the code for Ridge Regression is included.

5, standard.py: A python file where the code for some criterions for ML model evaluation is included.

6, CSP(Spatial_Filter).py: A python file where the code for Common Spatial Pattern, a powerful tool to realize signal data feature extraction, is included. For more about the CSP, please consult: https://blog.csdn.net/missxy_/article/details/81264953

7, ButterWorth(temporalfilter).py: A python file where the code for Common Spatial Pattern, a powerful tool to remove noises, is included.

8, utils.py: includes several machine learning gears.

(the file below please see in the Part Three folder)
It is all written in Matlab. Consult the main.m file for the code logics.