1112003001's Stars
hli1221/imagefusion_noisy_lrr
multi-focus image fusion using low-rank representation
FWen/ncreg
A Survey on Nonconvex Regularization Based Sparse and Low-Rank Recovery in Signal Processing, Statistics, and Machine Learning
moble/quaternion
Add built-in support for quaternions to numpy
beringresearch/ivis
Dimensionality reduction in very large datasets using Siamese Networks
robintibor/auto-eeg-diagnosis-example
TNTLFreiburg/brainfeatures
A toolbox to decode raw time-domain EEG using features.
mne-tools/mne-features
MNE-Features software for extracting features from multivariate time series
PyWavelets/pywt
PyWavelets - Wavelet Transforms in Python
forrestbao/pyeeg
Python + EEG/MEG = PyEEG
akrlowicz/eeg-eye-state-recognition
Using machine learning models topredict eye state of the subject based on preprocessed EEG signal. Includes preprocessing the data, feature extraction and selection, dimensionality reduction and visualization.
gauravSingh30/DeepLearning-Questions
深度学习500问,以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述,以帮助自己及有需要的读者。 全书分为18个章节,50余万字。由于水平有限,书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作,联系scutjy2015@163.com 版权所有,违权必究 Tan 2018.06
gauravSingh30/EEG-MotorActivity-Classification
EEG 4-class Motor Classification with Deep Learning Architectures and different preprocessing techniques
XiaTaopsycho/Hulab_EEG_preprocessing_tutorial
I prepared a MNE-BIDS and MNE python tutorial for Hulab
sccn/ICLabel
Automatic EEG IC classification plugin for EEGLAB
lucapton/ICLabel-Dataset
Dataset for training EEG IC classifiers.
lucapton/ICLabel-Train
Files for training the ICLabel classifier in tensorflow
ncclabsustech/DeepSeparator
Deep learning model for EEG artifact removal
ncclabsustech/EEGdenoiseNet
EEGdenoiseNet, a benchmark dataset, that is suited for training and testing deep learning-based EEG denoising models, as well as for comparing the performance across different models.
ncclabsustech/Single-Channel-EEG-Denoise
aliasvishnu/EEGNet
[Old version] PyTorch implementation of EEGNet: A Compact Convolutional Network for EEG-based Brain-Computer Interfaces - https://arxiv.org/pdf/1611.08024.pdf
pyRiemann/pyRiemann
Machine learning for multivariate data through the Riemannian geometry of positive definite matrices in Python
vlawhern/arl-eegmodels
This is the Army Research Laboratory (ARL) EEGModels Project: A Collection of Convolutional Neural Network (CNN) models for EEG signal classification, using Keras and Tensorflow
Ayantika22/Linear-discriminant-Analysis-LDA-for-Wine-Dataset
Linear discriminant Analysis(LDA) for Wine Dataset of Machine Learning
sagihaider/Common-Spatial-Pattern-Algorithm
Common spatial pattern (CSP) is a mathematical procedure used in signal processing for separating a multivariate signal into additive subcomponents which have maximum differences in variance between two windows. This algorithm is mainly used in motor imagery based BCI for processing EEG data.
spolsley/common-spatial-patterns
General CSP algorithm implementation for spatial filter construction
andacdemir/Removal-of-Ocular-Artifacts-from-EEG-Signals
Ocular Artifacts Removal in EEG Signals Using Extended-Infomax-ICA
HOORDS/01_EEG-preprocessing-with-MNE-python
mariogrune/MEMD-Python-
Python version of the Multivariate Empirical Mode Decomposition algorithm
czisou/noise_assisted_mvmd
ClimateTools/ssa
singular spectrum analysis (SSA) and multi-channel SSA