Project 1 Machine Learning
1.EmoDB dataset with SVM emotion classification
Train SVM machine learning model using the IS09 feature set of the EmoDB dataset.
Result of the project, accuracy more than 75% :
Core code using Python:
MNIST handwritten digit dataset image recognition
Designing a deep learning model to classify the MNIST dataset using Pytorch and achieve very high accuracy.
Result, more than 98%:
Model code:
Core code:
Project 2 Signal processing using MATLAB
Only a subset of the operations that can be performed using MATLAB will be demonstrated.
1.Wavelet transformation for filtering.
Result, remove 50Hz noise:
2.Obtain the Hilbert spectrum.
Project 3 EEG signal processing using MATLAB
The project mainly aims to identify differences between normal individuals and patients using EEG signals.
Preprocess, segment, and perform statistical analysis on EEG signals.
(Due to confidentiality reasons, only a portion of the results will be presented.)
