eeg Data Analysis

converting to torch long

y = y.to(torch.long)

transforms.toTensor

It changes the dimension

differential entropy

EEG Feature Extraaction and Data Augmentation in Emotion Reognition

• Problem Statement
  • Lacl of EEG datasets and high dimensional EEG recordings lead difficulty in building accurate emotional analysis models.

Contribution

• Using SVM and deep generative models were used to build emotional analysis model.
• Using COnditional Wasserstein GAN to create features in eeg datsets.

Introduction