📌EDAN

🍊 Overview: Minimizing the Difference Across Electrodes in Single-Source to Single-Target Motor Imagery Classification.

🧰 Train the model (Three Steps)

🍊 The model code is in the “EDANModel.py”.

🍊 Before running the application, ensure that you have the following prerequisites installed:

  1. **Python:** The code is tested with Python 3.8. It should be compatible with most Python 3.x versions.
  
  2. **PyTorch:** This project requires PyTorch. If you haven't installed PyTorch yet, you can find installation instructions on the [official PyTorch website](https://pytorch.org/get-started/locally/).

📕 Step 1: Calculating the electrode tradeoff

🍊 The magnitude of the tradeoff is determined by the relative positions of two different electrodes (electrode pairs), The weight function can be computed by:

📕 Step 2: Setting the parameters in the EDAN model

🍊 The “electrode channel numbers” and the “feature map numbers” need to be specific according to your datasets.

📕 Step 3: Run the model and optimize all the loss functions