Machine Learning for EEG Signal Denoising: A Transformer-Based Approach to Enhancing Brain Signal Quality
This thesis delves into the application of machine learning techniques, specifically Transformers, for denoising EEG signals. The accurate capture of brain activity through EEG is critically compromised by various sources of noise, and machine learning offers a powerful paradigm for learning complex noise patterns and...