Orthogonal Features Based EEG Signals Denoising Using Fractional and Compressed One-Dimensional CNN AutoEncoder

no code implementations • 16 Apr 2021 • Subham Nagar, Ahlad Kumar

The study shows that the proposed fractional and compressed architecture performs better than existing state-of-the-art signal denoising methods.

Denoising EEG +1

Orthogonal Features-based EEG Signal Denoising using Fractionally Compressed AutoEncoder

no code implementations • 16 Feb 2021 • Subham Nagar, Ahlad Kumar, M. N. S. Swamy

The architecture makes use of fractional calculus to calculate the gradients during the backpropagation process, as a result of which a new hyper-parameter in the form of fractional order ($\alpha$) has been introduced which can be tuned to get the best denoising performance.

Denoising EEG