EEG Noise Cancellation

Noise cancellation is one of the most critical challenges in communication systems, as signals are corrupted by noise during recording or transmission. For example, when recording an EEG signal, electrical currents, ECG, and EOG can all introduce noise into the signal. There are a variety of techniques for removing noise from EEG signals, each with its own advantages and disadvantages. This section first describes linear phase filters, ICA and PCA techniques, the CCA approach, and ARMAX. Next, it explores in detail a method based on adaptive filters, supported by simulations. This method uses the noise source and a filter to generate a signal that is highly similar to the noise in the main signal, and the noise is then removed.

Keywords:Signal Processing; Denoising; Adaptive Filters; LMS Algorithms
Course: Adaptive Filters
Programming Language: MATLAB
Code