A New Approach to Denoising EEG Signals - Merger of Translation Invariant Wavelet and ICA

In this paper we present a new algorithm using a merger of Independent Component Analysisand Translation Invariant Wavelet Transform. The efficacy of this algorithm is evaluated byapplying contaminated EEG signals. Its performance was compared to three fixed-point ICAalgorithms (FastICA, EFICA and Pearson-ICA) using Mean Square Error (MSE), Peak Signal toNoise Ratio (PSNR), Signal to Distortion Ratio (SDR), and Amari Performance Index.Experiments reveal that our new technique is the most accurate separation method.