Wavelet De-noising for Blind Source Separation in Noisy Mixtures

Blind source separation, which supposes that the sources are independent, is a well known domain in signal processing. However, in a noisy environment the estimation of the criterion is harder due to the noise. In strong noisy mixtures, we propose two new principles based on the combination of wavelet de-noising processing and blind source separation. We compare them in the cases of white/correlated Gaussian noise.

• Type: Conference
• Year: 2004
• Where: ICA
• Authors: Bertrand Rivet, Vincent Vigneron, Anisoara Paraschiv-Ionescu, Christian Jutten
• Keywords: Blind Source Separation, ICA 2004, Strong Noisy Mixtures, Wavelet De-noising Processing