Source Separation Techniques Applied to Blind Deconvolution of Real World Signals

The In this paper we present a method for blind deconvolution of linear channels based on source separation techniques, for real word si gnals. This technique applied to blind deconvolution problems is based in exploiting not the spatial independence between signals but the temporal independence between samples of the signal. Our objective will be to minimize the mutual information of the output in order to retrieve the original signal. To make use of this idea we need that input signal be a non-Gaussian i.i.d. signal. B ec use most real world signals do not have this i.i.d. nature, we will need to pr eprocess the original signal before the transmission into the channel. Likewise we should assure that the transmitted signal has non-Gaussian statistics in or der t achieve the correct function of the algorithm. The strategy used for this prepr oc ssing will be presented in this paper.