A Novel Blind Source Separation Method with Observation Vector Clustering

We propose a new method for separating sparse signals from their mixtures. Separation is achieved by clustering the normalized observation vectors and extracting each cluster as each separated signal. We show the practical result of speech separation with non-linear sensor arrangements in both a determined and an underdetermined scenarios. We also consider the musical noise problem and show the listening test results.