Blind non-negative source recovery in under-determined mixtures

Abstract

Under-determined mixtures in blind source separation (BSS) are characterized by the case that they have more inputs than outputs. The classical independent component analysis (ICA) methods cannot be applied to the under-determined case. However, sparseness-based approaches can be applied to the under-determined BSS. Two steps method has been widely employed to solve the under-determined BSS problem: mixing matrix estimation and source recovery. Source recovery in under-determined BSS (UBSS) is an NP -hard problem and, therefore, does not have a closed form solution. In this paper, we proposed a new blind non-negative source recovery approach to the under-determined mixtures. The results presented in this paper are limited to non-negative sources. Simulation results illustrate the effectiveness of our method.