Blind Source Separation Technique via Parallel Computing

Abstract

Blind source separation is one of the more challenging problems in signal processing where mixture of sources, sounds or any type of signals are to be separated and located without any prior information about these sources and the way they have been mixed, hence the name blind. Many methods and algorithms have been developed to tackle this problem, they are mostly complicated and computational expensive. The main aim of this paper is to study and compare these techniques that are currently used in source separation, highlighting their advantages and weaknesses. A parallel computing approach is introduced as an efficient way to enhance the current techniques of blind source separation. The benefits of the proposed technique are discussed.