Blind source separation: trends of new age - a review

Blind source separation (BSS) is a statistical approach to separate individual signals from an observed mixture of a group of signals. BSS relies on only very weak assumptions on the signals and the mixing process and this blindness enables the technique to be used in a wide variety of situations. In this paper we discuss significant challenges involved in the adaptation of existing techniques to build the system that can be useful in real world based on the survey. Results on the recent publication trends in the field are reported in retrospect of what has been achieved so far, we also conjecture what the future may hold for blind signal separation.