Elementary cost functions for blind separation of non-stationary source signals

Blind source separation (BSS) is a problem found in many applications related to acoustics or communications. This paper addresses the blind source separation problem for the case where the source signals are non-stationary and the sensors are noisy. To this end, we propose several useful elementary cost functions which can be combined to an overall cost function. The elementary cost functions might have different objectives, such as uncorrelated output signals or power normalization of the output signals. Additionally, the corresponding gradients with respect to the adjustable parameters are given. We discuss the design of an overall cost function and also give a simulation example.