A new demixer scheme for blind source separation using general neural network model

A new demixer scheme for blind source separation from instantaneous mixtures has been presented using a general neural network model. It is proven that the existing neural network demixer schemes used for blind source separation can be classed as simpler versions of the new model. Computer simulations are presented to demonstrate that the new scheme is more robust and faster to converge than the existing schemes.