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