Abstract
A normalised natural gradient algorithm (NGA) for the separation of cyclostationary source signals is proposed in this paper. It improves the convergence properties of the cyclostationary natural gradient algorithm (CSNGA) by employing a gradient adaptive learning rate whose value changes in response to some change in the filter parameters. Experimental results demonstrate the improved behaviour of the approach.