Normalised natural gradient algorithm for the separation of cyclostationary sources Maria G. Jafari Jonathon Chambers 2134/5756 https://repository.lboro.ac.uk/articles/conference_contribution/Normalised_natural_gradient_algorithm_for_the_separation_of_cyclostationary_sources/9555827 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. 2010-01-07 16:12:59 Adaptive filters Adaptive signal processing Convergence of numerical methods Gradient methods Learning (artificial intelligence) Source separation Mechanical Engineering not elsewhere classified