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