Normalised natural gradient algorithm for the separation of cyclostationary sources

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 respons...

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Bibliographic Details

Main Authors:	Maria G. Jafari, Jonathon Chambers
Format:	Default Conference proceeding
Published:	2003
Subjects:	Mechanical engineering not elsewhere classified Adaptive filters Adaptive signal processing Convergence of numerical methods Gradient methods Learning (artificial intelligence) Source separation Mechanical Engineering not elsewhere classified
Online Access:	https://hdl.handle.net/2134/5756
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