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Blind source separation based on improved natural gradient algorithm

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3 Author(s)
Ji Ce ; College of Information Science and Engineering, Northeastern University, Shenyang, Liaoning, China ; Yu Peng ; Yu Yang

The natural gradient algorithm is the most basic independent component analysis (ICA) algorithm. Because the traditional natural gradient algorithm adopts fixed-step-size, the choice of step size directly affects the convergence speed and steady-state performance. This paper proposes an improved natural gradient algorithm by using the difference between the separation matrixes to control the factor of step size. The algorithm is a good solution to the trade-offs problems of convergence speed and steady-state performance. Meanwhile, the complexity of the algorithm is lower than the algorithm of reference and reference. The computer simulations have proved the effectiveness of the algorithm.

Published in:

Intelligent Control and Automation (WCICA), 2010 8th World Congress on

Date of Conference:

7-9 July 2010