Non-negative Independent Component Analysis Algorithm Based on 2D Givens Rotations and a Newton Optimization

Abstract : In this paper, we consider the Independent Component Analysis problem when the hidden sources are non-negative (Non-negative ICA). This problem is formulated as a non-linear cost function optimization over the special orthogonal matrix group SO(n). Using Givens rotations and Newton optimization, we developed an effective axis pair rotation method for Non-negative ICA. The performance of the proposed method is compared to those designed by Plumbley and simulations on synthetic data show the efficiency of the proposed algorithm.
Keywords : Givens rotation NMF ICA
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Submitted on : Wednesday, October 13, 2010 - 3:32:51 PM
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Wendyam Ouedraogo, Antoine Souloumiac, Christian Jutten. Non-negative Independent Component Analysis Algorithm Based on 2D Givens Rotations and a Newton Optimization. 9th International Conference Latent Variable Analysis and Signal Separation (LVA/ICA 2010), Sep 2010, Saint Malo, France. pp.522-529. ⟨hal-00526058⟩

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