Non-negative independent component analysis algorithm based on 2D givens rotations and a Newton optimization

Authors:
Wendyam Serge Boris Ouedraogo;Antoine Souloumiac;Christian Jutten
Affiliations:
CEA, LIST, Laboratoire d'Outils pour l'Analyse de Données, Gif-sur-Yvette, France and National School of Engineers of Tunis, Tunis, Tunisia and GIPSA-lab, CNRS, University of Grenoble, Grenob ...;CEA, LIST, Laboratoire d'Outils pour l'Analyse de Données, Gif-sur-Yvette, France;GIPSA-lab, CNRS, University of Grenoble, Grenoble Cedex, France
Venue:
LVA/ICA'10 Proceedings of the 9th international conference on Latent variable analysis and signal separation
Year:
2010

Citing 10
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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.