Least Square Joint Diagonalization of Matrices under an Intrinsic Scale Constraint

Authors:
Dinh-Tuan Pham;Marco Congedo
Affiliations:
Laboratory Jean Kuntzmann, cnrs - Grenoble INP - UJF, Grenoble, France;GIPSA-lab, cnrs - UJF - Univ. Stendhal - Grenoble INP, Grenoble, France
Venue:
ICA '09 Proceedings of the 8th International Conference on Independent Component Analysis and Signal Separation
Year:
2009

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Abstract

We present a new algorithm for approximate joint diagonalization of several symmetric matrices. While it is based on the classical least squares criterion, a novel intrinsic scale constraint leads to a simple and easily parallelizable algorithm, called LSDIC (Least squares Diagonalization under an Intrinsic Constraint. Numerical simulations show that the algorithm behaves well as compared to other approximate joint diagonalization algorithms.