Fourth-order cumulant-based blind identification of underdetermined mixtures
Lieven De Lathauwer, Joséphine Castaing, Jean-François Cardoso
In this paper we study two fourth-order cumulant based techniques for the estimation of the mixing matrix in underdetermined independent component analysis. The first method is based on a simultaneous matrix diagonalization. The second is based on a simultaneous off-diagonalization. The number of sources that can be allowed is roughly quadratic in the number of observations. For both methods, explicit expressions for the maximum number of sources are given. Simulations illustrate the performance of the techniques.
This package provides an implementation of the FOOBI1 algorithm discussed in the fourth-order cumulant based BSI paper.
L. De Lathauwer, J. Castaing, J.-F. Cardoso, "Fourth-order cumulant based blind identification of underdetermined mixtures," IEEE Transactions on Signal Processing, Vol. 55, No. 6, Part 2, pp. 2965-2973, June 2007.
This repository can be cited as:
S. Hendrikx, M. Boussé, N. Vervliet, M. Vandecappelle, R. Kenis, and L. De Lathauwer, Tensorlab⁺, Available online, Version of Dec 2022 downloaded from https://www.tensorlabplus.net.