|Illustration of an example for an extedned SeDJoCo transformation.|
The extended “Sequentially Drilled” Joint Congruence (SeDJoCo) transformation is a special joint matrix transformation, reminiscent of (but different from) classical joint diagonalization. Interestingly, it turns out that the Maximum Likelihood (ML) solution for the Independent Vector Analysis (IVA) problem with a Gaussian model takes the form of an extended SeDJoCo problem.
This package contains five files: a (readme) detailed instruction file, two functions for an iterative solution of extended SeDJoCo—iterative relaxations and Newton’s method—and two scripts which demonstrate their operation. The first script solves a generic problem, while the second demonstrates how it is used for the computation of the ML solution of a Gaussian IVA problem. For more details, see .
To download the Matlab package, click here.
 Weiss, A., Yeredor, A., Cheema, S. A. and Haardt, M., “The Extended “Sequentially Drilled” Joint Congruence Transformation and its Application in Gaussian Independent Vector Analysis”, IEEE Transactions on Signal Processing, vol. 65, no. 23, pp. 1-13, Dec. 2017. arXiv
 Weiss, A., Yeredor, A., Cheema, S. A. and Haardt, M., “Performance Analysis of the Gaussian Quasi-Maximum Likelihood Approach for Independent Vector Analysis”, IEEE Transactions on Signal Processing, vol. 66, no. 19, pp. 5000-5013, Sept. 2018. arXiv
 Cheng, Y., Yeredor, A., Weiss, A. and Haardt, M., “Extension of the “Sequentially Drilled” Joint Congruence Transformation (SeDJoCo) Problem”, in Proc. of IEEE 6th Int. Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), pp. 185–188, Dec. 2015.