jointDiag: Joint Approximate Diagonalization of a Set of Square Matrices

Different algorithms to perform approximate joint diagonalization of a finite set of square matrices. Depending on the algorithm, orthogonal or non-orthogonal diagonalizer is found. These algorithms are particularly useful in the context of blind source separation. Original publications of the algorithms can be found in Ziehe et al. (2004), Pham and Cardoso (2001) <doi:10.1109/78.942614>, Souloumiac (2009) <doi:10.1109/TSP.2009.2016997>, Vollgraff and Obermayer <doi:10.1109/TSP.2006.877673>. An example of application in the context of Brain-Computer Interfaces EEG denoising can be found in Gouy-Pailler et al (2010) <doi:10.1109/TBME.2009.2032162>.

Getting started

Package details

AuthorCedric Gouy-Pailler <cedric.gouypailler@gmail.com>
MaintainerCedric Gouy-Pailler <cedric.gouypailler@gmail.com>
LicenseGPL (>= 2)
Version0.4
URL https://github.com/gouypailler/jointDiag
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("jointDiag")

Try the jointDiag package in your browser

Any scripts or data that you put into this service are public.

jointDiag documentation built on Jan. 8, 2021, 2:11 a.m.