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jointDiag

Joint Approximate Diagonalization of a Set of Square Matrices

v0.4 · Oct 27, 2020 · GPL (>= 2)

Description

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>.

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Maintainer: ‘Cedric Gouy-Pailler <cedric.gouypailler@gmail.com>’

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NOTE 12 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 9, 2026
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Maintainer: ‘Cedric Gouy-Pailler <cedric.gouypailler@gmail.com>’

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Maintainer: ‘Cedric Gouy-Pailler <cedric.gouypailler@gmail.com>’

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  Authors@R: person(given = "Cedric",
                    family = "Gouy-Pailler",
                    role = c("aut", "cre"),
                    email = "cedric.gouypailler@gmail.com")
as necessary.

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Dependency Network

Dependencies Reverse dependencies HDTSA MMeM iTensor gmGeostats jointDiag

Version History

new 0.4 Mar 9, 2026