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) , Souloumiac (2009) , Vollgraff and Obermayer . An example of application in the context of Brain-Computer Interfaces EEG denoising can be found in Gouy-Pailler et al (2010) .


README
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This package has been created during my PhD thesis and is based on different
joint approximate diagonalization algorithms, see authors pages for details.
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If you find any problem, feel free to contact me.

Reference manual

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install.packages("jointDiag")

0.4 by Cedric Gouy-Pailler, 6 years ago


https://github.com/gouypailler/jointDiag


Browse source code at https://github.com/cran/jointDiag


Authors: Cedric Gouy-Pailler <cedric.gouypailler@gmail.com>


Documentation:   PDF Manual  


GPL (>= 2) license



Imported by HDTSA, MMeM, iTensor, morpheus.

Suggested by gmGeostats.


See at CRAN