Package: jointDiag 0.4

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>, Vollgraf 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>.

Authors:Cedric Gouy-Pailler <[email protected]>

jointDiag_0.4.tar.gz
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jointDiag.pdf |jointDiag.html
jointDiag/json (API)

# Install 'jointDiag' in R:
install.packages('jointDiag', repos = c('https://gouypailler.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/gouypailler/jointdiag/issues

Uses libs:
  • openblas– Optimized BLAS

On CRAN:

6 exports 1 stars 1.82 score 0 dependencies 5 dependents 7 scripts 359 downloads

Last updated 4 years agofrom:b4f58f9859. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 05 2024
R-4.5-win-x86_64OKSep 05 2024
R-4.5-linux-x86_64OKSep 05 2024
R-4.4-win-x86_64OKSep 05 2024
R-4.4-mac-x86_64OKSep 05 2024
R-4.4-mac-aarch64OKSep 05 2024
R-4.3-win-x86_64OKSep 05 2024
R-4.3-mac-x86_64OKSep 05 2024
R-4.3-mac-aarch64OKSep 05 2024

Exports:ajdffdiagjadiagjediqdiaguwedge

Dependencies: