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
jointDiag_0.4.zip(r-4.7)jointDiag_0.4.zip(r-4.6)jointDiag_0.4.zip(r-4.5)
jointDiag_0.4.tgz(r-4.6-x86_64)jointDiag_0.4.tgz(r-4.6-arm64)jointDiag_0.4.tgz(r-4.5-x86_64)jointDiag_0.4.tgz(r-4.5-arm64)
jointDiag_0.4.tar.gz(r-4.7-arm64)jointDiag_0.4.tar.gz(r-4.7-x86_64)jointDiag_0.4.tar.gz(r-4.6-arm64)jointDiag_0.4.tar.gz(r-4.6-x86_64)
manual.pdf |manual.html
card.svg |card.png
jointDiag/json (API)

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

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

Uses libs:
  • openblas– Optimized BLAS

On CRAN:

Conda:

openblas

3.18 score 1 stars 5 packages 7 scripts 406 downloads 6 exports 0 dependencies

Last updated from:b4f58f9859. Checks:12 OK, 1 FAIL. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK114
linux-devel-x86_64OK101
source / vignettesOK167
linux-release-arm64OK105
linux-release-x86_64OK94
macos-release-arm64OK129
macos-release-x86_64OK230
macos-oldrel-arm64OK196
macos-oldrel-x86_64OK221
windows-develOK76
windows-releaseOK116
windows-oldrelOK60
wasm-releaseFAIL83

Exports:ajdffdiagjadiagjediqdiaguwedge

Dependencies: