Package: jointDiag 0.4

Cedric Gouy-Pailler

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>.

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

jointDiag_0.4.tar.gz
jointDiag_0.4.zip(r-4.7-x86_64)jointDiag_0.4.zip(r-4.7-arm64)jointDiag_0.4.zip(r-4.6-x86_64)jointDiag_0.4.zip(r-4.6-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✨
DESCRIPTION
card.svg |card.png
jointDiag/json (API)

# Install 'jointDiag' in R:
install.packages('jointDiag', repos = c('https://cran.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

2.18 score 5 packages 9 scripts 331 downloads 6 exports 0 dependencies

Last updated from:084a834a58. Checks:9 OK, 1 FAIL. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK73
linux-devel-x86_64OK125
source / vignettesOK111
linux-release-arm64OK67
linux-release-x86_64OK127
windows-devel-arm64OK197
windows-devel-x86_64OK96
windows-release-arm64OK199
windows-release-x86_64OK59
wasm-releaseFAIL77

Exports:ajdffdiagjadiagjediqdiaguwedge

Dependencies: