JADE: Blind Source Separation Methods Based on Joint Diagonalization and Some BSS Performance Criteria

Cardoso's JADE algorithm as well as his functions for joint diagonalization are ported to R. Also several other blind source separation (BSS) methods, like AMUSE and SOBI, and some criteria for performance evaluation of BSS algorithms, are given. The package is described in Miettinen, Nordhausen and Taskinen (2017) <doi:10.18637/jss.v076.i02>.

Version: 2.0-3
Imports: clue, graphics
Suggests: ICS, ICSNP
Published: 2020-03-25
Author: Klaus Nordhausen ORCID iD [aut, cre], Jean-Francois Cardoso [aut], Jari Miettinen ORCID iD [aut], Hannu Oja [aut], Esa Ollila [aut], Sara Taskinen ORCID iD [aut]
Maintainer: Klaus Nordhausen <klaus.nordhausen at tuwien.ac.at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Citation: JADE citation info
Materials: ChangeLog
In views: Multivariate
CRAN checks: JADE results

Downloads:

Reference manual: JADE.pdf
Vignettes: Blind Source Separation Based on Joint Diagonalization in R: The Packages JADE and BSSasymp
Package source: JADE_2.0-3.tar.gz
Windows binaries: r-devel: JADE_2.0-3.zip, r-release: JADE_2.0-3.zip, r-oldrel: JADE_2.0-3.zip
macOS binaries: r-release: JADE_2.0-3.tgz, r-oldrel: JADE_2.0-3.tgz
Old sources: JADE archive

Reverse dependencies:

Reverse depends: ICtest, isva, MineICA, tensorBSS, tsBSS
Reverse imports: BSSasymp, fICA, osd, SpatialBSS
Reverse suggests: gmGeostats, steadyICA

Linking:

Please use the canonical form https://CRAN.R-project.org/package=JADE to link to this page.