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.

Version: 2.0-0
Imports: clue, graphics
Suggests: ICS, ICSNP
Published: 2017-01-09
Author: Klaus Nordhausen, Jean-Francois Cardoso, Jari Miettinen, Hannu Oja, Esa Ollila, Sara Taskinen
Maintainer: Klaus Nordhausen <klaus.nordhausen at utu.fi>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Citation: JADE citation info
Materials: ChangeLog
In views: Multivariate
CRAN checks: JADE results


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

Reverse dependencies:

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


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