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JADE (version 2.0-3)

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

Description

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) .

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Version

Install

install.packages('JADE')

Monthly Downloads

1,275

Version

2.0-3

License

GPL (>= 2)

Maintainer

Klaus Nordhausen

Last Published

March 25th, 2020

Functions in JADE (2.0-3)

NSS.JD

NSS.JD Method for Nonstationary Blind Source Separation
k_JADE

Fast Equivariant k-JADE Algorithm for ICA
rjd

Joint Diagonalization of Real Matrices
coef.bss

Coefficients of a bss Object
djd

Function for Joint Diagonalization of k Square Matrices in a Deflation Based Manner
NSS.TD.JD

NSS.TD.JD Method for Nonstationary Blind Source Separation
NSS.SD

NSS.SD Method for Nonstationary Blind Source Separation
multscatter

Function to Compute Several Scatter Matrices for the Same Data
cjd

Joint Diagonalization of Complex Matrices
MD

Minimum Distance index MD
print.bss

Printing an Object of Class bss
plot.bss

Plotting an Object of Class bss
SIR

Signal to Interference Ratio
amari.error

Amari Error
JADE-package

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

Joint Diagonalization of Real Positive-definite Matrices
AMUSE

AMUSE Method for Blind Source Separation
FOBI

Function to perform FOBI for ICA
ComonGAP

Comon's Gap
JADE

JADE Algorithm for ICA
CPPdata

Cocktail Party Problem Data
bss.components

Function to Extract Estimated Sources from an Object of Class bss
SOBI

SOBI Method for Blind Source Separation