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JADE (version 2.0-4)

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

1,673

Version

2.0-4

License

GPL (>= 2)

Maintainer

Klaus Nordhausen

Last Published

September 17th, 2023

Functions in JADE (2.0-4)

k_JADE

Fast Equivariant k-JADE Algorithm for ICA
plot.bss

Plotting an Object of Class bss
multscatter

Function to Compute Several Scatter Matrices for the Same Data
rjd

Joint Diagonalization of Real Matrices
print.bss

Printing an Object of Class bss
CPPdata

Cocktail Party Problem Data
JADE-package

tools:::Rd_package_title("JADE")
ComonGAP

Comon's Gap
MD

Minimum Distance index MD
JADE

JADE Algorithm for ICA
FG

Joint Diagonalization of Real Positive-definite Matrices
FOBI

Function to perform FOBI for ICA
AMUSE

AMUSE Method for Blind Source Separation
NSS.JD

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

NSS.SD Method for Nonstationary Blind Source Separation
djd

Function for Joint Diagonalization of k Square Matrices in a Deflation Based Manner
amari.error

Amari Error
bss.components

Function to Extract Estimated Sources from an Object of Class bss
coef.bss

Coefficients of a bss Object
cjd

Joint Diagonalization of Complex Matrices
NSS.TD.JD

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

SOBI Method for Blind Source Separation
SIR

Signal to Interference Ratio