iTensor - iTensor: An R package for independent component analysis-based matrix/tensor decomposition

Peer-reviewed software and manuscript. See the JOSS review issue for details: https://github.com/openjournals/joss-reviews/issues/5496

Independent Component Analysis (ICA) is a widely used algorithm to extract a small number of mutually independent source signals in high-dimensional data. There are many applications of ICA in signal processing, neuroscience, bioinformatics, and causal discovery. ICA has been applied to matrix data but there is a growing demand to apply ICA to more heterogeneous data such as multiple matrices and tensors (high-dimensional arrays), which are higher-order data structures than matrices. To meet these requirements, I originally developed iTensor, which is an R/CRAN package to perform some ICA-based matrix/tensor decomposition algorithms (https://cran.r-project.org/web/packages/iTensor/index.html).

Zenodo doi: 10.5281/zenodo.8080600

Scientific Software - Peer-reviewed - R
Published by kokitsuyuzaki over 2 years ago

iTensor - v1.0.0

• GroupICA() are added
• 9 algorithms for ICA() are added
• Vignettes are added

Scientific Software - Peer-reviewed - R
Published by kokitsuyuzaki almost 3 years ago

iTensor - Version 0.99.0

First Release

Scientific Software - Peer-reviewed - R
Published by kokitsuyuzaki over 3 years ago