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ICA-based Matrix/Tensor Decomposition

git clone https://github.com/rikenbit/iTensor/R CMD INSTALL iTensor

or type the code below in the R console window

library(devtools)devtools::install_github("rikenbit/iTensor")

• ICA
  • InfoMax
    • Bell, A. J. et al., An information-maximization approach to blind separation and blind deconvolution. Neural computation, 7(6), 1129-1159, 1995
    • Amari, S. et al., A new learning algorithm for blind signal separation. NIPS 1995, 1995
  • ExtInfoMax
    • Lee, T. W., et al., Independent component analysis using an extended infomax algorithm for mixed subgaussian and supergaussian sources. Neural computation, 11(2), 417-441, 1999
  • FastICA
    • Hyvarinen, A. Fast and robust fixed-point algorithms for independent component analysis. IEEE transactions on Neural Networks, 10(3), 626-634, 1999
  • JADE
    • Cardoso, J. F. et al., Blind beamforming for non-gaussian signals, IEE Proceedings F, 140(6), 362-370, 1993
  • AuxICA1/2
    • Ono, N. et al., Auxiliary-Function-Based Independent Component Analysis for Super-Gaussian Sources, Lecture Notes in Computer Science, 6365, 165-172, 2010
  • IPCA
    • Yao, F. et al., Independent Principal Component Analysis for biologically meaningful dimension reduction of large biological data sets, BMC Bioinformatics, 13(24), 2012
  • SIMBEC
    • Cruces, S. et al., Criteria for the simultaneous blind extraction of arbitrary groups of sources, International Conference on ICA and BSS, 740-745, 2001
  • AMUSE
    • Tong, L. et al., Indeterminacy and identifiability of blind identification, IEEE Transactions on Circuits and Systems, 38(5), 499-509, 1991
  • SOBI
    • Belouchrani, A. et al., A blind source separation technique using second-order statistics, IEEE Transactions on Signal Processing, 45(2), 434-444, 1997
  • FOBI
    • Cardoso, J.-F. et al., Source separation using higher order moments, International Conference on Acoustics, Speech, and Signal Processing, 4, 2109-2112, 1989
  • ProDenICA
    • Hastie, T. et al., Independent Components Analysis through Product Density Estimation, NIPS 2002, 2002
  • RICA
    • Le, Q. et al., ICA with Reconstruction Cost for Efficient Overcomplete Feature Learning, NIPS 2011, 2011
• GroupICA
  • Calhourn V. D. et al, A review of group ICA for fMRI data and ICA for joint inference of imaging, genetic, and ERP data. Neuroimage. 45(1 Suppl), S163-72, 2009
  • Pfister, N. et al., groupICA: Independent component analysis for grouped data. arXiv, 2018
• MICA
  • Akaho, S. et al., MICA: Multimodal independent component analysis. IJCNN'99, 2, 927-932, 1999
• MultilinearICA
  • Vasilescu, M. A. O. et al., Multilinear Independent Component Analysis, IEEE CVPR 2005, 2005
• CorrIndex
  • Sobhani, E. et al., CorrIndex: a permutation invariant performance index, Signal Processing, 195, 108457, 2022

If you have suggestions for howiTensor could be improved, or want to report a bug, open an issue! We'd love all and any contributions.

For more, check out theContributing Guide.

• Koki Tsuyuzaki