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.

References in zbMATH (referenced in 25 articles )

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  1. Cappello, Claudia; De Iaco, Sandra; Palma, Monica: Computational advances for spatio-temporal multivariate environmental models (2022)
  2. Chen, You-Lin; Kolar, Mladen; Tsay, Ruey S.: Tensor canonical correlation analysis with convergence and statistical guarantees (2021)
  3. Klaus Nordhausen, Markus Matilainen, Jari Miettinen, Joni Virta, Sara Taskinen: Dimension Reduction for Time Series in a Blind Source Separation Context Using R (2021) not zbMATH
  4. Lee, Seonjoo; Shen, Haipeng; Truong, Young: Sampling properties of color independent component analysis (2021)
  5. Nordhausen, Klaus; Fischer, Gregor; Filzmoser, Peter: Blind source separation for compositional time series (2021)
  6. Tounsi, Mariem; Zitouni, Mouna: Matrix-variate Lindley distributions and its applications (2021)
  7. Virta, Joni; Lietzén, Niko; Ilmonen, Pauliina; Nordhausen, Klaus: Fast tensorial JADE (2021)
  8. Virta, Joni; Nordhausen, Klaus: Determining the signal dimension in second order source separation (2021)
  9. Prasadan, Arvind; Nadakuditi, Raj Rao: Time series source separation using dynamic mode decomposition (2020)
  10. Radojičić, Una; Nordhausen, Klaus: Non-Gaussian component analysis: testing the dimension of the signal subspace (2020)
  11. Virta, Joni; Li, Bing; Nordhausen, Klaus; Oja, Hannu: Independent component analysis for multivariate functional data (2020)
  12. Jin, Ze; Risk, Benjamin B.; Matteson, David S.: Optimization and testing in linear non-Gaussian component analysis (2019)
  13. Matilainen, Markus; Croux, C.; Nordhausen, K.; Oja, H.: Sliced average variance estimation for multivariate time series (2019)
  14. Maghrebi, Houssem; Prouff, Emmanuel: On the use of independent component analysis to denoise side-channel measurements (2018)
  15. Virta, Joni; Li, Bing; Nordhausen, Klaus; Oja, Hannu: JADE for tensor-valued observations (2018)
  16. Jari Miettinen and Klaus Nordhausen and Sara Taskinen: Blind Source Separation Based on Joint Diagonalization in R: The Packages JADE and BSSasymp (2017) not zbMATH
  17. Virta, Joni; Li, Bing; Nordhausen, Klaus; Oja, Hannu: Independent component analysis for tensor-valued data (2017)
  18. Qian, Guobing; Wei, Ping; Liao, Hongshu: Efficient variant of noncircular complex FastICA algorithm for the blind source separation of digital communication signals (2016)
  19. Taskinen, Sara; Miettinen, Jari; Nordhausen, Klaus: A more efficient second order blind identification method for separation of uncorrelated stationary time series (2016)
  20. Matilainen, Markus; Nordhausen, Klaus; Oja, Hannu: New independent component analysis tools for time series (2015)

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