Independent Subspace Analysis Using Three Scatter Matrices


  • Klaus Nordhausen University of Tampere, Finland
  • Hannu Oja University of Tampere, Finland



In independent subspace analysis (ISA) one assumes that the components of the observed random vector are linear combinations of the components of a latent random vector with independent subvectors. The problem is then to find an estimate of a transformation matrix to recover the independent subvectors. Regular independent component analysis (ICA) is a special case. In this paper we show how three scatter matrices with the so called block independence property can be used in independent subspace analysis. The procedure is illustrated with a small example.


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How to Cite

Nordhausen, K., & Oja, H. (2016). Independent Subspace Analysis Using Three Scatter Matrices. Austrian Journal of Statistics, 40(1&2), 93–101.