Chapter 20. Other Extensions

  1. Aapo Hyvärinen,
  2. Juha Karhunen and
  3. Erkki Oja

Published Online: 15 MAY 2002

DOI: 10.1002/0471221317.ch20

Independent Component Analysis

Independent Component Analysis

How to Cite

Hyvärinen, A., Karhunen, J. and Oja, E. (2001) Other Extensions, in Independent Component Analysis, John Wiley & Sons, Inc., New York, USA. doi: 10.1002/0471221317.ch20

Author Information

  1. Neural Networks Research Center, Helsinki University of Technology, Finland

Publication History

  1. Published Online: 15 MAY 2002
  2. Published Print: 21 MAY 2001

ISBN Information

Print ISBN: 9780471405405

Online ISBN: 9780471221319



  • extensions;
  • priors;
  • mixing matrix;
  • independence assumption;
  • complex-valued data


In this chapter, the authors present some additional extensions of the basic independent component analysis (ICA) model. First, they discuss the use of prior information on the mixing matrix, especially on its sparseness. Second, they present models that somewhat relax the assumption of the independence of the components. Finally, they show how to adapt some of the basic ICA algorithms to the case where the data is complex-valued instead of real-valued.