ICA and ICAMM Methods

  • Addisson Salazar
Part of the Springer Theses book series (Springer Theses, volume 4)


Independent component analysis (ICA) aims to separate hidden sources from their observed linear mixtures without any prior knowledge. The only assumption about the sources is that they are mutually independent. Thus, the goal is blind source estimation; although it has been recently alleviated by incorporating prior knowledge about the sources into the ICA model in the so-called semi-blind source separation. This technique has been widely used in many fields of application such as telecommunications, bioengineering, and material testing.


Mutual Information Independent Component Analysis Canonical Correlation Analysis Independent Component Analysis Leibler Divergence 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Department of Communications, School of Telecommunication EngineeringPolytechnic University of ValenciaValenciaSpain

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