## Free component analysis

#### Raj Rao NadakuditiUniversity of Michigan

We describe a method for unmixing mixtures of freely' independent random variables in a manner analogous to the independent component analysis (ICA) based method for unmixing independent random variables from their additive mixture. Random matrices play the role of free random variables in this context so the method we develop, which we call Free component analysis (FCA), unmixes matrices from an additive mixture of matrices. We describe the theory - the various contrast functions', computational methods and compare FCA to ICA on data derived from real-world experiments.

Back to Workshop I: Expected Characteristic Polynomial Techniques and Applications