Deformed Statistics Free Energy Model for Source Separation using Unsupervised Learning

Details Deformed Statistics Free Energy Model for Source Separation using Unsupervised Learning Deformed Statistics Free Energy Model for Source Separation using Unsupervised Learning

2011-02-26

arxiv.org/abs/1102.5396v1

Physics

Condensed Matter

Statistical Mechanics

5 pages, 2 figures

Scientific paper

A generalized-statistics variational principle for source separation is formulated by recourse to Tsallis' entropy subjected to the additive duality and employing constraints described by normal averages. The variational principle is amalgamated with Hopfield-like learning rules resulting in an unsupervised learning model. The update rules are formulated with the aid of q-deformed calculus. Numerical examples exemplify the efficacy of this model.

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