On Statistical Pattern Recognition in Independent Component Analysis Mixture Mod
147,35 €
A natural evolution of statistical signal processing, in connection with the progressive increase in computational power, has been exploiting higher-order information. This thesis defines a novel formalism for pattern recognition and classification based on ICAMM, which unifies a certain number of pattern recognition tasks allowing generalization.
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