Um Estudo sobre Separação Cega de Fontes e Análise de Componentes Independentes

This work is a study of a technique of Blind Source Separation called Independent Component Analysis (ICA). Some of the most important ICA methods will be presented: maximization of kurtosis, negentropy and likelihood and minimization of mutual information. These methods will be implemented and validated for synthetic signals within the software MATLAB. A test with real audio signals will also be carried out.