Application of Ica in blind source separation

Abstract

The fundamental area in this project is Application of Independent Component Analysis (ICA) in Blind Source Separation. ICA is a tool for discovering structure and patterns in data by factoring a multidimensional data distribution into a product of onedimensional, statistically independent component distributions. Traditional ICA methods, however, can be limited in the flexibility of their decompositions and in the modeling of component distributions.