Application of Ica in blind source separation
That Mon Htwe · DR-NTU (Nanyang Technological University) · 2005
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.