Independent component analysis P20

Other Extensions In this chapter, we present some additional extensions of the basic independent component analysis (ICA) model. First, we discuss the use of prior information on the mixing matrix, especially on its sparseness. Second, we present models that somewhat relax the assumption of the independence of the components. In the model called independent subspace analysis, the components are divided into subspaces that are independent, but the components inside the subspaces are not independent. In the model of topographic ICA, higher-order dependencies are modeled by a topographic organization. Finally, we show how to adapt some of the basic ICA algorithms to...