A New Algorithm of ICA: Using the Parametrized Orthogonal Matrixes of Any Dimensions
利用参数表示任意维数正交矩阵的ICA新算法

In independent component analysis(ICA)problems,it is the key to find an orthogonal matrix to throw away high-order redundancy between components.Orthogonal matrixes have special structures in which row vectors of them can be seen as vectors perpendicular to each other on N-sphere.A parametrization method of all the matrices of any dimensions is proposed and the completeness of the parametric presentation is proven.Further,a theoretical analysis is made for randomicity.We use genetic algorithm(GA)in searching of the optimized separating matrix.Finally,some numerical simulation results are given.