①School of Electronics and Information, Dalian University of Technology, Dalian 116024, China; ②School of Electronics and Information Engineering, Dalian Jiaotong University, Dalian 116028, China
Abstract:This paper defines analogy measure of two random variables, and discusses the principle and algorithm of maximizing non-Gaussianity of observed data with a linear transformation to estimate independent components serially. It also proves the non-polynomial moment theorem by a generalized way, and states the feasibility that substitutes the analogy with the expectation of a non-quadratic smooth even function based on the theorem. A formula to compute sign of above algorithm is given. The algorithm overcomes the contradiction between the objective function and the sign computation formula.Comparing with Maximum likelihood ICA, the analogy is Maximum likelihood function of single source under pre-whited.