Asymptotic analysis of the generalized symmetric FastICA algorithm

This contribution deals with the generalized symmetric FastICA algorithm in the domain of Independent Component Analysis (ICA). The generalized symmetric version of FastICA has the potential to achieve the optimal separation performance by allowing the usage of different nonlinearity functions in its parallel implementations of one-unit FastICA. In spite of this appealing property, a rigorous study of the asymptotic error of the generalized symmetric FastICA algorithm is still missing in the community. In this work, we aim at filling this blank. The main result of this contribution is the original analytic expression for the asymptotic covariance matrix of the generalized FastICA algorithm.