A Fixed-Point Algorithm for Nonnegative Independent Component Analysis

This paper proposes a fixed-point algorithm for nonnegative independent component analysis, based on the mutual independency of source signals and `nonpositive´ parts of source signals. The algorithm is computationally simple, provides fast convergence and does not need choose any learning step sizes. Simulations by independent source signals which are nonnegative and well grounded verify the efficient implementation of the proposed method.