Application of JADE to separate complex-valued sources

Blind source separation (BSS) denotes observing mixtures of independent sources, and by making use of these mixtures signals only and nothing else ,recovering the original signals. Joint Approximative Diagonalization of Eigenmatrices (JADE) is a statistic-based method for transforming an observed random vector into components that are as mutually independent as possible. In this paper, we employ JADE for separating the complex-valued signals. Results of the simulation show that the JADE can separate the complex-valued sources form the observations effectively.