Eigenvalue decomposition based blind separation for cyclo-stationary discrete-time singals
基于特征值分解的循环平稳离散时间信号的盲分离

The goal of blind source separation methods is to restore the unknown source signals from their mixtures. Many approaches proposed exploiting some statistics associated to the temporal representation of the signals. From the point of signal frequency analysis, this paper put forward a new approach used for processing frequency-domain discrete-time signals exploiting the cyclo-stationarity of the signals. First, It constructed a product of two second-order statistics matrices, and then implemented eigenvalue decomposition of this product matrix. It also analyzed the condition of eigenvalue decomposition. The proposed method cauld derive a satisfying separation result in the case of low dimensional source signals. The simulation results using artificial sources prove the good performance of the proposed method.