关键词: 单通道盲源分离, 边缘效应, 总体经验模式分解, 主成分分析, 独立成分分析

Abstract: Single Input Multiple Out Blind Source Separation（SIMO_BSS） is a special kind of underdetermined blind source separation. To address this problem of single channel, it usually takes the Ensemble Empirical Mode Decomposition and Independent Component Analysis combination algorithms（EEMD_ICA）. However, on the basis of the EEMD blind source separation algorithm, it produces the edge effect to reduce the signal separation accuracy. In this paper, it presents a method to suppress the edge effect through increasing prediction extreme value points, this method on the time and space complexity is significantly superior to the method based on the cycle continuation of source signals, and it is suitable for the long sequence signal. Under different SNR, through ECG mixed signal simulation, the separated performance of this method is compared with EEMD-ICA and EEMD-PCA-ICA algorithms, and experimental results show that this method outperforms the two latter algorithms with higher correlation coefficient. Finally, the practical application of this algorithm to the piezoelectric periodic signal, results show that this algorithm has obvious separation effect.

Key words: single channel blind source separation, edge effect, ensemble empirical mode decomposition, principal component analysis, independent component analysis