抑制边缘效应的自适应单通道盲源分离-计算机工程与应用.PDF

130 2016 ，52（14） Computer Engineering and Applications 计算机工程与应用 ⦾模式识别与人工智能⦾ 抑制边缘效应的自适应单通道盲源分离 1 1 2 吴龙华 ，朱嘉钢 ，陆 晓 1 1 2 WU Longhua , ZHU Jiagang , LU Xiao 1.江南大学 物联网工程学院，江苏 无锡 214122 2.江南大学 晓山股份联合实验室，江苏 无锡 214122 1.School of IOT Engineering, Jiangnan University, Wuxi, Jiangsu 214122, China 2.Co-Laboratory in Hillsun Ltd., Jiangnan University, Wuxi, Jiangsu 214122, China WU Longhua, ZHU Jiagang, LU Xiao. Inhibition of edge effect of adaptive single channel blind source separation. Computer Engineering and Applications, 2016, 52 （14）：130-135. 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 com- ponent analysis; independent component analysis