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目的为更加有效地处理强弱信号混合这一特殊盲源分离问题。方法根据阵列信号处理模型与盲源分离模型之间的一致性,以最小输出能量为准则推导了相应的约束条件,并求得线形约束最小方差下的解,即对真实信源的估计;实验中采用强背景噪声EEG与诱发脑电(EP)作为源信号,利用本文方法对其混合信号进行处理。结果该方法能够有效地从强背景噪声EEG中将弱信号EP提取出来,具有很好的有效性和鲁棒性。结论与独立分量分析等经典的盲源分离方法相比,该算法不需要求解解混矩阵,计算量小,在低信噪比情况下能够准确地估计出信源。
The purpose is to deal with the special blind source separation problem of the strong and weak signal mixture more effectively. According to the consistency between the array signal processing model and the blind source separation model, the corresponding constraint conditions are deduced based on the minimum output energy, and the solution of the minimum variance of the linear constraint is obtained, that is, the estimation of the true source. The experiment In the use of strong background noise EEG and evoked electroencephalography (EP) as the source signal, the use of this method to process their mixed signal. Results The proposed method can effectively extract the weak signal EP from the strong background noise EEG, and has good efficiency and robustness. Conclusion Compared with the classical blind source separation methods such as independent component analysis, the proposed algorithm does not need to solve the matrices and has low computational complexity and can accurately estimate the signal source under low signal-to-noise ratio.