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针对欠定情况下源数的估计、解混叠矩阵和源信号恢复关键技术,提出一种源数未知的欠定盲源分离算法,首先利用S变换和聚类技术相结合来估算源数和混叠矩阵,然后将源信号以零空间形式表示,再通过最大似然估计关于其后验概率以达到恢复源信号的目的.仿真实验结果表明了该方法不仅能同时分离服从超高斯分布和亚高斯分布的源信号,且比其他传统的方法具有更优越的估计性能.“,”Aiming to the estimation of source numbers,mixing matrix and source signals under underdetermined case,and a method of underdetermined blind source separation with an unknown number of sources was proposed.Firstly,an algorithm based on S transforms and clustering technology was introduced to estimate the number of sources and mixing mixtures.Then sources were represented as null space form,the recovery of source signals using a method based on maximum likelihood.The simulation results show that the proposed method can separate sources of super-Gaussian dis-tribution and sub-Gaussian distribution,and compared to other conventional algorithms,estimated mixing matrix and separated sources with higher accuracy.