基于拉普拉斯势函数的欠定盲分离中源数的估计

A New Method to Estimate the Number of the Sources for Underdetermined Blind Separation Based on Lapulacial Potential Function

本文提出了一种新的欠定盲源分离中源信号个数的估计算法,利用稀疏混合信号的特征,引入拉普拉斯势函数,并采用聚类算法来估计其局部最大值,由此得到源信号的个数估计。所提出的算法具有较好的抗噪声性能,对信号的稀疏度要求低。仿真实验结果说明了该算法的有效性。

In this paper, a new method is proposed to estimate the number of the sources for underdetermined blind sources separation （UBSS）. Based on the sparse mixture models, the Lapulacial potential function is introduced, and then the number of sources can be obtained by estimating the local maxim of the potential function. In order to increase the robustness to the noise and the sparsity of the sources, the clustering algorithm is exploited to estimate the local maxim of the potential function instead of directly estimating the local maxim of the potential function. The simulation results show the validity of the algorithm.