西安电子科技大学学报（自然科学版）2019，Vol.46Issue(1)：106-111,6.DOI:10.19665/j.issn1001-2400.2019.01.017
一种最大密度检测欠定混合矩阵估计算法
Estimation algorithm for an underdetermined mixing matrix based on maximum density point searching
摘要
Abstract
Aiming at mixing matrix estimation when the source number is unknown for underdetermined blind source separation (UBSS),a mixing matrix estimation method based on maximum density point searching is proposed.Based on sparse representation of observed signals,for the proposed algorithm, preprocessing of observed signals is processed first,and then the maximum density point of each observed signal is searched,after which the effective sample points are assembled,and then the source number and mixing matrix are estimated by the clustering method.For validation of the proposed algorithm,the simulations are developed by employing two sparse representation methods,which are single source point detection in the time-frequency domain and wavelet transform.Results show that the source number and the mixing matrix effect of the proposed algorithm are better than those of the reference algorithm,and that the calculation complexity of the proposed algorithm is much less than that of the reference algorithm.Further tests show that the proposed algorithm is applicable for mixing matrix estimation of positive-determined, overdetermined and underdetermined blind source separation models.关键词
欠定盲源分离/稀疏表示/最大密度检测法/源数估计/混合矩阵估计Key words
underdetermined blind source separation/sparse representation/maximum density point searching algorithm/source number estimation/mixing matrix estimation分类
信息技术与安全科学引用本文复制引用
王川川,曾勇虎,付卫红,汪连栋..一种最大密度检测欠定混合矩阵估计算法[J].西安电子科技大学学报（自然科学版）,2019,46(1):106-111,6.基金项目
国家973计划项目(61331903) （61331903）
