摘要
提出了信号源盲分离的DBBSS算法 .利用随机变量概率密度函数非参数估计的核函数法 ,对混合信号的概率密度函数及其导数进行估计 ,并由此估计信号的评价函数 (scorefunction) .解决了现有信号源盲分离算法中 ,普遍存在的非线性函数只能凭经验选取 ,以及混合信号同时包含超高斯信号和亚高斯信号时 ,算法失效的问题 .该方法非常简单 ,可以直接应用于所有以非线性函数代替评价函数的信号源盲分离算法 .
A new blind source separation algorithm called DBBSS (Density Based Blind Source Separation) is proposed.Instead of using nonlinear functions,the DBBSS algorithm use nonparametric kernel density estimation to directly estimate the score functions of the signals.The key advantage of the proposed method over many existing blind source separation algorithms is its ability to separate hybrid mixtures that contain both super Gaussian and sub Gaussian sources.The DBBSS algorithm is also very simple in implementation.Simulations show good performance of the proposed algorithm.
出处
《电子学报》
EI
CAS
CSCD
北大核心
2001年第10期1392-1396,共5页
Acta Electronica Sinica
基金
国家自然科学基金 (No .69772 0 0 1 )
