机构地区: 东南大学信息科学与工程学院无线电工程系
出 处: 《应用科学学报》 2001年第3期198-201,共4页
摘 要: 研究后非线性混合信号的盲分离 ,从最大似然角度推导了一般后非线性分离结构的学习公式 ;在前人一些工作的基础上 ,提出一种用于亚、超高斯信号后非线性混合的盲分离算法 .通过对人造及自然信号的实验 ,证实了该算法的有效性 . The problem of blind separation of signals in post-nonlinear mixture is addressed. The learning rules for the general post-nonlinear separation structure are derived by a maximum likelihood approach. An algorithm for blind separation of post-nonlinearly mixed sub- and super-Gaussian signals based on the results of previous work is proposed. The effectiveness of the algorithm is verified by experiments on artificial and natural signals.