回波对消中盲源分离算法的研究与仿真  

Optimization and simulation of blind source separation in acoustic echo cancellation

作　　者：张艳萍[1] 李杰[1] 

机构地区：[1]南京信息工程大学电子与信息工程学院,南京210044

出　　处：《南京信息工程大学学报（自然科学版）》2013年第6期539-543,共5页Journal of Nanjing University of Information Science & Technology（Natural Science Edition）

基　　金：江苏省自然科学基金(BK2009410)

摘　　要：盲源分离因为可以仅根据接收到的观测信号来估计还原源信号,成为近年来在信号处理领域的研究热点.针对盲源分离中的基于峭度的独立分量分析算法在源信号还原的过程中计算量较大的问题,采用共轭梯度方法对独立分量分析法进行优化,优化后的算法收敛速度更快,稳态误差变小.Matlab仿真实验表明,优化后的独立分量分析算法收敛更快,实际分离效果更好.Blind source separation is the separation of source signals from a set of mixed signals,without or with very little information about the source signals or the mixing process. Blind source separation has become a hot spot in research of signal processing in recent years. Large amount of calculation is required for source signal recovery process in blind source separation by Kurtosis based Independent Component Analysis（ ICA） algorithm,thus the conjugate gradient method is employed in this paper to optimize the ICA algorithm. The Matlab simulation results show that the improved ICA algorithm is quick in convergence speed,good in separation performance,and low in steady-state error.

关 键 词：盲源分离 独立分量分析 共轭梯度法 回波对消 

分 类 号：TN911.72[电子电信—通信与信息系统]