基于仿射投影一独立分量分析的盲源分离

仿射投影算法（APA）重复利用数据，可提高算法的收敛速度。针对现有盲源分离（BSS）收敛慢问题，以BSS的独立分量分析（ICA）为基础，结合APA思想，设计出BSS的APA—ME、APA—MMI、APA-EASI新算法。在这些新算法中，输出向量数据被重复利用，向量式数据转变成矩阵式数据，从而加快了BSS的收敛速度。仿真结果表明，APA—ICA类的BSS算法是有效的。...

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Bibliographic Details
Published in计算机应用研究 Vol. 34; no. 6; pp. 1721 - 1725
Main Author 李雄杰 周东华
Format Journal Article
LanguageChinese
Published 浙江工商职业技术学院电子信息工程系,浙江宁波315012 2017
清华大学自动化系,北京100084%清华大学自动化系,北京,100084
Subjects
仿射投影算法
最大熵
最小互信息
独立分量分析
盲源分离
minimum mutual information
independent component analysis
最大熵
独立分量分析
盲源分离
maximum entropy
仿射投影算法
affine projection algorithm
blind source separation
最小互信息
Online AccessGet full text
ISSN1001-3695
DOI10.3969/j.issn.1001-3695.2017.06.027

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Summary:仿射投影算法（APA）重复利用数据，可提高算法的收敛速度。针对现有盲源分离（BSS）收敛慢问题，以BSS的独立分量分析（ICA）为基础，结合APA思想，设计出BSS的APA—ME、APA—MMI、APA-EASI新算法。在这些新算法中，输出向量数据被重复利用，向量式数据转变成矩阵式数据，从而加快了BSS的收敛速度。仿真结果表明，APA—ICA类的BSS算法是有效的。
Bibliography:blind source separation; affine projection algorithm; independent component analysis; maximum entropy; minimum mutual information
51-1196/TP
Li Xiongjie1,2 , Zhou Donghua2 （ 1. Dept. of Electronic ＆ Information Engineering, Zhefiang Business Technology Institute, Ningbo Zhefiang 315012, China ; 2. Dept. of Automation, Tsinghua University, Beijing 100084, China）
Using data in a repeated mode can improve the convergence speed of the affine projection algorithm （APA）. Ai- ming at the problem of slow convergence in the existing blind source separation （BSS） , based on the independent component analysis （ICA） for BSS, this paper designed new APA-ME, APA-MMI and APA-EASI algorithms for BSS by using the idea of APA. In these new algorithms, output vector data was utilized in a repeated fashion, and the vector data was thus converted into matrix data. The convergence rate of BSS was accelerated. Simulation results show that the effectiveness and applicability of APA-ICA class BSS algorithm.
ISSN:1001-3695
DOI:10.3969/j.issn.1001-3695.2017.06.027