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一种基于扩展Infomax的自适应学习算法
引用本文:侯艳艳.一种基于扩展Infomax的自适应学习算法[J].九江学院学报,2008,27(6):20-23.
作者姓名:侯艳艳
作者单位:枣庄学院计算机科学系,山东枣庄277160
摘    要:独立向量分析根据信源统计独立特性对观测信号进行分离运算,扩展Informax算法既能分离超高斯信号,也能分离亚高斯信号,得到广泛的应用。本文基于扩展Infomax算法特点,提出了一种自适应的学习算法,该算法使得学习步长根据信号的代价函数变化而变化,克服了扩展Infomax算法在稳态步长调整过程中的不足,仿真结果证实了该算法的有效性。

关 键 词:独立向量分析  扩展Infomax  超高斯  亚高斯

AN SELF-ADAPTIVE LEARNING ALGORITHM BASED ON EXTENDED INFOMAX
Hou Yanyan.AN SELF-ADAPTIVE LEARNING ALGORITHM BASED ON EXTENDED INFOMAX[J].JOurnal of Jiujiang University :Social Science Edition,2008,27(6):20-23.
Authors:Hou Yanyan
Abstract:Independent component analysis did signal separation operation based on independences of the observed signal.Extended Informax could separate Super-Gaussion signal and Sub-Gaussion signal,and got widely used.An improved self-adaptive learning algorithm was introduced in the paper.The algorithm made learning step change according to the cost function of signal changes,and overcame the disadvantages of extended informax algorithm in the process of step size change of adaptive steady state.The simulations had ...
Keywords:independent component analysis  extended information-maximization  super-Gaussion  sub-Gaussion  
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