| 基于独立成分分析的跳频信号盲分离 |
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| 引用本文： | 王建雄,张立民,张媛.基于独立成分分析的跳频信号盲分离[J].计算机与数字工程,2011(10):64-66,165. |
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| 作者姓名： | 王建雄 张立民 张媛 |
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| 作者单位： | 海军航空工程学院电子信息工程系 烟台 264001 |
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| 基金项目： | 国家自然科学基金(编号:61032001,60972159,61002006)资助 |
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| 摘 要： | 近年来,ICA（Independent Component Analysis,独立成分分析）已成为处理BSS（Blind Source Separation,盲源分离）问题的主要手段,同时也受到人们越来越多的关注。该文首先介绍ICA,然后引入FastICA算法的推导过程,最后通过MATLAB仿真将跳频信号进行盲分离,并与梯度算法所得的仿真结果进行对比分析。通过算法验证,经FastICA处理得到的分离信号与源信号相关系数的绝对值不小于0.99,与梯度算法比较可以明显地得到FastICA是一种更为有效的跳频信号盲分离方法。
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| 关 键 词： | 独立成分分析 跳频信号 盲源分离 梯度算法 |
Blind Source Separation of Hop-Frequency Signals Based on ICA |
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| Wang Jianxiong,Zhang Limin,Zhang Yuan.Blind Source Separation of Hop-Frequency Signals Based on ICA[J].Computer and Digital Engineering,2011(10):64-66,165. |
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| Authors: | Wang Jianxiong Zhang Limin Zhang Yuan |
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| Affiliation: | Wang Jianxiong Zhang Limin Zhang Yuan(Dept.of Electronic & Information Engineering,Naval Aeronautical and Astronautical University,Yantai 264001) |
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| Abstract: | ICA（Independent Component Analysis） has been a primary method solving BSS（Blind Source Separation） in recent years,and aroused more and more concern.In this paper,ICA and FastICA algorithm were intrduced,firstly,hop-frequency signals has been separead through MATLAB,and then simulation result by FastICA,gradient algorithm were analyzed.Through verification,absolute value of correlation coefficient between separation signals and source signals is not less than 0.99.Compared with gradient algorithm,the FastICA is a more effective algorithm. |
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| Keywords: | independent component analysis blind source separation principal component analysis gradient algorithm |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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