| 基于自然梯度的独立子空间盲信号处理方法 |
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| 引用本文： | 王法松,张林让.基于自然梯度的独立子空间盲信号处理方法[J].南京大学学报(自然科学版),2011(4):420-425. |
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| 作者姓名： | 王法松 张林让 |
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| 作者单位： | 西安电子科技大学雷达信号处理国防科技重点实验室;中国电子科技集团公司第二十七研究所; |
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| 基金项目： | 国家自然科学基金(61071188); 国家高技术研究发展计划(2010AAXXX1402B) |
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| 摘 要： | 作为盲信号处理的独立成分分析方法的扩展,独立子空间分析具有更广阔的应用前景.本文首先给出了独立子空间分析的一般定义和正则化定义,同时把其与独立成分分析方法进行了对比.此外,讨论了独立子空间分析的可分离性与解的唯一性问题.基于极大似然估计和自然梯度方法,本文给出了独立子空间分析的自然梯度算法.仿真实验通过二维的独立子空间...
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| 关 键 词： | 独立成分分析 盲源分离 独立子空间分析 极大似然 自然梯度 |
Independent subspace analysis for blind signal separation using natural gradient algorithm |
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| Wang Fa-Song,Zhang Lin-Rang.Independent subspace analysis for blind signal separation using natural gradient algorithm[J].Journal of Nanjing University: Nat Sci Ed,2011(4):420-425. |
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| Authors: | Wang Fa-Song Zhang Lin-Rang |
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| Institution: | Wang Fa-Song1,2,Zhang Lin-Rang1 (1.National Key Laboratory for Radar Signal Processing,Xidian University,Xi'an,710071,China,2.China Electronics Technology Group Corporation,the 27th Research Institute,Zhengzhou,450047,China) |
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| Abstract: | Standard blind signal separation(BSS) model and methods have been successfully applied to many areas of science.The basic model assumes that the observed signals are linear superpositions of underlying hidden source signals.Most of the blind signal separation algorithms are based on the independent assumption of the source signals,and are called independent component analysis(ICA).However,the independence property of sources may not hold in some real-world situations,especially in biomedical signal processi... |
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| Keywords: | independent component analysis blind signal separation independent subspace analysis maximum likelihood natural gradient |
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