| 传统独立分量分析和变分贝叶斯独立分量分析的比较 |
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| 引用本文： | 李志农,范涛,岳秀廷. 传统独立分量分析和变分贝叶斯独立分量分析的比较[J]. 江苏大学学报(自然科学版), 2010, 31(1). DOI: 10.3969/j.issn.1671-7775.2010.01.024 |
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| 作者姓名： | 李志农 范涛 岳秀廷 |
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| 作者单位： | 郑州大学,机械工程学院,河南,郑州,450001 |
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| 基金项目： | 国家自然科学基金资助项目(50775208);;河南省教育厅自然科学基金资助项目(2006C460005,2008C460003) |
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| 摘 要： | 通过试验比较了传统的独立分量分析(ICA)和变分贝叶斯独立分量分析(VbICA)在源信号分离中的能力,试验研究表明,无噪声环境下的盲源分离,两种方法都能得到很好的分离性能.然而,噪声环境下的源信号分离,变分贝叶斯独立分量明显优于传统独立分量分析,特别是随着噪声的增强,变分贝叶斯独立分量的优势就越明显.另外,变分贝叶斯独立分量可以估计源信号的数目,而传统独立分量分析往往事先假设源信号的个数已知,否则无法进行源信号分离.
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| 关 键 词： | 独立分量分析 变分贝叶斯独立分量 盲源分离 信源估计 |
Comparison of traditional independent component analysis with variational Bayesian independent component analysis |
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| Li Zhinong,Fan Tao,Yue Xiuting. Comparison of traditional independent component analysis with variational Bayesian independent component analysis[J]. Journal of Jiangsu University:Natural Science Edition, 2010, 31(1). DOI: 10.3969/j.issn.1671-7775.2010.01.024 |
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| Authors: | Li Zhinong Fan Tao Yue Xiuting |
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| Affiliation: | School of Mechanical Engineering/a>;Zhengzhou University/a>;Zhengzhou/a>;He'nan 450001/a>;China |
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| Abstract: | The capabilities of blind source separation(BSS) with the traditional independent component analysis(ICA) and with variational Bayesian independent component analysis(VbICA) were discussed and verified by the experiment.The experimental results show that both methods can give a satisfactory separation performance in a noise-free BSS.However the VbICA method is superior to the traditional ICA method in the noise BSS,especially in the lower signal-to-noise BSS.In addition,the VbICA method can estimate the opt... |
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