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基于峭度的独立分量算法的性能分析研究 被引量：4

Research on Performance Analysis of Independent Component Algorithm Based on Kurtosis
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摘要 独立分量算法是一种应用非常广泛的盲信号处理算法。而峭度作为一种重要的信号分析工具,可以有效地进行优化分析。然而,对于各种不同类型的算法的对比分析目前还少有介绍,所以有必要对基于峭度的FastICA和RobustICA两种独立分量算法进行对比分析研究。理论分析及实验结果表明,鲁棒独立分量法RobustICA在鲁棒性、收敛性和复杂度方面整体优于快速定点独立分量法FastICA,从而为实际应用提供一定的参考价值。 Independent component analysis algorithm is a widely used algorithm for blind signal processing. As an important signal analysis tool, kurtosis can be effective for optimization and analysis. However, there is little introduction to the comparison and analysis for various types of algorithms currently. Therefore, it is necessary to research and analyze the comparison between FastlCA and RobustlCA based on kurtosis. The theoretical analysis and the simulation results indicate that the robustness, convergence and complexity of RobustlCA are better than that of FastlCA on the whole. Thus it provides the reference for practical applications.
作者 钟丽莉 熊兴中
机构地区 四川理工学院自动化与电子信息学院
出处 《四川理工学院学报（自然科学版）》 CAS 2014年第4期43-47,共5页 Journal of Sichuan University of Science & Engineering(Natural Science Edition)
基金 四川省杰出青年基金项目(2011JQ0034) 四川省省属高校科研创新团队建设计划基金项目(13TD0017) 人工智能四川省重点实验室基金项目(2012RYJ05)
关键词 峭度 快速定点独立分量法 鲁棒独立分量法 鲁棒性 收敛 复杂度 kurtosis FastlCA RobustlCA robustness convergence complexity
分类号 TN911.72 [电子电信—通信与信息系统]
  • 相关文献

参考文献13

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二级参考文献43

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共引文献21

同被引文献29

  • 1高飞,杨平先,孙兴波.基于小波变换与阀值收缩法的图像增强去噪[J].四川理工学院学报（自然科学版）,2006,19(2):8-11. 被引量：11
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  • 9Zhang J,Zhang Z S,Cheng W,et al.Kurtosis-based constrained independent component analysis and its application on source contribution quantitative estimation[J].Instrumentation and Measurement,2014,63(7):1842-1854.
  • 10Zarzoso V,Conmon P.Robust independent component analysis for blind source separation and extraction with application in electrocardiography[J].IEEE Engineering in Medicine and Biology Society,2008:3344-3347.

引证文献4

二级引证文献12

四川理工学院学报（自然科学版）
2014年 第4期

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