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Principal basis analysis in sparse representation

稀疏信号主元分析

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创新点

  1. 1.

    构建了一个以“基元频率”为准则的稀疏信号主元分析方法。

  2. 2.

    “基元频率”准则适合于在非正交超完备空间(超完备字典)上的主元分析, 它也是稀疏信号的一个重要特征。

  3. 3.

    “稀疏信号主元分析”方法将信号的“能量集中特性”、“稀疏表达特性”和“基元高频率特性”集中于稀疏分解框架, 从而在抑制强噪声的同时有效地保留弱信号细节。

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References

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Acknowledgements

This work was supported by National Natural Science Foundation of China (Grant No. 60872131). The idea of the principal basis analysis presented here arises through a lot of deep discussions with Professor Henri Maître at Telecom-ParisTech in France. We are also grateful to Prof. Didier Le Ruyet at CNAM in France for many fruitful discussions.

Author information

Correspondence to Hong Sun.

Additional information

The authors declare that they have no conflict of interest.

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Sun, H., Sang, C. & Liu, C. Principal basis analysis in sparse representation. Sci. China Inf. Sci. 60, 028102 (2017). https://doi.org/10.1007/s11432-015-0960-8

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Keywords

  • 稀疏表示
  • 超完备字典
  • 主元分析
  • 噪声抑制
  • 信息提取