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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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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.

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Authors and Affiliations

  1. School of electronic Information, ZWuhan University, Wuhan, 430072, China

    Hong Sun, Chengwei Sang & Chenguang Liu

  2. Department Signal and Image Processing, Telecom ParisTech, Paris, 75013, France

    Hong Sun & Chenguang Liu

  3. Department of Scientific Research, Air Force Early Warning Academy, Wuhan, 430019, China

    Chengwei Sang

Authors
  1. Hong Sun
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  2. Chengwei Sang
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  3. Chenguang Liu
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Corresponding author

Correspondence to Hong Sun.

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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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  • DOI: https://doi.org/10.1007/s11432-015-0960-8

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