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Research on Compressed Sensing Signal Reconstruction Algorithm Based on Smooth Graduation l 1 Norm

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Advanced Hybrid Information Processing (ADHIP 2017)

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Abstract

The compressed signal reconstruction of the sensing node has been a hot research topic for the mobile Internet. At present, some reconstruction algorithms finally adopt the minimum l 1 norm optimization algorithm. In order to solve the roughness, poor derivability and other defects of the minimum l 1 norm function, this paper constructs the smooth graduation algorithm based on l 1 norm, proves the monotonicity of the function and the sequence convergence of the optimal solution, and finally verifies the effectiveness of the function through examples. In the simulation experiment, the signal reconstruction algorithm and the classical OMP algorithm were compared, and the results show that it receives better reconstruction effects, small error and high precision.

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Authors and Affiliations

  1. Zhejiang Industry Polytechnic College, Shaoxing, Zhejiang, China

    Xuan Chen

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  1. Xuan Chen
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Correspondence to Xuan Chen .

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Editors and Affiliations

  1. Harbin University of Science and Technology, Harbin, China

    Guanglu Sun

  2. Inner Mongolia University, Hohhot, China

    Shuai Liu

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© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Chen, X. (2018). Research on Compressed Sensing Signal Reconstruction Algorithm Based on Smooth Graduation l 1 Norm. In: Sun, G., Liu, S. (eds) Advanced Hybrid Information Processing. ADHIP 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 219. Springer, Cham. https://doi.org/10.1007/978-3-319-73317-3_11

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  • DOI: https://doi.org/10.1007/978-3-319-73317-3_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-73316-6

  • Online ISBN: 978-3-319-73317-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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