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The Science and Information (SAI) Organization publishes open-access peer-reviewed journals in computer science and artificial intelligence.

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Research Article | Open Access |

A Self-adaptive Algorithm for Solving Basis Pursuit Denoising Problem

Author 1: Mengkai Zhu Author 2: Xu Zhang Author 3: Bing Xue Author 4: Hongchun Sun
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 12, No. 6 · Published 2021

DOI: https://doi.org/10.14569/IJACSA.2021.01206103

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Abstract

In this paper, we further consider a method for solving the basis pursuit denoising problem (BPDP), which has received considerable attention in signal processing and statistical inference. To this end, a new self-adaptive algorithm is proposed, its global convergence results is established. Furthermore, we also show that the method is sublinearly convergent rate of O( 1/k). Finally, the availability of given method is shown via somek numerical examples.

Keywords

Basis pursuit denoising problem algorithm global convergence sublinearly convergent rate sparse signal recovery

How to Cite this Article

Zhu, M., Zhang, X., Xue, B., & Sun, H. (2021). A Self-adaptive Algorithm for Solving Basis Pursuit Denoising Problem. International Journal of Advanced Computer Science and Applications, 12(6). https://doi.org/10.14569/IJACSA.2021.01206103

Zhu, Mengkai, et al.. "A Self-adaptive Algorithm for Solving Basis Pursuit Denoising Problem." International Journal of Advanced Computer Science and Applications, vol. 12, no. 6, 2021, https://doi.org/10.14569/IJACSA.2021.01206103.

@article{Zhu2021,
  title     = {A Self-adaptive Algorithm for Solving Basis Pursuit Denoising Problem},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {12},
  number    = {6},
  year      = {2021},
  publisher = {The Science and Information Organization},
  author    = {Mengkai Zhu and Xu Zhang and Bing Xue and Hongchun Sun},
  doi       = {10.14569/IJACSA.2021.01206103},
  url       = {https://doi.org/10.14569/IJACSA.2021.01206103}
}

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