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Iterative Hard Thresholding Based on Randomized Kaczmarz Method

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Abstract

The iterative hard thresholding methods have been recently developed to deal with the sparse regularization problems arising in compressed sensing and other sparse signal processing methods. The methods are attractive due to their simplicity. In this paper, we propose acceleration schemes for iterative hard thresholding methods based on randomized Kaczmarz method. The speedup is achieved by replacing the gradient step in the iterative hard thresholding methods with a randomized Kaczmarz algorithm. Numerical experiments with the sparse signal recovery show the simplicity and effectiveness of the proposed algorithms.

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Acknowledgments

This work is supported by the ‘973’ National Basic Research Program of China (2010CB731900). The authors would like to thank the reviewers for their comments and suggestions that helped improve the quality of this paper.

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Authors and Affiliations

  1. Department of Information Science, Xi’an Jiaotong University, Xi’an, China

    Zhuosheng Zhang, Yongchao Yu & Shumin Zhao

  2. Beijing Center for Mathematics and Information Interdisciplinary Sciences, Beijing, China

    Zhuosheng Zhang

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  1. Zhuosheng Zhang
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  2. Yongchao Yu
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  3. Shumin Zhao
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Correspondence to Zhuosheng Zhang.

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Zhang, Z., Yu, Y. & Zhao, S. Iterative Hard Thresholding Based on Randomized Kaczmarz Method. Circuits Syst Signal Process 34, 2065–2075 (2015). https://doi.org/10.1007/s00034-014-9934-y

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  • DOI: https://doi.org/10.1007/s00034-014-9934-y

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