Earticle

초록

영어

The matrix completion problem is to reconstruct an unknown matrix with low-rank or approximately low-rank constraints from its partially known samples. Most methods to solve the rank minimization problem are relaxing it to the nuclear norm regularized least squares problem. Recently, there have been some simple and fast algorithms based on hard thresholding operator. In this paper, we propose an accelerated iterative hard thresholding method for matrix completion (AIHT). Then we report numerical results for solving noiseless and noisy matrix completion problems and image reconstruction. The numerical results suggest that significant improvement can be achieved by our algorithm compared to the other reported methods, especially in terms of CPU time.

목차

Abstract
 1. Introduction
 2. Notations and Preliminaries on Matrix Completion
 3. The Accelerated Iterative Hard Thresholding Method
 4. Numerical Experiments
  4.1 Parameter v
  4.2 Numerical Results for Noiseless Matrix Completion
  4.3 Numerical Results for Noisy Matrix Completion
  4.4 Application in Low-rank Image Recovery
 5. Conclusion
 Acknoweldgements
 References

키워드

저자

• Juan Geng [ College of Mathematics and Statistics, Hebei University of Economics and Business 050064 Shijiazhuang, China ]
• Xingang Yang [ Department of Safety Engineering Engineering, China Institute of Industrial Relations 100048 Beijing, China, College of Science, China Agricultural University ]
• Xiuyu Wang [ Department of Information Technology, Shijiazhuang Information Engineering Vocational College, China ]
• Laisheng Wang [ College of Science, China Agricultural University Beijing, China ] Corresponding author.

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605