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Advances in Computational Mathematics

, Volume 42, Issue 5, pp 1209–1224 | Cite as

A modified augmented lagrange multiplier algorithm for toeplitz matrix completion

  • Chuanlong WangEmail author
  • Chao Li
  • Jin Wang
Article

Abstract

In this paper, a modified scheme is proposed for iterative completion matrices generated by the augmented Lagrange multiplier (ALM) method based on the mean value. So that the iterative completion matrices generated by the new algorithm are of the Toeplitz structure, which decrease the computation of SVD and have better approximation to solution. Convergence is discussed. Finally, the numerical experiments and inpainted images show that the new algorithm is more effective than the accelerated proximal gradient (APG) algorithm, the singular value thresholding (SVT) algorithm and the ALM algorithm, in CPU time and accuracy.

Keywords

Toeplitz matrix Matrix completion Augmented Lagrange multiplier Mean value 

Mathematics Subject Classification (2010)

15A83 15A18 15B05 90C25 

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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.Higher Education Key Laboratory of Engineering Science Computing in Shanxi ProvinceTaiyuan Normal UniversityTaiyuanChina
  2. 2.School of Computer Science and TechnologyBeihang UniversityBeijingPeople’s Republic of China

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