A mean value algorithm for Toeplitz matrix completion
A mean value algorithm for Toeplitz matrix completion
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DOI：
10.1016/j.aml.2014.10.013
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发表时间：
2015-03
期刊：
影响因子：
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通讯作者：
Chuan-Long Wang;C. Li
中科院分区：
文献类型：
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作者：
Chuan-Long Wang;C. Li
本文提出了一种基于奇异值阈值（SVT）算法的Toeplitz矩阵补全均值算法。新算法生成的补全矩阵保持可行的Toeplitz结构。同时，在一些合理的条件下证明了新算法的收敛性。最后，通过数值实验和图像绘制，证明了新算法比ALM（增广拉格朗日乘法器）算法更有效。
In this paper, we propose a new mean value algorithm for the Toeplitz matrix completion based on the singular value thresholding (SVT) algorithm. The completion matrices generated by the new algorithm keep a feasible Toeplitz structure. Meanwhile, we prove the convergence of the new algorithm under some reasonal conditions. Finally, we show the new algorithm is much more effective than the ALM (augmented Lagrange multiplier) algorithm through numerical experiments and image inpainting.