scholarly journals Connections between the real positive semidefinite and distance matrix completion problems

1995 ◽  
Vol 223-224 ◽  
pp. 375-391 ◽  
Author(s):  
Charles R. Johnson ◽  
Pablo Tarazaga
Keyword(s):  
Matrix Completion ◽  
Distance Matrix ◽  
Positive Semidefinite ◽  
The Real ◽  
Completion Problems

scholarly journals Ad hoc microphone array calibration: Euclidean distance matrix completion algorithm and theoretical guarantees

2015 ◽  
Vol 107 ◽  
pp. 123-140 ◽  
Author(s):  
Mohammad J. Taghizadeh ◽  
Reza Parhizkar ◽  
Philip N. Garner ◽  
Hervé Bourlard ◽  
Afsaneh Asaei
Keyword(s):  
Euclidean Distance ◽  
Ad Hoc ◽  
Microphone Array ◽  
Matrix Completion ◽  
Distance Matrix ◽  
Euclidean Distance Matrix ◽  
Array Calibration ◽  
Euclidean Distance Matrix Completion

scholarly journals A New Algorithm for Positive Semidefinite Matrix Completion

2016 ◽  
Vol 2016 ◽  
pp. 1-5 ◽  
Author(s):  
Fangfang Xu ◽  
Peng Pan
Keyword(s):  
Matrix Completion ◽  
Positive Semidefinite ◽  
Alternating Direction Method ◽  
Low Rank ◽  
System Control ◽  
Positive Semidefinite Matrix ◽  
Linear Least Squares ◽  
Alternating Direction ◽  
Semidefinite Matrix Completion ◽  
Semidefinite Matrix

Positive semidefinite matrix completion (PSDMC) aims to recover positive semidefinite and low-rank matrices from a subset of entries of a matrix. It is widely applicable in many fields, such as statistic analysis and system control. This task can be conducted by solving the nuclear norm regularized linear least squares model with positive semidefinite constraints. We apply the widely used alternating direction method of multipliers to solve the model and get a novel algorithm. The applicability and efficiency of the new algorithm are demonstrated in numerical experiments. Recovery results show that our algorithm is helpful.

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