Research Progress in Matrix Completion Algorithms

As an important development of compressed sensing theory,matrix completion and recovery has been a new and remarkable technique for signal and image processing.This paper made a survey on the latest research progress in matrix completion algorithms.Firstly,it analyzed several main algorithms to nuclear norm minimization model,and elaborated their iterative procedure and principle.Secondly,it discussed low-rank matrix factorization model of matrix completion and listed the corresponding new algorithms emerged in recent years.Then it complemented other versions derived from the above two models and pointed out the solving methods.In numerical experiments,performance comparisons were made on the main algorithms to matrix completion.Finally,it gave future research direction and focus for matrix completion algorithms.