Applied Mathematics LettersVolume 98, December 2019, Pages 164-170Minimum rank Hermitian solution to the matrix approximation problem in the spectral norm and its applicationAuthor links open overlay panelXifu LiuShow moreShareCitehttps://doi.org/10.1016/j.aml.2019.06.012Get rights and contentUnder an Elsevier user licenseopen archiveAbstractIn this paper, we discuss the following minimum rank matrix approximation problem in the spectral norm: minXr(X) subject to ‖A−BXB∗‖2<1, where A and X are Hermitian matrices. For its application, we also consider the minimum rank matrix approximation problem: minXr(X) subject to ‖ABB∗X‖2<1.Previous article in issueNext article in issueKeywordsMatrix approximationMinimum rankHermitian solutionRecommended articlesCited by (0)© 2019 Elsevier Ltd.