Continuity of closest rank-p approximations to matrices

Hans Mittelmann, James A. Cadzow

Research output: Contribution to journalArticlepeer-review

13 Scopus citations


In signal processing, the singular value decomposition and rank characterization of matrices play prominent roles. The mapping which associates with any complex m x n matrix X its closest rank-p approximation X(p)need not be continuous. When the pth and the (p + 1)st singular values of X are equal, this mapping maps, in fact, a matrix to a set of matrices. Furthermore, an example is given to show that large errors in computing X(p)can be expected when σ  is sufficiently close to αP+ I,. It is finally shown that this mapping is closed in the sense of Zangwill. The property of closedness is an essential assumption of a global convergence proof for algorithms involving this mapping (e.g., see [l]).

Original languageEnglish (US)
Pages (from-to)1211-1212
Number of pages2
JournalIEEE Transactions on Acoustics, Speech, and Signal Processing
Issue number8
StatePublished - Aug 1987

ASJC Scopus subject areas

  • Signal Processing


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