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Structured weighted low rank approximation
18
Citations
10
References
2004
Year
Numerical AnalysisMathematical ProgrammingLow Rank ApproximationEngineeringMatrix FactorizationHankel MatricesHankel Wlra ProblemsBenchmark ProblemMultilinear Subspace LearningSemidefinite ProgrammingInverse ProblemsMatrix MethodStructural OptimizationMatrix AnalysisApproximation TheoryLow-rank Approximation
Abstract This paper extends the weighted low rank approximation (WLRA) approach towards linearly structured matrices. In the case of Hankel matrices an equivalent unconstrained optimization problem is derived and an algorithm for solving it is proposed. The correctness of the latter algorithm is verified on a benchmark problem. Finally the statistical accuracy and numerical efficiency of the proposed algorithm is compared with that of STLNB, a previously proposed algorithm for solving Hankel WLRA problems. Copyright © 2004 John Wiley & Sons, Ltd.
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