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Solving polynomial least squares problems via semidefinite programming relaxations

Title
Solving polynomial least squares problems via semidefinite programming relaxations
Authors
Kim S.Kojima M.
Ewha Authors
김선영
SCOPUS Author ID
김선영scopus
Issue Date
2010
Journal Title
Journal of Global Optimization
ISSN
0925-5001JCR Link
Citation
vol. 46, no. 1, pp. 1 - 23
Indexed
SCI; SCIE; SCOPUS WOS scopus
Abstract
A polynomial optimization problem whose objective function is represented as a sum of positive and even powers of polynomials, called a polynomial least squares problem, is considered. Methods to transform a polynomial least square problem to polynomial semidefinite programs to reduce degrees of the polynomials are discussed. Computational efficiency of solving the original polynomial least squares problem and the transformed polynomial semidefinite programs is compared. Numerical results on selected polynomial least square problems show better computational performance of a transformed polynomial semidefinite program, especially when degrees of the polynomials are larger. © 2009 Springer Science+Business Media, LLC.
DOI
10.1007/s10898-009-9405-3
Appears in Collections:
자연과학대학 > 수학전공 > Journal papers
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