Jezik: | Angleški jezik |
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Leto izida: | 2018 |
Tipologija: | 1.01 - Izvirni znanstveni članek |
Organizacija: | UL FS - Fakulteta za strojništvo |
UDK: | 519.85(045) |
COBISS: | 16398875 |
ISSN: | 1052-6234 |
Št. ogledov: | 657 |
Št. prenosov: | 644 |
Ocena: | 0 (0 glasov) |
Metapodatki: |
Sekundarni jezik: | Slovenski jezik |
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Sekundarni povzetek: | In this article we present a robustness analysis of the extraction of optimizers in polynomial optimization. Optimizers can be extracted by solving moment problems using flatness and the Gelfand-Naimark-Segal (GNS) construction. Here a modification of the GNS construction is presented that applies even to nonflat data, and then its sensitivity under perturbations is studied. The focus is on eigenvalue optimization for noncommutative polynomials, but we also explain how the main results pertain to commutative and tracial optimization. |
Sekundarne ključne besede: | polinomska optimizacija;vsote kvadratov;semidefinitno programiranje;problem momentov;Hankelova matrika;ploščata razširitev;GNS konstrukcija;nekomutativni polinomi;sled; |
Vrsta dela (COBISS): | Članek v reviji |
Strani: | str. 3177-3207 |
Letnik: | ǂVol. ǂ28 |
Zvezek: | ǂno. ǂ4 |
Čas izdaje: | 2018 |
DOI: | 10.1137/17M1152061 |
ID: | 10993927 |