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Passive Approximation and Optimization Using B-splines
Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
Vise andre og tillknytning
Rekke forfattare: 72019 (engelsk)Inngår i: SIAM Journal on Applied Mathematics, ISSN 0036-1399, E-ISSN 1095-712X, Vol. 79, nr 1, s. 436-458Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

A passive approximation problem is formulated where the target function is an arbitrary complex-valued continuous function defined on an approximation domain consisting of a finite union of closed and bounded intervals on the real axis. The norm used is a weighted L-p-norm where 1 <= p <= infinity. The approximating functions are Herglotz functions generated by a measure with Holder continuous density in an arbitrary neighborhood of the approximation domain. Hence, the imaginary and the real parts of the approximating functions are Holder continuous functions given by the density of the measure and its Hilbert transform, respectively. In practice, it is useful to employ finite B-spline expansions to represent the generating measure. The corresponding approximation problem can then be posed as a finite-dimensional convex optimization problem which is amenable for numerical solution. A constructive proof is given here showing that the convex cone of approximating functions generated by finite uniform B-spline expansions of fixed arbitrary order (linear, quadratic, cubic, etc.) is dense in the convex cone of Herglotz functions which are locally Holder continuous in a neighborhood of the approximation domain, as mentioned above. As an illustration, typical physical application examples are included regarding the passive approximation and optimization of a linear system having metamaterial characteristics, as well as passive realization of optimal absorption of a dielectric small sphere over a finite bandwidth.

sted, utgiver, år, opplag, sider
2019. Vol. 79, nr 1, s. 436-458
Emneord [en]
approximation, Herglotz functions, B-splines, passive systems, convex optimization, sum rules
HSV kategori
Identifikatorer
URN: urn:nbn:se:su:diva-167692DOI: 10.1137/17M1161026ISI: 000460127100021OAI: oai:DiVA.org:su-167692DiVA, id: diva2:1301654
Tilgjengelig fra: 2019-04-02 Laget: 2019-04-02 Sist oppdatert: 2019-04-02bibliografisk kontrollert

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