Svenja Lowitzsch

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Recently a new class of customized radial basis functions (RBFs) was introduced. We revisit this class of RBFs and derive a density result guaranteeing that any sufficiently smooth divergence-free function can be approximated arbitrarily closely by a linear combination of members of this class. This result has potential applications to numerically solving(More)
Approximation and Interpolation Employing Divergence–free Radial Basis Functions with Applications. (May 2002) Svenja Lowitzsch, Dipl., Georg-August University, Göttingen Co–Chairs of Advisory Committee: Dr. Francis J. Narcowich Dr. Joseph D. Ward Approximation and interpolation employing radial basis functions has found important applications since the(More)
We present the combination of a sensor based on “Phase-Measuring Deflectometry” and a new numerical algorithm to obtain the shape of specular free-form surfaces. The sensor measures the local slope of the surface which then is used to reconstruct the object’s shape. The sensor is calibrated and yields absolute slope data. We solved the inherent ambiguity of(More)
Radial basis functions (RBFs) have found important applications in areas such as signal processing, medical imaging, and neural networks since the early 1980’s. Several applications require that certain physical properties are satisfied by the interpolant, for example being divergence free in case of incompressible data. In this paper we consider a class of(More)
Zusammenfassung. In vielen Operationssituationen muss der Chirurg trotz Weichgewebeschwellung im Eingriffsgebiet eine Prädiktion des postoperativen Zustands treffen. Zur Unterstützung des Arztes kann die Schwellung anhand des Volumens zwischen den Gewebeflächen von Haut und Knochen quantifiziert werden. In diesem Beitrag wird eine Methode vorgestellt, die(More)
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