dc.contributor.advisor | Plonka-Hoch, Gerlind Prof. Dr. | |
dc.contributor.author | Stampfer, Kilian | |
dc.date.accessioned | 2019-05-10T09:01:12Z | |
dc.date.available | 2019-05-10T09:01:12Z | |
dc.date.issued | 2019-05-10 | |
dc.identifier.uri | http://hdl.handle.net/11858/00-1735-0000-002E-E631-3 | |
dc.identifier.uri | http://dx.doi.org/10.53846/goediss-7406 | |
dc.language.iso | eng | de |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | |
dc.subject.ddc | 510 | de |
dc.title | The Generalized Operator Based Prony Method | de |
dc.type | doctoralThesis | de |
dc.contributor.referee | Plonka-Hoch, Gerlind Prof. Dr. | |
dc.date.examination | 2019-01-17 | |
dc.description.abstracteng | The well known Prony method was introduced to reconstruct finite linear combinations of complex exponentials.
A first approach towards generalizing this method to more arbitrary expansions was made by Peter & Plonka in 2013.
Based on their work, this thesis generalizes the classical Prony method in a purely operator-based way to
finite linear combinations of eigenfunctions of certain linear operators. The major achievements are thereby a more flexible
way of data acquisition and a full embedding of all existing examples of the classical Prony method. Furthermore, new examples including
the Stieltjes-Wigert polynomials have been given and it was also possible to derive
a general treatment of linear combinations into Sturm-Liouville type polynomials in the context of the Prony method. | de |
dc.contributor.coReferee | Kunis, Stefan Prof. Dr. | |
dc.subject.eng | generalized Prony method | de |
dc.subject.eng | exponential operators | |
dc.subject.eng | sparse expansions into eigenfunctions of linear operators | |
dc.subject.eng | parameter identification | |
dc.subject.eng | generalized sampling | |
dc.identifier.urn | urn:nbn:de:gbv:7-11858/00-1735-0000-002E-E631-3-3 | |
dc.affiliation.institute | Fakultät für Mathematik und Informatik | de |
dc.subject.gokfull | Mathematics (PPN61756535X) | de |
dc.identifier.ppn | 1666651087 | |