Publikation: The Gauß-Newton Method and its Implementation in the Optimization Library Oppy
Lade...
Dateien
Datum
2022
Autor:innen
Herausgeber:innen
ISSN der Zeitschrift
Electronic ISSN
ISBN
Bibliografische Daten
Verlag
Schriftenreihe
Auflagebezeichnung
URI (zitierfähiger Link)
Internationale Patentnummer
Link zur Lizenz
Angaben zur Forschungsförderung
Projekt
Open Access-Veröffentlichung
Open Access Green
Sammlungen
Core Facility der Universität Konstanz
Titel in einer weiteren Sprache
Publikationstyp
Masterarbeit/Diplomarbeit
Publikationsstatus
Published
Erschienen in
Zusammenfassung
This thesis provides a detailed description of the Gauß-Newton method, which is a common and effective technique for solving least-squares problems. A proof of its linear and locally quadratic convergence is presented. Additionally, the Levenberg-Marquardt method is discussed as a variant of the Gauß-Newton approach. Furthermore, a new implementation of the mentioned optimization techniques and its embedding into the Python library oppy is introduced. Two distinct application cases are performed and evaluated, which adopt the formerly presented theoretical considerations and demonstrate the effectiveness of the applied methods.
Zusammenfassung in einer weiteren Sprache
Fachgebiet (DDC)
510 Mathematik
Schlagwörter
Konferenz
Rezension
undefined / . - undefined, undefined
Zitieren
ISO 690
ALBICKER, Julia, 2022. The Gauß-Newton Method and its Implementation in the Optimization Library Oppy [Master thesis]. Konstanz: Universität KonstanzBibTex
@mastersthesis{Albicker2022GauNe-57727,
year={2022},
title={The Gauß-Newton Method and its Implementation in the Optimization Library Oppy},
address={Konstanz},
school={Universität Konstanz},
author={Albicker, Julia}
}RDF
<rdf:RDF
xmlns:dcterms="http://purl.org/dc/terms/"
xmlns:dc="http://purl.org/dc/elements/1.1/"
xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
xmlns:bibo="http://purl.org/ontology/bibo/"
xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#"
xmlns:foaf="http://xmlns.com/foaf/0.1/"
xmlns:void="http://rdfs.org/ns/void#"
xmlns:xsd="http://www.w3.org/2001/XMLSchema#" >
<rdf:Description rdf:about="https://kops.uni-konstanz.de/server/rdf/resource/123456789/57727">
<dcterms:rights rdf:resource="http://creativecommons.org/licenses/by/4.0/"/>
<bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/57727"/>
<dcterms:title>The Gauß-Newton Method and its Implementation in the Optimization Library Oppy</dcterms:title>
<dcterms:issued>2022</dcterms:issued>
<dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/39"/>
<dcterms:abstract xml:lang="eng">This thesis provides a detailed description of the Gauß-Newton method, which is a common and effective technique for solving least-squares problems. A proof of its linear and locally quadratic convergence is presented. Additionally, the Levenberg-Marquardt method is discussed as a variant of the Gauß-Newton approach. Furthermore, a new implementation of the mentioned optimization techniques and its embedding into the Python library oppy is introduced. Two distinct application cases are performed and evaluated, which adopt the formerly presented theoretical considerations and demonstrate the effectiveness of the applied methods.</dcterms:abstract>
<dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/57727/3/Albicker_2-segrisl6w08o7.pdf"/>
<dc:language>eng</dc:language>
<dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/39"/>
<void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
<dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2022-06-03T06:33:26Z</dc:date>
<dc:rights>Attribution 4.0 International</dc:rights>
<dc:creator>Albicker, Julia</dc:creator>
<dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2022-06-03T06:33:26Z</dcterms:available>
<dc:contributor>Albicker, Julia</dc:contributor>
<foaf:homepage rdf:resource="http://localhost:8080/"/>
<dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/57727/3/Albicker_2-segrisl6w08o7.pdf"/>
</rdf:Description>
</rdf:RDF>Interner Vermerk
xmlui.Submission.submit.DescribeStep.inputForms.label.kops_note_fromSubmitter
Prüfungsdatum der Dissertation
Hochschulschriftenvermerk
Konstanz, Universität Konstanz, Masterarbeit/Diplomarbeit, 2022
Finanzierungsart
Kommentar zur Publikation
Allianzlizenz
Corresponding Authors der Uni Konstanz vorhanden
Internationale Co-Autor:innen
Universitätsbibliographie
Ja
