aller au contenu
Methods and applications of topological data analysis Aperçu de cet ouvrage
FermerAperçu de cet ouvrage
Vérifiant…

Methods and applications of topological data analysis

Auteur : Jennifer Novak Kloke; G Carlsson; Steve Kerckhoff; Rafe Mazzeo; Stanford University. Department of Mathematics.
Éditeur : 2010.
Dissertation : Thesis (Ph. D.)--Stanford University, 2010.
Édition/format :   Thèse/dissertation : Document : Thèse/mémoire : Livre électronique   Fichier informatique : Anglais
Base de données :WorldCat
Résumé :
The focus of this dissertation is the development of methods for topological analysis as well as the application of topological tools to real world problems. The first half of the dissertation focuses on an algorithm for de-noising high-dimensional data for topological data analysis. This method significantly extends the applicability of many topological data analysis methods. In particular, this method extends the  Lire la suite...
Évaluation :

(pas encore évalué) 0 avec des critiques - Soyez le premier.

 

Trouver un exemplaire en ligne

Liens vers cet ouvrage

Trouver un exemplaire dans la bibliothèque

&AllPage.SpinnerRetrieving; Recherche de bibliothèques qui possèdent cet ouvrage...

Détails

Type d’ouvrage : Document, Thèse/mémoire, Ressource Internet
Format : Ressource Internet, Fichier informatique
Tous les auteurs / collaborateurs : Jennifer Novak Kloke; G Carlsson; Steve Kerckhoff; Rafe Mazzeo; Stanford University. Department of Mathematics.
Numéro OCLC : 652792734
Notes : Submitted to the Department of Mathematics.
Description : 1 online resource.
Responsabilité : Jennifer Novak Kloke.

Résumé :

The focus of this dissertation is the development of methods for topological analysis as well as the application of topological tools to real world problems. The first half of the dissertation focuses on an algorithm for de-noising high-dimensional data for topological data analysis. This method significantly extends the applicability of many topological data analysis methods. In particular, this method extends the use of persistent homology, a generalized notion of homology for discrete data points, to data sets that were previously inaccessible because of noise. The second half of this dissertation focuses on a method for using topology to simplify complex chemical structures and to define a metric to quantify similarity for use in screening large databases of chemical compounds. This method has shown very promising initial results in locating new materials for efficiently separating carbon dioxide from the exhaust of coal-burning power plants.

Critiques

Critiques d’utilisateurs
Récupération des critiques de GoodReads...
Récuperation des critiques DOGObooks…

Tags

Soyez le premier.
Confirmez cette demande

Vous avez peut-être déjà demandé cet ouvrage. Veuillez sélectionner OK si vous voulez poursuivre avec cette demande quand même.

Données liées


<http://www.worldcat.org/oclc/652792734>
library:oclcnum"652792734"
owl:sameAs<info:oclcnum/652792734>
rdf:typeschema:Book
rdf:typej.1:Web_document
rdf:typej.1:Thesis
schema:contributor
<http://viaf.org/viaf/139860406>
rdf:typeschema:Organization
schema:name"Stanford University. Department of Mathematics."
schema:contributor
schema:contributor
schema:contributor
schema:creator
schema:datePublished"2010"
schema:description"The focus of this dissertation is the development of methods for topological analysis as well as the application of topological tools to real world problems. The first half of the dissertation focuses on an algorithm for de-noising high-dimensional data for topological data analysis. This method significantly extends the applicability of many topological data analysis methods. In particular, this method extends the use of persistent homology, a generalized notion of homology for discrete data points, to data sets that were previously inaccessible because of noise. The second half of this dissertation focuses on a method for using topology to simplify complex chemical structures and to define a metric to quantify similarity for use in screening large databases of chemical compounds. This method has shown very promising initial results in locating new materials for efficiently separating carbon dioxide from the exhaust of coal-burning power plants."@en
schema:exampleOfWork<http://worldcat.org/entity/work/id/553334413>
schema:inLanguage"en"
schema:name"Methods and applications of topological data analysis"@en
schema:url<http://purl.stanford.edu/yg805jw1021>
schema:url

Content-negotiable representations

Fermer la fenêtre

Veuillez vous identifier dans WorldCat 

Vous n’avez pas de compte? Vous pouvez facilement créer un compte gratuit.