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Methods and applications of topological data analysis

저자: Jennifer Novak Kloke; G Carlsson; Steve Kerckhoff; Rafe Mazzeo; Stanford University. Department of Mathematics.
출판사: 2010.
논문: Thesis (Ph. D.)--Stanford University, 2010.
판/형식:   주제/주장 : 문서 : 눈문/학위논문 : 전자도서   컴퓨터 파일 : 영어
데이터베이스:WorldCat
요약:
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  더 읽기…
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자료 유형: 문서, 눈문/학위논문, 인터넷 자료
문서 형식: 인터넷 자원, 컴퓨터 파일
모든 저자 / 참여자: Jennifer Novak Kloke; G Carlsson; Steve Kerckhoff; Rafe Mazzeo; Stanford University. Department of Mathematics.
OCLC 번호: 652792734
메모: Submitted to the Department of Mathematics.
설명: 1 online resource.
책임: Jennifer Novak Kloke.

초록:

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.

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