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165324.pdf (1.74 MB)

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Bachelor thesis

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2020-01-19

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cc-by-nc-nd (c) Fritz Pere Nobbe Fisas, 2020
Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/165324

Homology and persistent homology

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[en] Extracting information from data sets that are high-dimensional, incomplete and noisy is generally challenging. The aim of this work is to explain a homology theory for data sets, called Persistent Homology, and the topology and algebra behind it. Moreover, we will show different ways to represent it and finally computing some examples with the help of the GUDHI software for Python.

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Treballs Finals de Grau de Matemàtiques, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2020, Director: Francisco Belchí Guillamón

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Topologia algebraica, Treballs de fi de grau, Homologia, Anàlisi multivariable, Python (Llenguatge de programació)

Subject (English)

Algebraic topology, Bachelor's theses, Homology, Multivariate analysis, Python (Computer program language)

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Treballs Finals de Grau (TFG) - Matemàtiques

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NOBBE FISAS, Fritz Pere. Homology and persistent homology. [consulted: 6 of October of 2026]. Available at: https://hdl.handle.net/2445/165324

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