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From Zigzags to Networks: Topological Tools for Time Series Analysis

Sarah Tymochko (Michigan State University)
Thursday, January 13, 2022 - 1:00pm to 2:00pm
Online
Sarah Tymochko

Abstract: Topological data analysis (TDA) is a fairly new field with tools to quantify the shape of data in a manner that is concise and robust using concepts from algebraic topology. Persistent homology, one of the most popular tools in TDA, has proven useful in applications to time series data, detecting shape that changes over time and quantifying features like periodicity. In this talk, I will present two applications using tools from TDA to study time series data: the first using zigzag persistence, a generalization of persistent homology, to study bifurcations in dynamical systems and the second, using the shape of weighted, directed networks to distinguish periodic and chaotic behavior in time series data.

TAG-DS is a hybrid seminar and will be available in-person at the UW Mathematics Department as well as online on Zoom. You can find the link to the Zoom meeting here. If you would like to be added to our mailing list, you can do so by visiting this page.

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