Multidimensional sensors represent an increasingly popular, yet challenging data source in modern statistics. Using tools from the emerging branch of Topological Data Analysis (TDA), we address two issues frequently encountered when analysing sensor data, namely their (often) high dimension and their sensibility to the reference system. We show how topological invariants provide a tool for detecting change--points which is robust with respect to both the time resolution we consider and the sensor placement.
Dettaglio pubblicazione
2019, Smart Statistics for Smart Applications. Book of short papers SIS2019, Pages 1119-1124
Multiresolution topological data analysis for robust activity tracking (04b Atto di convegno in volume)
Trappolini Giovanni, Padellini Tullia, Brutti Pierpaolo
ISBN: 9788891915108
Gruppo di ricerca: Theory of Deep Learning
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