Persistent Homology
Persistent homology is a method in topological data analysis that quantifies the multi-scale topological structure of data by tracking connected components, loops, and voids as a scale parameter varies. Introduced by Edelsbrunner, Letscher, and Zomorodian in 2002, it encodes topological features through their birth and death scales, producing persistence diagrams or barcodes that serve as compact, coordinate-free descriptors of shape. The approach is robust to noise and provides a mathematically rigorous bridge between discrete data and algebraic topology.
Allikakirje
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- Edelsbrunner, H., Letscher, D., & Zomorodian, A. (2002). Topological persistence and simplification. Discrete & Computational Geometry, 28(4), 511–533. · DOI 10.1007/s00454-002-2885-2
- Carlsson, G. (2009). Topology and data. Bulletin of the American Mathematical Society, 46(2), 255–308. · DOI 10.1090/S0273-0979-09-01249-X
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