Author

B. Antosh

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Preprint Jul 2026

Topological Feature Extraction of Scanty Time Series Data: A Data-Driven Approach for Dynamic State Change Detection

A methodology that combines Topological Data Analysis (TDA), specifically 0-D sublevel persistence, with Machine Learning (ML) classifiers to distinguish periodic and chaotic regimes directly from time series is proposed, providing an effective alternative for analysing sparse or incomplete time series.

B. Antosh, Sanjit Das, N. N. Thyagu · 0 citations