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This summer, I studied persistence theory and its applications to time-series analysis and knot theory under the supervision of Prof. Martin Frankland at the University of Regina.
We begin with a brief introduction to persistent homology, covering filtered complexes, barcodes, and persistence diagrams. We then explore two distinct applications:
Our main contribution lies in developing Python and MATLAB tools that make these methods computationally accessible—supporting visualization and quantitative analysis of topological features in both temporal and geometric datasets.
📌 Code available on GitHub: github.com/wiliiiii/Persistence_Homology
The full report is available below:
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