Conputational Intelligence and Multimedia Laboratory

第12回 筑波大学ソフトコンピューティングセミナー 開催案内


■日時: 2020年1月16日(木) 16:00~17:00(質疑含む)

■場所: 筑波大学第三エリア 3B213 (プレゼンテーションルーム)

[講演] 16:00-16:50 

講演タイトル: Fractal Dimension Estimation with Persistent Homology

講演者: Jonathan Jaquette氏 (Department of Mathematics, Brandeis University)

Persistent homology quantifies the shape of a geometric object in terms of how its topology changes as it is thickened. Over the past decade there has been a surge of interest in applications of persistent homology. We propose that the recently defined persistent homology dimensions are a practical tool for fractal dimension estimation of point samples. We implement an algorithm to estimate the persistent homology dimension, and compare its performance to classical methods (e.g. the correlation and box-counting dimensions) in examples of self-similar fractals, chaotic attractors, and an empirical dataset of earthquake hypocenters.

from Jonathan’s web site(

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