On the stability of persistent entropy and new summary functions for topological data analysis
作者：
Highlights：
• Persistent entropy is a topological variable which is stable and scale in-variant.
• It can be used to reduce the dimensionality of data analysis problems to one.
• Summary functions for persistent homology based on persistent entropy are stable.
• They are more robust to noise than Betti functions and distinguish different features.
摘要
•Persistent entropy is a topological variable which is stable and scale in-variant.•It can be used to reduce the dimensionality of data analysis problems to one.•Summary functions for persistent homology based on persistent entropy are stable.•They are more robust to noise than Betti functions and distinguish different features.
论文关键词：Persistent homology,Persistent entropy,Stability,Dimensionality reduction
论文评审过程：Received 28 June 2019, Revised 14 June 2020, Accepted 17 June 2020, Available online 18 June 2020, Version of Record 24 June 2020.
论文官网地址：https://doi.org/10.1016/j.patcog.2020.107509
