Topological Signal Processing over Weighted Simplicial Complexes

Weighing the topological domain over which data can be represented and analysed is a key strategy in many signal processing and machine learning applications, enabling the extraction and exploitation of meaningful data features and their (higher order) relationships. Our goal in this paper is to pre...

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Main Authors Battiloro, Claudio, Sardellitti, Stefania, Barbarossa, Sergio, Di Lorenzo, Paolo
Format Journal Article
LanguageEnglish
Published 16.02.2023
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Abstract Weighing the topological domain over which data can be represented and analysed is a key strategy in many signal processing and machine learning applications, enabling the extraction and exploitation of meaningful data features and their (higher order) relationships. Our goal in this paper is to present topological signal processing tools for weighted simplicial complexes. Specifically, relying on the weighted Hodge Laplacian theory, we propose efficient strategies to jointly learn the weights of the complex and the filters for the solenoidal, irrotational and harmonic components of the signals defined over the complex. We numerically asses the effectiveness of the proposed procedures.
AbstractList Weighing the topological domain over which data can be represented and analysed is a key strategy in many signal processing and machine learning applications, enabling the extraction and exploitation of meaningful data features and their (higher order) relationships. Our goal in this paper is to present topological signal processing tools for weighted simplicial complexes. Specifically, relying on the weighted Hodge Laplacian theory, we propose efficient strategies to jointly learn the weights of the complex and the filters for the solenoidal, irrotational and harmonic components of the signals defined over the complex. We numerically asses the effectiveness of the proposed procedures.
Author Battiloro, Claudio
Barbarossa, Sergio
Di Lorenzo, Paolo
Sardellitti, Stefania
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  fullname: Barbarossa, Sergio
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  givenname: Paolo
  surname: Di Lorenzo
  fullname: Di Lorenzo, Paolo
BackLink https://doi.org/10.48550/arXiv.2302.08561$$DView paper in arXiv
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Snippet Weighing the topological domain over which data can be represented and analysed is a key strategy in many signal processing and machine learning applications,...
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