An Information-Theoretic Approach to Analyze Irregularity of Graph Signals and Network Topological Changes Based on Bubble Entropy

Author:

Dong Keqiang12ORCID,Li Dan2ORCID

Affiliation:

1. Key Laboratory of Smart Airport Theory and System, Civil Aviation University of China, Tianjin 300300, P. R. China

2. Department of Mathematics, College of Science, Civil Aviation University of China, Tianjin 300300, P. R. China

Abstract

This work generalizes the recently introduced bubble entropy (BE) algorithm for univariate time series to graph and network analysis. In this paper, we introduce a modified method, called bubble entropy for graph signals ([Formula: see text], as an invaluable tool for detecting the irregularity of signals defined on graphs. Our algorithm is based on using the adjacency matrix to combine the signal values with the topology of the graph. Experiments on both synthetic and real data demonstrate the availability of the proposed measures in detecting the irregularity of graph signals and identifying topological changes in graphs.

Funder

Tianjin Science and Technology Plan Project

Key Laboratory of Smart Airport Theory and System

Publisher

World Scientific Pub Co Pte Ltd

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