Characterizing systems by multi-scale structural complexity

Ping Wang, Changgui Gu, Huijie Yang, Haiying Wang and Jack Murdoch Moore

Physica A: Statistical Mechanics and its Applications, 2023, vol. 609, issue C

Abstract: Complexity is one of the most fundamental criteria by which people distinguish different types of systems. However, the concept of complexity remains difficult to quantify objectively. In this article, we exploit recent advances in measuring the complexity of visual images to develop a multi-scale structural complexity method for characterizing system complexity based solely on a scalar time series. Moreover, we develop a method based on scatter plots and correlation to provide visual insight into system characteristics. This method can accurately reflect the dynamical characteristics of the system as a whole. In addition, it can identify the local complexity of a system at different scales as well as indicate how the complexity of the system changes with scale. Finally, we discovered that the ratio of local complexity to total complexity varied strikingly with system type (including continuous systems, discrete systems, and empirical system), which allowed us to distinguish between them. In summary, our methods provide new insights into the multi-scale structural complexity of a system based simply on a scalar time series.

Keywords: Complexity; Multi-scale structural complexity; Scatter plot; Continuous systems; Discrete systems; Empirical system (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:609:y:2023:i:c:s0378437122009165

DOI: 10.1016/j.physa.2022.128358

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