Belief entropy-of-entropy and its application in the cardiac interbeat interval time series analysis

Huizi Cui, Lingge Zhou, Yan Li and Bingyi Kang

Chaos, Solitons & Fractals, 2022, vol. 155, issue C

Abstract: How to measure the complexity of physiological signals in biological system is an open problem. Various entropy algorithms have been presented, but most of them fail to account for the complexity of time series with high accuracy. In this paper, the concept of Belief Entropy-of-Entropy (BEoE) is introduced, it expands entropy of entropy (EoE) into belief structure, and computes quadratic belief entropy to characterize the complexity of biological systems based on multiple time scales. The influence of inherent complex fluctuation, length bound, correlation of time windows, etc. is considered in the BEoE analysis. Application and discussion demonstrate that BEoE has better accurateness and applicability than many existing entropy algorithms.

Keywords: D-S evidence theory; Belief entropy; Deng entropy; Time series; Complexity (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (13)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:155:y:2022:i:c:s0960077921010900

DOI: 10.1016/j.chaos.2021.111736

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