Double symbolic joint entropy in nonlinear dynamic complexity analysis
Source abstract
Abstract
Symbolizations, the base of symbolic dynamic analysis, are classified as global static and local dynamic approaches which are combined by joint entropy in our works for nonlinear dynamic complexity analysis. Two global static methods, symbolic transformations of Wessel N. symbolic entropy and base-scale entropy, and two local ones, namely symbolizations of permutation and differential entropy, constitute four double symbolic joint entropies that have accurate complexity detections in chaotic models, logistic and Henon map series. In nonlinear dynamical analysis of different kinds of heart rate variability, heartbeats of healthy young have higher complexity than those of the healthy elderly, and congestive heart failure (CHF) patients are lowest in heartbeats’ joint entropy values. Each individual symbolic entropy is improved by double symbolic joint entropy among which the combination of base-scale and differential symbolizations have best complexity analysis. Test results prove that double symbolic joint entropy is feasible in nonlinear dynamic complexity analysis.
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Research context
OpenAlex topics: Complex Systems and Time Series Analysis · Chaos control and synchronization · Heart Rate Variability and Autonomic Control
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications 1 , Nanjing 210003, China
School of Geography and Biological Information, Nanjing University of Posts and Telecommunications 2 , Nanjing 210023, China
Funding
National Natural Science Foundation of China · Natural Science Foundation of Jiangsu Province
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