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Consistent Quantification of Complex Dynamics via a Novel Statistical Complexity Measure

Keul, Frank ; Hamacher, Kay (2022):
Consistent Quantification of Complex Dynamics via a Novel Statistical Complexity Measure. (Publisher's Version)
In: Entropy, 24 (4), MDPI, e-ISSN 1099-4300,
DOI: 10.26083/tuprints-00021285,
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Item Type: Article
Origin: Secondary publication DeepGreen
Status: Publisher's Version
Title: Consistent Quantification of Complex Dynamics via a Novel Statistical Complexity Measure
Language: English
Abstract:

Natural systems often show complex dynamics. The quantification of such complex dynamics is an important step in, e.g., characterization and classification of different systems or to investigate the effect of an external perturbation on the dynamics. Promising routes were followed in the past using concepts based on (Shannon’s) entropy. Here, we propose a new, conceptually sound measure that can be pragmatically computed, in contrast to pure theoretical concepts based on, e.g., Kolmogorov complexity. We illustrate the applicability using a toy example with a control parameter and go on to the molecular evolution of the HIV1 protease for which drug treatment can be regarded as an external perturbation that changes the complexity of its molecular evolutionary dynamics. In fact, our method identifies exactly those residues which are known to bind the drug molecules by their noticeable signal. We furthermore apply our method in a completely different domain, namely foreign exchange rates, and find convincing results as well.

Journal or Publication Title: Entropy
Volume of the journal: 24
Issue Number: 4
Publisher: MDPI
Collation: 9 Seiten
Uncontrolled Keywords: complexity, co-evolution, Jensen–Shannon, entropy
Classification DDC: 000 Allgemeines, Informatik, Informationswissenschaft > 004 Informatik
500 Naturwissenschaften und Mathematik > 570 Biowissenschaften, Biologie
Divisions: 10 Department of Biology > Computational Biology and Simulation
Date Deposited: 09 May 2022 13:45
Last Modified: 09 May 2022 13:46
DOI: 10.26083/tuprints-00021285
Corresponding Links:
URN: urn:nbn:de:tuda-tuprints-212856
SWORD Depositor: Deep Green
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/21285
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