Statistical Versus Optimal Partitioning For Block Entropies
Abstract
Purpose: Given A Time-Series, What Is The Best Partitioning Of The State Space In Order To Obtain Reasonable Values For The Block Entropies? The Purpose Of This Paper Is To Provide A Simple Answer (An Algorithm), Although Approximative, In Connection With Symbolic Dynamics And Statistical Properties Of 1-D Maps On The Interval. Design/methodology/approach: The Logistic Map Is Examined As An Archetype Of A Complex System With Different Behaviors, Namely: Periodicity, Order-To-Chaos Period-Doubling Transition, Weak Chaos, Parametric Intermittent Chaos, Developed Chaos And Fully Developed Chaos. For The Logistic Map The Generating Partition Is Known, And Allows Comparison With Other Prescriptions In The Literature. The Partitioning Of The Phase Space With The Easy Generated Bipartition Induced By The Mean Value Of A Curve In The Plane, Gives Results In Good Agreement (Roughly Up To A 20 Per Cent Difference) With The Results Of The Generating Partition, If The Trajectory Of The System Is In Parametric Intermittent Chaos And In Developed Chaos (DC). In The Case Of Fully Developed Chaos (FDC), The Agreement Is Perfect. Findings: The Authors Confirm That A Statistical Partitioning Is Almost Equivalent With The Exact Partitioning For The Logistic Map. Originality/value: The Paper Updates Previous Results And Proposes A Better Understanding On The Partitioning For Symbolic Dynamics. © Emerald Group Publishing Limited.
Recommended Citation
I. Mistakidis et al., "Statistical Versus Optimal Partitioning For Block Entropies," Kybernetes, vol. 42, no. 1, pp. 35 - 54, Emerald, Jan 2013.
The definitive version is available at https://doi.org/10.1108/03684921311295466
Department(s)
Physics
Keywords and Phrases
Block entropies; Dynamical systems; Dynamics; Lumping; Symbolic dynamics; Time series analysis
International Standard Serial Number (ISSN)
0368-492X
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Emerald, All rights reserved.
Publication Date
01 Jan 2013