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Special Issue "Theoretical Developments and Applications of Entropy and Ordinal Patterns"
A special issue of Entropy (ISSN 1099-4300).
Deadline for manuscript submissions: closed (15 December 2019) | Viewed by 17919
Special Issue Editors
Interests: dynamical systems; nonlinear time-series analysis; ergodic theory; mathematical physics
Special Issues, Collections and Topics in MDPI journals
Interests: nonlinear time-series analysis; time-series prediction; point processes; mathematical medicine
Special Issue Information
The concept of entropy (whether as a measure of disorder, uncertainty, randomness, or complexity) is ubiquitous in applied mathematics. This is due both to its exceptional mathematical properties, such as invariance under relevant transformations, and, especially, to its generality, which causes other similar quantifiers to be related to it. In this context, one of the scopes of this Special Issue is to develop new theoretical insights and practical applications with the concept of entropy, in any of its different materializations, as a leitmotif.
At the same, we are also interested in papers devoted to the study of ordinal patterns. Permutation entropy, an entropy of ordinal patterns originally introduced by Bandt and Pompe (2002), has led to a paradigm shift in nonlinear time-series analysis, because we do not have to estimate a generating partition for rigorously analysing a given time series by preserving the information for the underlying dynamics. Now, we can estimate metric and topological entropies much more easily. In addition, there are lots of emerging applications of ordinal patterns such as change-point detections, time-series predictions, detection of determinism, directional coupling, and surrogate data. Thus, this Special Issue aims as well at accelerating theoretical developments of ordinal patterns, and expanding their applications in science, engineering, medicine, and society. Both theoretical and/or application-oriented papers will be considered for the publication in this Special Issue of Entropy.
Prof. José María Amigó
Prof. Yoshito Hirata
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Entropy is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
- entropy and entropy-like quantities
- complexity quantified with entropy and/or ordinal patterns
- determinism and stochasticity using entropy and/or ordinal patterns
- causality/directional coupling using entropy and/or ordinal patterns
- surrogate data using entropy and/or ordinal patterns
- early warning signals/change-point detection using entropy and/or ordinal patterns
- time-series analysis/time-series prediction using entropy and/or ordinal patterns
- other emerging applications using entropy and/or ordinal patterns
- theoretical justification for analysis using entropy and/or ordinal patterns