Back to the Origin: Addressing Physical Phenomena with Information-Theoretic Tools
A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Information Theory, Probability and Statistics".
Deadline for manuscript submissions: closed (20 December 2022) | Viewed by 2195
Special Issue Editors
Interests: nonlinear dynamics; time series analysis; information dynamics; digital signal processing
Interests: time series analysis; information dynamics; network physiology; cardiovascular neuroscience; brain connectivity
Special Issues, Collections and Topics in MDPI journals
Interests: nonlinear dynamics; time series analysis; information dynamics; digital signal processing
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Entropy was first formulated in the deeply physical context of thermodynamics. Thereupon, the seminal works by Boltzmann, Shannon and others disclosed the awesome link of the “physical” entropy with statistics and information, thus triggering the field of information theory and its application to a wide spectrum of “less physical” fields, from physiology and neuroscience to economy and social sciences.
The urge of tackling issues in these fields has then stimulated the elaboration of information measures like approximate entropy, sample entropy, transfer entropy, permutation entropy and higher-order multivariate measures, along with theoretical works aiming at providing a sound mathematical background to these tools. This process is far from being definitely established, thus making information theory still a thriving research field.
In an apparent contradiction, a more limited, though increasing, number of works are being devoted to addressing purely physical problems with information-theoretical methods, thus providing a complementary approach to more conventional and established analytical techniques.
This Special Issue is especially devoted to contributions addressing applications of information theory in physical systems and problems. Nevertheless, contributions concerning new methods as well as works addressing complexity and stemming from other research fields, from biomedical engineering and neuroscience to geophysics and climatology, in which both the physical aspect and the information-theoretical one are apparent, are also welcome.
Prof. Dr. Leonardo Ricci
Prof. Dr. Luca Faes
Dr. Ludovico Minati
Guest Editors
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 2600 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.
Keywords
- entropy
- relative entropy
- mutual information
- information dynamics
- multivariate information
- empirical estimators
