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Special Issue "Complex Networks from Information Measures"
Deadline for manuscript submissions: closed (31 July 2019).
Prof. Dr. Dimitris Kugiumtzis Website E-Mail
Department of Electrical and Computer Engineering, Aristotle University of Thessaloniki, Thessaloniki 54124, Greece
Interests: linear and nonlinear analysis of time series; connectivity analysis of multivariate time series; complex systems from multivariate time series; complex networks; computational statistics; dynamical systems, chaos and complexity; classification, clustering and feature selection; software development; stochastic simulation; computational neuroscience; analysis of geophysical data; analysis of financial data and econophysics; analysis of biological data; analysis of data in engineering; biosurveillance
In the study of complex systems, such as brain dynamics and financial market dynamics, a main objective is the estimation of the connectivity structure of the observed variables (or subsystems). Having selected a connectivity measure to estimate the inter-dependence among the observed variables, the complex network is then formed, where the nodes are the observed variables and the connections are the estimated inter-dependences. A main stream of methods for connectivity estimation are based on information theory, focusing on the primary property of connectivity, the information processing and transfer. Information measures have been used to estimate both symmetrical (correlation) and directed (causality) inter-dependences in the observed variables. For independent observations, information measures are attractive alternatives to classical correlation measures, whereas in time series, information measures are found to generalize the Granger causality beyond linear models.
The aim of this Special Issue is to highlight the research topic of complex networks from information measures and collect original contributions on this topic. Researchers are encouraged to present recent developments on the methodology and applications of information-based complex networks, as well as comparative studies of information and other connectivity measures.
Prof. Dr. Dimitris Kugiumtzis
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 papers will be 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 1600 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.
- information theory
- complex systems
- complex networks
- time series
- correlation networks
- information transfer
- nonlinear dynamics.