Information theory and Symbolic Analysis: Theory and Applications

Dear Colleagues,

Symbolic analysis has been developed and used successfully in very diverse fields. In recent literature, contributions of symbolic analysis to the study of complex dynamics and network structure are easily found, mainly those based on symbolic entropy measures (such as permutation entropy) and symbolic correlation integral (connected with Renyi and Tsallis entropies). Also notable are the contributions to recurrence quantification analysis, as well as their use for the analysis of massive data.

On the other hand, the scientific fields with applications of symbolic analysis and its related information-theoretic concepts have been of a very interdisciplinary nature. Thus, for example, we find applications in the field of economics, in particular in finance and risk; in the field of geography and geolocation; and in the field of health, among others.

This Special Issue seeks contributions from researchers working on symbolic analysis, complex dynamics, and information theory, from both theoretical and applied perspectives, in the form of original research or review papers. The applications of symbolic analysis and its associated entropy measures to the study of time series, spatial processes, and complex networks are especially welcome. Also welcome are preeminently appreciated applied contributions to real-world data from any scientific area.

Prof. Manuel Ruiz Marín
Prof. Mariano Matilla-García
Guest Editors

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