The New Special Issue "Multiscale Entropy Approaches and Their Applications: Fourth Edition" is Open for Submission!

Guest Editor: Dr. Anne Humeau-Heurtier

Submit to the Special Issue: https://www.mdpi.com/journal/entropy/special_issues/3BLEN764BP

Submission deadline: 30 November 2025

Special Issue Information:

Multiscale entropy measures have been proposed since the beginning of the 2000s to evaluate the complexity of time series, by considering the multiple time scales present in physical systems. Since then, these approaches have received significant attention and been employed in an extensive range of applications. Multivariate and multidimensional approaches have also been developed.

The algorithms used in a multiscale entropy approach comprise two main steps: (i) a coarse-graining procedure to represent the system’s dynamics on different scales and (ii) entropy computation for the original data and for the coarse-grained data, in order to evaluate the irregularity for each scale. Moreover, different entropy measures have been associated with the coarse-graining approach, each one exhibiting advantages and drawbacks: approximate entropy, sample entropy, permutation entropy, fuzzy entropy, distribution entropy, dispersion entropy, ensemble entropy, etc.

This Special Issue aims to compile papers that focus on both the theory and applications of entropy and its multiscale approaches. Any kind of entropy measure is considered (see above).

The scope of this Special Issue includes, but is not limited to, the following topics:

• Proposal of new entropy-based irregularity measures;
• Improvement of the coarse-graining concept;
• Improvement in the entropy measure itself;
• The application of entropy measures and/or its multiscale approach for univariate, multivariate, and multidimensional data.

We welcome contributions that encompass the fields of biomedical engineering, chemical engineering, hydrology, pharmaceutical sciences, financial analyses, neurosciences, industrial engineering, geosciences and information sciences.