Entropy in Data Analysis II

Dear Colleagues,

Entropy is a powerful nonlinear metric widely used to assess the dynamical characteristics of data. A number of methods, such as sample entropy, fuzzy entropy, permutation entropy, distribution entropy, and dispersion entropy, have been introduced to quantify the irregularity or uncertainty of signals and images. Their multiscale extensions have been developed to quantify the complexity of data to deal with the multiple time scales inherent in such signals and images. For a better understanding of the underlying signal-generating system, multivariate multiscale entropy methods have also been proposed to take into account both the time and spatial domains at the same time.

These entropy approaches have been used in a wide range of real-world applications ranging from neuroscience and biomedical engineering to mechanical and financial studies. In particular, they have been successfully used for physiological signals, such as electrocardiograms (ECG), electroencephalograms (EEG), electromyograms (EMG), electrooculograms (EOG), gait fluctuations, and respiratory signals to help the diagnosis of different diseases such as Alzheimer’s disease, Parkinson’s disease, ALS, and ataxia.

The main goal of this Special Issue is to disseminate new and original research based on entropy analyses in order to assist in a better understanding of the physiology and data-generating mechanism, early diagnosing disorders or diseases, treatment monitoring, and planning healthcare strategies, required to prevent the occurrences of certain pathologies. Another goal is dealing with practical challenges while using these entropy-based approaches such as the effect of various noises, the quantization influences, the lengths of data, or parameters tuning. This Special Issue also seeks contributions for signal analysis based on correntropy, mutual information, divergences, and so on, which can capture higher-order statistics and the information content of signals.

Potential topics include but are not limited to the following:

• Spectral, sample, fuzzy, permutation, distribution, dispersion, and fluctuation dispersion entropies;
• Kullback–Leibler divergence (relative entropy), correntropy, and causality analysis;
• Analysis of physiological signals at multiple temporal, frequency, and spatial scales (ECG, EEG, EMG, MEG, etc.);
• Underlying mechanisms behind entropy-based results used for physiological data to improve our understanding of the disease diagnosis/pathogenesis/progression;
• Psychophysiological signals (physical/mental/emotional analysis), especially in newborns and the elderly;
• Univariate and multivariate multiscale entropy and complexity loss theory for the diagnosing diseases and monitoring treatments;
• Complexity loss theory in different diseases and disorders, especially dementia, epilepsy, and sleep disorders;
• Practical considerations: data length, embedding dimension, time delay, noise power, and signal modality characterization for health;
• Two- and three-dimensional entropy methods for image analysis;
• Mechanical and financial applications of entropy methods.

Dr. Hamed Azami
Dr. Peng Li 
Prof. Dr. Jose C. Principe
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.

• Entropy in Data Analysis in Entropy (11 articles)