MDPI Entropy — Special Issue “Wavelet Entropy: Computation and Applications”

Dear Colleagues,

Wavelet Entropy (WE) is a novel tool with the ability to analyze transient features of non-stationary signals. This metric combines wavelet decomposition and entropy to estimate the degree of order/disorder of a signal with a high time-frequency resolution. Initially, Shannon entropy was proposed to quantify the energy distribution in wavelet sub-bands, the metric defined in this way being applied to a wide variety of different scenarios. Special interest has shown WE’s application to physiological signals, such as electrocardiograms, electroencephalograms, intracranial pressure recordings or evoked related potentials, in which it is able to reveal clinically useful information, e.g., in the prevention of cardiac diseases or the detection of driving fatigue. A similar attention has also initiated WE’s use in forecasting faults and dangers in modern power systems and detecting machinery vibration. Moreover, several studies have also shown the superiority of WE in analyzing the variability and complexity of climate processes compared with traditional methods. Finally, it is worth noting that WE-based analysis of electromechanical noise has recently gained an increasing interest regarding remote corrosion monitoring in industrial applications.

However, Shannon entropy can present difficulties, such as wavelet aliasing and energy leakage, in the processing of some non-stationary signals. Thus, recent studies have proposed various alternatives to compute this metric. Novel indices such as Relative WE, Wavelet Singular Entropy, Wavelet Tsallis Entropy and Wavelet Sample Entropy, amongst others, can be found in the literature. Within this context, this special issue aims to provide a forum for contributions on these new ways of computing WE and the most recent advances in its application to every scenario in which useful information can be obtained.

Prof. Dr. Raúl Alcaraz Martínez
Guest Editor

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Brief Biography

Raúl Alcaraz Martínez received the M.Sc. degree in electronic engineering from the University of Alcalá, Madrid, Spain, in 2005, and the Ph.D. degree in biomedical engineering from the Universidad Politécnica de Valencia, Valencia, Spain, in 2008. Since 2006 he has been a lecturer at the Department of Electrical, Electronic, Automatic and Communication Engineering, University of Castilla-La Mancha, Spain. He has taught several subjects related to Electronic and Biomedical Instrumentation, Analog and Digital Electronic and Biomedical Signal Processing and has been the author of several academic publications in these areas. His research interests include statistical, nonlinear and array signal processing applied to biomedical signal and the development of new medical equipments. He is author of more than 130 publications, including more than 30 peer-reviewed articules, about 100 contributions in conference proceedings and 3 book chapters. He also serves as a referee for a lot of international journals, including Computers in Biology and Medicine, IEEE Transaction on Biomedical Engineering, Artificial Intelligent in Medicine, Physiological Measurement, Medical Engineering & Physics, Biomedical Signal Processing and Control, etc. Since 2014 he is a member of the Editorial Board of the Entropy — Open Access Journal and The Open Access Journal of Science and Technology.

Contact Information

Prof. Raúl Alcaraz Martínez
Innovation in Bioengineering Research Group
Technical School of Cuenca, University of Castilla-La Mancha
Campus Universitario s/n
16071, Cuenca, Spain
Tel. +34 969 179 100
Fax. +34 969 179 119