Wavelet q-extropies of fractal signals

The standard Tsallis and R´enyi extropies of parameter q are extended to the time-scale domain, and closed-form expressions of these extropies for fractal signals of parameter α are obtained. Wavelet extropy planes are computed for a range of the fractality parameter α and signal length N which allows an unveiling of the properties and potential applications of wavelet q-extropies on fractals. Results indicate that wavelet q-extropies allow accurate description of the complexities of fractals since they are maximum for completely random samples, decreasing for correlated fractals and increasing for uncorrelated fractals. Unlike Shannon and R´enyi, Tsallis extropies display a constant region, symmetric on α, which allows classification of fractals based on a simple heuristic of wavelet extropy values. Finally, the application of wavelet Tsallis extropies allows the differentiation of electroencephalogram (EEG) times series from volunteers with eyes closed and eyes open.

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Publication Details

Journal
Papers in Physics
Published
2025-11-07
DOI
https://doi.org/10.4279/pip.170004
Primary Topic
Statistical Mechanics and Entropy
Type
article
Field-Weighted Citation Impact
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article

Wavelet q-extropies of fractal signals

Luis Rizo-Domínguez, Julio César Ramírez Pacheco, J. Sánchez
Papers in Physics
Statistical Mechanics and Entropy
article

Wavelet q-extropies of fractal signals

Luis Rizo-Domínguez, Julio César Ramírez Pacheco, J. Sánchez
article en

Abstract

The standard Tsallis and R´enyi extropies of parameter q are extended to the time-scale domain, and closed-form expressions of these extropies for fractal signals of parameter α are obtained. Wavelet extropy planes are computed for a range of the fractality parameter α and signal length N which allows an unveiling of the properties and potential applications of wavelet q-extropies on fractals. Results indicate that wavelet q-extropies allow accurate description of the complexities of fractals since they are maximum for completely random samples, decreasing for correlated fractals and increasing for uncorrelated fractals. Unlike Shannon and R´enyi, Tsallis extropies display a constant region, symmetric on α, which allows classification of fractals based on a simple heuristic of wavelet extropy values. Finally, the application of wavelet Tsallis extropies allows the differentiation of electroencephalogram (EEG) times series from volunteers with eyes closed and eyes open.

Papers in PhysicsVol. 17
University of Quintana Roo (MX), Mathematics Research Center (MX), Centro Tecnológico de Investigación, Desarrollo e Innovación en tecnologías de la Información y las Comunicaciones (TIC) (ES)
Openalex Percentile: Top 74%
Statistical Mechanics and Entropy
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