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Quantized Information in Spectral Cyberspace

The constant-Q Gabor atom is developed for spectral power, information, and uncertainty quantification from time–frequency representations. Stable multiresolution spectral entropy algorithms are constructed with continuous wavelet and Stockwell transforms. The recommended processing and scaling meth...

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Detalles Bibliográficos
Autor principal: Garcés, Milton A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10047514/
https://www.ncbi.nlm.nih.gov/pubmed/36981308
http://dx.doi.org/10.3390/e25030419
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author Garcés, Milton A.
author_facet Garcés, Milton A.
author_sort Garcés, Milton A.
collection PubMed
description The constant-Q Gabor atom is developed for spectral power, information, and uncertainty quantification from time–frequency representations. Stable multiresolution spectral entropy algorithms are constructed with continuous wavelet and Stockwell transforms. The recommended processing and scaling method will depend on the signature of interest, the desired information, and the acceptable levels of uncertainty of signal and noise features. Selected Lamb wave signatures and information spectra from the 2022 Tonga eruption are presented as representative case studies. Resilient transformations from physical to information metrics are provided for sensor-agnostic signal processing, pattern recognition, and machine learning applications.
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spelling pubmed-100475142023-03-29 Quantized Information in Spectral Cyberspace Garcés, Milton A. Entropy (Basel) Article The constant-Q Gabor atom is developed for spectral power, information, and uncertainty quantification from time–frequency representations. Stable multiresolution spectral entropy algorithms are constructed with continuous wavelet and Stockwell transforms. The recommended processing and scaling method will depend on the signature of interest, the desired information, and the acceptable levels of uncertainty of signal and noise features. Selected Lamb wave signatures and information spectra from the 2022 Tonga eruption are presented as representative case studies. Resilient transformations from physical to information metrics are provided for sensor-agnostic signal processing, pattern recognition, and machine learning applications. MDPI 2023-02-26 /pmc/articles/PMC10047514/ /pubmed/36981308 http://dx.doi.org/10.3390/e25030419 Text en © 2023 by the author. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Garcés, Milton A.
Quantized Information in Spectral Cyberspace
title Quantized Information in Spectral Cyberspace
title_full Quantized Information in Spectral Cyberspace
title_fullStr Quantized Information in Spectral Cyberspace
title_full_unstemmed Quantized Information in Spectral Cyberspace
title_short Quantized Information in Spectral Cyberspace
title_sort quantized information in spectral cyberspace
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10047514/
https://www.ncbi.nlm.nih.gov/pubmed/36981308
http://dx.doi.org/10.3390/e25030419
work_keys_str_mv AT garcesmiltona quantizedinformationinspectralcyberspace