Zobrazeno 1 - 10
of 95
pro vyhledávání: '"David Cuesta–Frau"'
Publikováno v:
Entropy, Vol 26, Iss 1, p 82 (2024)
Slope Entropy (SlpEn) is a novel method recently proposed in the field of time series entropy estimation. In addition to the well-known embedded dimension parameter, m, used in other methods, it applies two additional thresholds, denoted as δ and γ
Externí odkaz:
https://doaj.org/article/c6b952a2b46c4e049d313afc2433cbf9
Autor:
Mahdy Kouka, David Cuesta-Frau
Publikováno v:
Engineering Proceedings, Vol 39, Iss 1, p 67 (2023)
Slope Entropy (SlpEn) is a recently proposed time series entropy estimation method for classification. This method has yielded better results than other similar methods in all the published studies so far. It is based on a signal-gradient thresholdin
Externí odkaz:
https://doaj.org/article/2cf9e298a49649d38104ecad6e6f8404
Autor:
David Cuesta-Frau, Pau Miró-Martínez, Sandra Oltra-Crespo, Antonio Molina-Picó, Pradeepa H. Dakappa, Chakrapani Mahabala, Borja Vargas, Paula González
Publikováno v:
Mathematical Biosciences and Engineering, Vol 17, Iss 1, Pp 235-249 (2020)
Fever is a common symptom of many diseases. Fever temporal patterns can be different depending on the specific pathology. Differentiation of diseases based on multiple mathematical features and visual observations has been recently studied in the sci
Externí odkaz:
https://doaj.org/article/9cac169aad304a108649c47409679d53
Autor:
David Cuesta-Frau, Borja Vargas
Publikováno v:
Mathematical Biosciences and Engineering, Vol 17, Iss 2, Pp 1637-1658 (2020)
Despite its widely demonstrated usefulness, there is still room for improvement in the basic Permutation Entropy (PE) algorithm, as several subsequent studies have proposed in the recent years. For example, some improved PE variants try to address po
Externí odkaz:
https://doaj.org/article/809f7e33e4b14745ae2a9584e0aa5cbe
Publikováno v:
Entropy, Vol 25, Iss 1, p 66 (2022)
Slope Entropy (SlpEn) is a very recently proposed entropy calculation method. It is based on the differences between consecutive values in a time series and two new input thresholds to assign a symbol to each resulting difference interval. As the his
Externí odkaz:
https://doaj.org/article/e9eaf1b8b3464ad3adbb0a1b02d295fc
Autor:
Mahdy Kouka, David Cuesta-Frau
Publikováno v:
Entropy, Vol 24, Iss 10, p 1456 (2022)
Many time series entropy calculation methods have been proposed in the last few years. They are mainly used as numerical features for signal classification in any scientific field where data series are involved. We recently proposed a new method, Slo
Externí odkaz:
https://doaj.org/article/71a382d726eb4782a93586c42a52be00
Autor:
David Cuesta–Frau
Publikováno v:
Mathematical Biosciences and Engineering, Vol 16, Iss 6, Pp 6842-6857 (2019)
Permutation Entropy (PE) is a very popular complexity analysis tool for time series. De-spite its simplicity, it is very robust and yields goods results in applications related to assessing the randomness of a sequence, or as a quantitative feature f
Externí odkaz:
https://doaj.org/article/069a7c963cae477993e2d2aac666a19d
Autor:
Borja Vargas, David Cuesta-Frau, Paula González-López, María-José Fernández-Cotarelo, Óscar Vázquez-Gómez, Ana Colás, Manuel Varela
Publikováno v:
Entropy, Vol 24, Iss 4, p 510 (2022)
Body temperature is usually employed in clinical practice by strict binary thresholding, aiming to classify patients as having fever or not. In the last years, other approaches based on the continuous analysis of body temperature time series have eme
Externí odkaz:
https://doaj.org/article/5d633d232051464783851f0df796f3f9
Publikováno v:
Applied Sciences, Vol 11, Iss 19, p 8790 (2021)
Emerging Industry 4.0 applications require ever-increasing amounts of data and new sources of information to more accurately characterize the different processes of a production line. Industrial Internet of Things (IIoT) technologies, and in particul
Externí odkaz:
https://doaj.org/article/dcafdfd8ea6341418cbc782ebbf722f5
Publikováno v:
PLoS ONE, Vol 14, Iss 12, p e0225817 (2019)
Complexity analysis of glucose time series with Detrended Fluctuation Analysis (DFA) has been proved to be useful for the prediction of type 2 diabetes mellitus (T2DM) development. We propose a modified DFA algorithm, review some of its characteristi
Externí odkaz:
https://doaj.org/article/0ea2077f7d994c5bb4d5bf8f8f64a1b5