Zobrazeno 1 - 10
of 86
pro vyhledávání: '"Ana M. Aguilera"'
Publikováno v:
npj Science of Learning, Vol 8, Iss 1, Pp 1-7 (2023)
Abstract Music performance requires high levels of motor control. Professional musicians use body movements not only to accomplish and help technical efficiency, but to shape expressive interpretation. Here, we recorded motion and audio data of twent
Externí odkaz:
https://doaj.org/article/6e7ee24dbe0a4322b72e339918448d90
Publikováno v:
Mathematics, Vol 9, Iss 11, p 1237 (2021)
The aim of this paper is the imputation of missing data of COVID-19 hospitalized and intensive care curves in several Spanish regions. Taking into account that the curves of cases, deceases and recovered people are completely observed, a function-on-
Externí odkaz:
https://doaj.org/article/39f0e3c7c90e4253933ea3434393adad
Publikováno v:
Mathematics, Vol 9, Iss 11, p 1243 (2021)
Motivated by mapping adverse artifactual events caused by body movements in electroencephalographic (EEG) signals, we present a functional independent component analysis based on the spectral decomposition of the kurtosis operator of a smoothed princ
Externí odkaz:
https://doaj.org/article/282169a5b5694e9680ff1dfd40aa104c
Publikováno v:
Mathematics, Vol 9, Iss 4, p 390 (2021)
A new stochastic process was developed by considering the internal performance of macro-states in which the sojourn time in each one is phase-type distributed depending on time. The stationary distribution was calculated through matrix-algorithmic me
Externí odkaz:
https://doaj.org/article/c424b7de958842ef8af14eda3557808c
Publikováno v:
Mathematics, Vol 8, Iss 11, p 2085 (2020)
Functional Principal Component Analysis (FPCA) is an important dimension reduction technique to interpret the main modes of functional data variation in terms of a small set of uncorrelated variables. The principal components can not always be simply
Externí odkaz:
https://doaj.org/article/839f2ad9e52f4156ae220a992ca93942
Publikováno v:
The R Journal. 14:231-248
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::572a96c20c86be7cc0662eca63147b90
https://doi.org/10.32614/rj-2022-053
https://doi.org/10.32614/rj-2022-053
Autor:
null Marc Vidal, null Kelsey E. Onderdijk, null Ana M. Aguilera, null Joren Six, null Pieter‐Jan Maes, null Thomas Hans Fritz, null Marc Leman
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5a699eb8704d115e9db114fc8a18d05f
https://doi.org/10.1111/ejn.15998/v2/response1
https://doi.org/10.1111/ejn.15998/v2/response1
Autor:
Christian Acal, David Maldonado, Ana M. Aguilera, Kaichen Zhu, Mario Lanza, Juan Bautista Roldán
The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acsami.2c22617
We present a new methodology to quantify the variability of resistive switching memories. Instead of statistically analyzing few data point
We present a new methodology to quantify the variability of resistive switching memories. Instead of statistically analyzing few data point
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9dd25bd3d68bc76084788ec2c990a450
https://hdl.handle.net/10481/81638
https://hdl.handle.net/10481/81638
Autor:
Ana M. Aguilera, Christian Acal
Publikováno v:
Digibug. Repositorio Institucional de la Universidad de Granada
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instname
The methodological contribution in this paper is motivated by biomechanical studies where data characterizing human movement are waveform curves representing joint measures such as flexion angles, velocity, acceleration, and so on. In many cases the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8b9839da5ef5d2b5aa9cd33109942f1c
https://doi.org/10.1007/s11634-022-00500-y
https://doi.org/10.1007/s11634-022-00500-y
Autor:
Marc Vidal, Ana M. Aguilera
Publikováno v:
STAT
Stat
Stat
Whitening is a critical normalization method to enhance statistical reduction via reparametrization to unit covariance. This article introduces the notion of whitening for random functions assumed to reside in a real separable Hilbert space. We compa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e65342adcfc897a6c8c4ca10392389e6
https://biblio.ugent.be/publication/8770510/file/01GSWNAPD4GHQMDNF2VBVVT780
https://biblio.ugent.be/publication/8770510/file/01GSWNAPD4GHQMDNF2VBVVT780