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pro vyhledávání: '"L. De Lathauwer"'
Akademický článek
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Autor:
Michiel Vandecappelle, Liesbeth Thewissen, Karel Allegaert, Anne Smits, O De Wel, L. De Lathauwer, Gunnar Naulaers, Alexander Caicedo, S. Van Huffel
Publikováno v:
EMBC
In this paper we explore the use of updated tensor decompositions for the monitoring of brain hemodynamics in neonates. For this study, we used concomitant measurements of heart rate, mean arterial blood pressure, arterial oxygen saturation, EEG, and
Publikováno v:
IFAC-PapersOnLine. 50:14150-14155
Fitting a signal to a sum-of-exponentials model is a basic problem in signal processing. It can be posed and solved as a Hankel structured low-rank matrix approximation problem. Subsequently, local optimization, subspace, and convex relaxation method
Autor:
Nico Vervliet, L. De Lathauwer
© 2019 Elsevier B.V. Combining various sources of information to discover hidden patterns is key in data analysis. These sources can often be represented as matrices and/or multiway arrays, or tensors, which can be factorized jointly, e.g., as sums
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e1165750a9ee0a8ce391df5549248516
https://lirias.kuleuven.be/handle/123456789/637655
https://lirias.kuleuven.be/handle/123456789/637655
Akademický článek
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Autor:
Nicolas Sauwen, Diana M. Sima, Uwe Himmelreich, S. Van Huffel, L. De Lathauwer, H. N. Bharath
Publikováno v:
EUSIPCO
© 2016 IEEE. In diagnosis and treatment planning of brain tumors, characterisation and localization of tissue plays an important role. Blind source separation techniques are generally employed to extract the tissue-specific profiles and its correspo
Autor:
L. De Lathauwer, S. Van Huffel, Nicolas Sauwen, Diana M. Sima, H. N. Bharath, Uwe Himmelreich
Publikováno v:
IEEE journal of biomedical and health informatics. 21(4)
Magnetic resonance spectroscopic imaging (MRSI) reveals chemical information that characterizes different tissue types in brain tumors. Blind source separation techniques are used to extract the tissue-specific profiles and their corresponding distri
Autor:
Uwe Himmelreich, Nicolas Sauwen, S. Van Huffel, Diana M. Sima, H. N. Bharath, L. De Lathauwer
Publikováno v:
EMBC
Magnetic resonance spectroscopic imaging (MRSI) has the potential to characterise different tissue types in brain tumors. Blind source separation techniques are used to extract the specific tissue profiles and their corresponding distribution from th
Publikováno v:
IEEE Transactions on Signal Processing. 60:2304-2314
We consider the problem of training a discriminative classifier given a set of labelled multivariate time series (a.k.a. multichannel signals or vector processes). We propose a novel kernel function that exploits the spectral information of tensors o
Publikováno v:
Numerical Linear Algebra with Applications. 25:e2190