Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Martijn Bousse"'
Publikováno v:
CAMSAP
Multivariate regression is an important task in domains such as machine learning and statistics. We cast this regression problem as a linear system with a solution that is a vectorized symmetric tensor, which is assumed to be of low rank. We show tha
Publikováno v:
Series in BioEngineering ISBN: 9789811390968
The electrocardiogram (ECG) is a biomedical signal that is widely used to monitor the heart and diagnose cardiac problems. Depending on the clinical need, the ECG is recorded with one or multiple leads (or channels) from different body locations. The
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e60bbaf064e453a4ad542697aea190ff
https://doi.org/10.1007/978-981-13-9097-5_13
https://doi.org/10.1007/978-981-13-9097-5_13
Publikováno v:
IEEE Transactions on Signal Processing. 65:5770-5784
Many real-life signals can be described in terms of much fewer parameters than the actual number of samples. Such compressible signals can often be represented very compactly with low-rank matrix and tensor models. The authors have adopted this strat
Publikováno v:
EUSIPCO
In various applications within signal processing, system identification, pattern recognition, and scientific computing, the canonical polyadic decomposition (CPD) of a higher-order tensor is only known via general linear measurements. In this paper,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f29e881a482a0877242782aa0f961e60
https://lirias.kuleuven.be/handle/123456789/641081
https://lirias.kuleuven.be/handle/123456789/641081
Publikováno v:
DSW
The fourth release of Tensorlab — a Matlab toolbox which bundles state-of-the-art tensor algorithms and tools — introduces a number of algorithms which allow a variety of new types of problems to be solved. For example, Gauss–Newton type algori
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::79b098ea0edf4e586958f49552cc3283
https://lirias.kuleuven.be/handle/123456789/636972
https://lirias.kuleuven.be/handle/123456789/636972
Autor:
Martijn Bousse, Lieven De Lathauwer
Publikováno v:
GlobalSIP
© 2018 IEEE. By exploiting the intrinsic structure and/or sparsity of the system coefficients in large-scale system identification, one can enable efficient processing. In this paper, we employ this strategy for large-scale single-input multiple-out
Autor:
Martijn Bousse, Simon Geirnaert, Griet Goovaerts, Sabine Van Huffel, Sibasankar Padhy, Lieven De Lathauwer
Publikováno v:
ACSSC
© 2018 IEEE. Atrial fibrillation (AF) is the most common cardiac arrhythmia, increasing the risk of a stroke substantially. Hence, early and accurate detection of AF is paramount. We present a matrix-and tensor-based method for AF detection in singl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::640a4a600fdfb1b1ade825756c17e8a3
https://lirias.kuleuven.be/handle/123456789/634880
https://lirias.kuleuven.be/handle/123456789/634880
Publikováno v:
MLSP
© 2018 IEEE. The classification of brain states using neural recordings such as electroencephalography (EEG) finds applications in both medical and non-medical contexts, such as detecting epileptic seizures or discriminating mental states in brain-c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d27e542dfba3ab500eb18dc6e3b5d5db
https://lirias.kuleuven.be/handle/123456789/628365
https://lirias.kuleuven.be/handle/123456789/628365
Autor:
Martijn Bousse, Lieven De Lathauwer
Publikováno v:
CAMSAP
The canonical polyadic decomposition (CPD) is an important tensor tool in signal processing with various applications in blind source separation and sensor array processing. Many algorithms have been developed for the computation of a CPD using a lea
Publikováno v:
CAMSAP
Various parameters influence face recognition such as expression, pose, and illumination. In contrast to matrices, tensors can be used to naturally accommodate for the different modes of variation. The multilinear singular value decomposition (MLSVD)