Exploració per tema "Dimensionality reduction"
Ara es mostren els items 1-16 de 16
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A practical method to estimate the resolving power of a chemical sensor array: application to feature selection
(2018-06-12)
Article
Accés obertA methodology to calculate analytical figures of merit is not well established for detection systems that are based on sensor arrays with low sensor selectivity. In this work, we present a practical approach to estimate ... -
Adaptive surrogates of crashworthiness models for multi-purpose engineering analyses accounting for uncertainty
(2022-06-01)
Article
Accés obertUncertainty Quantification (UQ) is a booming discipline for complex computational models based on the analysis of robustness, reliability and credibility. UQ analysis for nonlinear crash models with high dimensional outputs ... -
Characterization of damage evolution on metallic components using ultrasonic non-destructive methods
(Universitat Politècnica de Catalunya, 2019-09-27)
Tesi
Accés obertWhen fatigue is considered, it is expected that structures and machinery eventually fail. Still, when this damage is unexpected, besides of the negative economic impact that it produces, life of people could be potentially ... -
Comparison of feature selection techniques for power amplifier behavioral modeling and digital predistortion linearization
(Multidisciplinary Digital Publishing Institute (MDPI), 2021-08-27)
Article
Accés obertThe power amplifier (PA) is the most critical subsystem in terms of linearity and power efficiency. Digital predistortion (DPD) is commonly used to mitigate nonlinearities while the PA operates at levels close to saturation, ... -
Dimensionality reduction for clustering with deep neural networks
(Universitat Politècnica de Catalunya / Universitat de Barcelona, 2020-09)
Treball Final de Grau
Accés obert[eng] Nowadays, high dimensional data is ubiquitous: you can think for example in images, videos or texts. Unfortunately, this property can harm seriously the performance of some algorithms. In this project, I analyse how ... -
Dimensionality reduction of non-buoyant microconfined high-pressure transcritical fluid turbulence
(2023-06-02)
Article
Accés obertThis work utilizes a novel data-driven methodology to reduce the dimensionality of non-buoyant microconfined high-pressure transcritical fluid turbulence. Classical dimensional analysis techniques are limited by the ... -
Exploratory characterization of outliers in a multi-centre 1H-MRS brain tumour dataset
(2008-09)
Article
Accés restringit per política de l'editorialAs part of the AIDTumour research project, the analysis of MRS data corresponding to various tumour pathologies is used to assist expert diagnosis. The high dimensionality of the MR spectra might obscure atypical aspects ... -
Geometrical and topological approaches to big data
(Elsevier, 2016-06-29)
Article
Accés obertModern data science uses topological methods to find the structural features of data sets before further supervised or unsupervised analysis. Geometry and topology are very natural tools for analysing massive amounts of ... -
Improving dimensionality reduction projections for data visualization
(Multidisciplinary Digital Publishing Institute, 2023-09-04)
Article
Accés obertIn data science and visualization, dimensionality reduction techniques have been extensively employed for exploring large datasets. These techniques involve the transformation of high-dimensional data into reduced versions, ... -
Intelligent data aggregation using autoencoders and other statistics
(Universitat Politècnica de Catalunya / Universitat de Barcelona, 2022-10)
Projecte Final de Màster Oficial
Accés obertOptical constellations offer a highly dimensional representation of the signals in optical transport network technologies and they can be analyzed for several use cases such as optical network health analysis and secure ... -
Manifold learning algorithms applied to structural damage classification
(2021-06-05)
Article
Accés obertA comparative study of four manifold learning algorithms was carried out to perform the dimensionality reduction process within a proposed methodology for damage classification in structural health monitoring (SHM). Isomap, ... -
Mixtures of controlled Gaussian processes for dynamical modeling of deformable objects
(Proceedings of Machine Learning Research (PMLR), 2022)
Text en actes de congrés
Accés obertControl and manipulation of objects is a highly relevant topic in Robotics research. Although significant advances have been made over the manipulation of rigid bodies, the manipulation of non-rigid objects is still ... -
Motion planning using synergies : application to anthropomorphic dual-arm robots
(Universitat Politècnica de Catalunya, 2019-10-08)
Tesi
Accés obertMotion planning is a traditional field in robotics, but new problems are nevertheless incessantly appearing, due to continuous advances in the robot developments. In order to solve these new problems, as well as to improve ... -
Multivariate Time Series dimensionality reduction: Techniques and their applications in the industry
(Universitat Politècnica de Catalunya / Universitat de Barcelona, 2022-06)
Projecte Final de Màster Oficial
Accés restringit per acord de confidencialitat -
New electronic tongue sensor array system for accurate liquor beverage classification
(2023-07-01)
Article
Accés obertThe use of sensors in different applications to improve the monitoring of a process and its variables is required as it enables information to be obtained directly from the process by ensuring its quality. This is now ... -
Radars in transport applications
(Springer, 2020-02-28)
Capítol de llibre
Accés restringit per política de l'editorialIn the recent years, automotive car industry is evolving towards a new generation of autonomous vehicles, where decision making is not fully perform by the driver but it partially relies on the technology of the car itself. ...
