Search

Your search keyword '"Rojo-Álvarez, Jose Luis"' showing total 42 results
Start Over Author "Rojo-Álvarez, Jose Luis"
42 results on '"Rojo-Álvarez, Jose Luis"'

7. Comparison of Infinite Impulse Response (IIR) and Finite Impulse Response (FIR) Filters in Cardiac Optical Mapping Records

Author

Rivas-Lalaleo, David, Muñoz-Romero, Sergio, Huerta, Monica, Bautista-Naranjo, Víctor, García-Quintanilla, Jorge, Moreno-Planas, Javier, Rojo-Álvarez, José Luis, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Botto-Tobar, Miguel, editor, Montes León, Sergio, editor, Camacho, Oscar, editor, Chávez, Danilo, editor, Torres-Carrión, Pablo, editor, and Zambrano Vizuete, Marcelo, editor

Published
2021
Full Text
View/download PDF

10. A Unified SVM Framework for Signal Estimation

Author

Rojo-Álvarez, José Luis, Martínez-Ramón, Manel, Muñoz-Marí, Jordi, and Camps-Valls, Gustavo

Subjects
Statistics - Machine Learning, Statistics - Applications
Abstract

This paper presents a unified framework to tackle estimation problems in Digital Signal Processing (DSP) using Support Vector Machines (SVMs). The use of SVMs in estimation problems has been traditionally limited to its mere use as a black-box model. Noting such limitations in the literature, we take advantage of several properties of Mercer's kernels and functional analysis to develop a family of SVM methods for estimation in DSP. Three types of signal model equations are analyzed. First, when a specific time-signal structure is assumed to model the underlying system that generated the data, the linear signal model (so called Primal Signal Model formulation) is first stated and analyzed. Then, non-linear versions of the signal structure can be readily developed by following two different approaches. On the one hand, the signal model equation is written in reproducing kernel Hilbert spaces (RKHS) using the well-known RKHS Signal Model formulation, and Mercer's kernels are readily used in SVM non-linear algorithms. On the other hand, in the alternative and not so common Dual Signal Model formulation, a signal expansion is made by using an auxiliary signal model equation given by a non-linear regression of each time instant in the observed time series. These building blocks can be used to generate different novel SVM-based methods for problems of signal estimation, and we deal with several of the most important ones in DSP. We illustrate the usefulness of this methodology by defining SVM algorithms for linear and non-linear system identification, spectral analysis, nonuniform interpolation, sparse deconvolution, and array processing. The performance of the developed SVM methods is compared to standard approaches in all these settings. The experimental results illustrate the generality, simplicity, and capabilities of the proposed SVM framework for DSP., Comment: 22 pages, 13 figures. Digital Signal Processing, 2014

Published
2013

12. Prediction of Healthcare Associated Infections in an Intensive Care Unit Using Machine Learning and Big Data Tools

Author

Revuelta-Zamorano, Paz, Sánchez, Alberto, Rojo-Álvarez, José Luis, Álvarez-Rodríguez, Joaquín, Ramos-López, Javier, Soguero-Ruiz, Cristina, Magjarevic, Ratko, Editor-in-chief, Ładyżyński, Piotr, Series editor, Ibrahim, Fatimah, Series editor, Lacković, Igor, Series editor, Rock, Emilio Sacristan, Series editor, Kyriacou, Efthyvoulos, editor, Christofides, Stelios, editor, and Pattichis, Constantinos S., editor

Published
2016
Full Text
View/download PDF

13. Cluster Headache Diagnosis Using Iris Color Features and Statistical Pixel Classification

Author

El-Yaagoubi, Mohammed, Mora-Jiménez, Inmaculada, Rojo-Álvarez, José Luis, Pareja-Grande, Juan Antonio, Magjarevic, Ratko, Editor-in-chief, Ładyżyński, Piotr, Series editor, Ibrahim, Fatimah, Series editor, Lacković, Igor, Series editor, Rock, Emilio Sacristan, Series editor, Kyriacou, Efthyvoulos, editor, Christofides, Stelios, editor, and Pattichis, Constantinos S., editor

Published
2016
Full Text
View/download PDF

14. A Support Vector Laplacian Distance Kernel Approach to the Inverse Problem in Intracardiac Electrophysiology

Author

Caulier-Cisterna, Raúl, Sanromán-Junquera, Margarita, Rojo-Álvarez, José Luis, García-Alberola, Arcadio, Magjarevic, Ratko, Editor-in-chief, Ładyżyński, Piotr, Series editor, Ibrahim, Fatimah, Series editor, Lacković, Igor, Series editor, Rock, Emilio Sacristan, Series editor, Kyriacou, Efthyvoulos, editor, Christofides, Stelios, editor, and Pattichis, Constantinos S., editor

Published
2016
Full Text
View/download PDF

15. Influence of Normalization on the Analysis of Electroanatomical Maps with Manifold Harmonics

Author

Sanromán-Junquera, Margarita, Mora-Jiménez, Inmaculada, García-Alberola, Arcadio, Caamaño-Fernández, Antonio, Rojo-Álvarez, José Luis, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Ortuño, Francisco, editor, and Rojas, Ignacio, editor

Published
2016
Full Text
View/download PDF

22. Numerical Analysis of the Resolution of Surface Electrocardiographic Lead Systems

Author

Requena-Carrión, Jesús, Väisänen, Juho, Rojo-Álvarez, José Luis, Hyttinen, Jari, Alonso-Atienza, Felipe, Malmivuo, Jaakko, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Rangan, C. Pandu, editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Sachse, Frank B., editor, and Seemann, Gunnar, editor

Published
2007
Full Text
View/download PDF

23. Contributions of the 12 Segments of Left Ventricular Myocardium to the Body Surface Potentials

Author

Väisänen, Juho, Requena-Carrión, Jesús, Alonso-Atienza, Felipe, Hyttinen, Jari, Rojo-Álvarez, José Luis, Malmivuo, Jaakko, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Rangan, C. Pandu, editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Sachse, Frank B., editor, and Seemann, Gunnar, editor

Published
2007
Full Text
View/download PDF

35. Machine Learning Applications in Electromagnetics and Antenna Array Processing

Author

Martínez-Ramón, Manel, Gupta, Arjun, Rojo-Álvarez, José Luis, Christodoulou, Christos, Martínez-Ramón, Manel, Gupta, Arjun, Rojo-Álvarez, José Luis, and Christodoulou, Christos

Subjects
Machine learning
Abstract

This practical resource provides an overview of machine learning (ML) approaches as applied to electromagnetics and antenna array processing. Detailed coverage of the main trends in ML, including uniform and random array processing (beamforming and detection of angle of arrival), antenna optimization, wave propagation, remote sensing, radar, and other aspects of electromagnetic design are explored. An introduction to machine learning principles and the most common machine learning architectures and algorithms used today in electromagnetics and other applications is presented, including basic neural networks, gaussian processes, support vector machines, kernel methods, deep learning, convolutional neural networks, and generative adversarial networks. Applications in electromagnetics and antenna array processing that are solved using machine learning are discussed, including antennas, remote sensing, and target classification.

Published
2021

41. Prognostic Significance of Long-Period Heart Rate Rhythms in Chronic Heart Failure

Author

Pastor-Pérez, Francisco J., primary, Manzano-Fernández, Sergio, additional, Goya-Esteban, Rebeca, additional, Pascual-Figal, Domingo A., additional, Barquero-Pérez, Oscar, additional, Rojo-Álvarez, Jose Luis, additional, Everss, Estrella, additional, Martinez Martinez-Espejo, Maria Dolores, additional, Valdés Chavarri, Mariano, additional, and García-Alberola, Arcadi, additional

Published
2012
Full Text
View/download PDF

42. Kernel Antenna Array Processing.

Author

Martínez-Ramón, Manel, Rojo-Álvarez, Jose Luis, Camps-Valls, Gustavo, and Christodoulou, Christos G.

Subjects
*ANTENNAS (Electronics), *VECTOR analysis, *MAXIMA & minima, *SIGNAL-to-noise ratio, *ANTENNA arrays
Abstract

We introduce two support vector machine (SVM)-based approaches for solving antenna problems such as beamforming, sidelobe suppression, and maximization of the signal-to-noise ratio. A basic introduction to SVM optimization is provided and a complex nonlinear SVM formulation developed to handle antenna array processing in space and time. The new optimization formulation is compared with both the minimum mean square error and the minimum variance distortionless response methods. Several examples are included to show the performance of the new approaches [ABSTRACT FROM PUBLISHER]

Published
2007
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results