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10. Classification Algorithms for Fetal QRS Extraction in Abdominal ECG Signals

Author

Álvarez, Pedro, Romero, Francisco J., García, Antonio, Parrilla, Luis, Castillo, Encarnación, Morales, Diego P., 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, Rojas, Ignacio, editor, and Ortuño, Francisco, editor

Published
2017
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21. Efficient Clock Distribution Scheme for VLSI RNS-Enabled Controllers

Author

González, Daniel, Parrilla, Luis, García, Antonio, Castillo, Encarnación, Lloris, Antonio, 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, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Paliouras, Vassilis, editor, Vounckx, Johan, editor, and Verkest, Diederik, editor

Published
2005
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30. Intellectual Property Protection for RNS Circuits on FPGAs

Author

Parrilla, Luis, Castillo, Encarnación, García, Antonio, Lloris, Antonio, 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, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Becker, Jürgen, editor, Platzner, Marco, editor, and Vernalde, Serge, editor

Published
2004
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33. Digital Implementation of Radial Basis Function Neural Networks Based on Stochastic Computing

Author

Moran, Alejandro, Parrilla, Luis, Roca, Miquel, Font-Rossello, Joan, Isern, Eugeni, and Canals, Vincent

Abstract

Nowadays Internet of Things (IoT) and mobile systems use more and more Machine Learning based solutions, which implies a high computation cost with a low energy consumption. This is causing a revival of interest in unconventional hardware computing methods capable of implementing both linear and nonlinear functions with less hardware overhead than conventional fixed point and floating point alternatives. Particularly, this work proposes a novel Radial Basis Function Neural Network (RBF-NN) hardware implementation based on Stochastic Computing (SC), which applies probabilistic laws over conventional digital gates. Several complex functions design to implement RBF-NN are presented and theoretically analyzed, such as the squared Euclidean distance and the stochastic Gaussian kernel similarity function between input samples and prototypes. The efficiency and performance of the methodology is tested over well-known pattern recognition tasks, including the MNIST dataset. The results show a low-cost methodology in terms of logic resources and power, along with an inherent capability to implement complex functions in a simple way. This methodology enables the implementation of massively parallel large scale RBF-NN with relatively low hardware requirements while maintaining 96.20% accuracy, which is nearly the same for the floating point and fixed point models (96.4% and 96.25%, respectively).

Published
2023
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41. Modelado y simulación de una planta solar Fresnel de refrigeración

Author

González Parrilla, Luis, Camacho, Eduardo F., Gallego Len, Antonio Javier, and Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática

Abstract

Este Trabajo de Fin de Grado trata sobre el modelado y simulación de la planta de refrigeración solar ubicada en el techo del edificio de la Escuela Técnica Superior de Ingeniería de Sevilla. La planta está compuesta por tres elementos principales: un campo de colectores solares de Fresnel, una máquina de absorción de doble efecto y un acumulador de energía. El campo solar calienta el agua y es utilizada por la máquina de absorción para producir aire acondicionado para el edificio. Si la radiación solar disponible no es lo suficientemente alta como para alcanzar la temperatura adecuada para el enfriador de agua, el acumulador de energía se puede usar si está cargado. Cada componente se describe con detalle en el trabajo. Se desarrolla y presenta un modelo matemático de los tres componentes y las tuberías que los conectan. Los modelos desarrollados tienen como objetivo obtener un comportamiento similar en comparación con los reales, y de este modo, tener una adecuada compensación entre complejidad y precisión. Los modelos muy complejos replican más exactamente el comportamiento de los sistemas reales al costo de aumentar dramáticamente la carga computacional. Dado que uno de los objetivos del desarrollo de este modelo es su utilización como un banco de pruebas para las estrategias de control, se debe descartar un modelo muy complejo. Los modelos desarrollados en este trabajo se comparan con datos reales obtenidos de la planta real. También se proporcionan algunas simulaciones utilizando el modelo agregado de la planta de refrigeración solar. This Final Degree Project deals with the modeling and simulation of the solar cooling plant located at the roof of the Higher Technical School of Engineering of Seville building. The plant is composed by three main elements: a Fresnel Solar Collector Field, a double effect absorption machine and a storage tank. The solar field heats up pressurized water used by the absorption machine to produce air conditioning for the building. If the solar radiation available is not high enough to reach the adequate temperature for the water chiller, the storage tank can be used if charged. Every component is accurately described in the text. A mathematical model of the three components and the pipes connecting them is developed and presented. The models developed here aim at obtaining a similar behaviour compared to the real ones. Thus an adequate trade-off between complexity and precision. Very complex models replicate more exactly the behaviour of the real systems at the cost of increasing dramatically the computational burden. Since one of the goals of the developing of this model is to be used as a test-bench for control strategies, a very complex model has to be ruled out. The models developed in this work are compared to real data obtained from the real plant. Some simulations are also provided used the aggregate model of the solar cooling plant. Universidad de Sevilla. Grado en Ingeniería Electrónica, Robótica y Mecatrónica

Published
2019

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