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El pasado 2 de marzo nos dejó nuestro querido amigo y compañero FERNANDO MEDEIRO, investigador del IMSE y profesor titular del área de electrónica de la Universidad de Sevilla.

Desde el inicio de su carrera, Fernando demostró tener un gran talento y capacidad como diseñador de circuitos integrados analógicos y de señal mixta, siendo pionero en diversos ámbitos del modelado y diseño de convertidores analógico-digitales de tipo sigma-delta. En este campo, Fernando destacó en multitud de facetas, publicando sus trabajos en foros de alto impacto, como IEEE Journal of Solid-State Circuits, lo que le llevó a ser reconocido como uno de los mayores expertos a nivel mundial. Entre sus muchos logros académicos, cabe resaltar su libro Top-Down Design of High-Performance Sigma-Delta Modulators, publicado en 1999 por Kluwer, ampliamente citado por autores del ámbito académico e industrial y que sigue siendo una obra de referencia imprescindible tanto para estudiantes que se inician en este campo como para diseñadores experimentados que quieren profundizar en aspectos más avanzados.

Además de su perfil académico, Fernando mostró siempre un gran interés por la transferencia de sus resultados a la industria. En esto también fue pionero en nuestro centro, recorriendo el difícil camino que lleva desde una idea a un prototipo y posteriormente a un producto comercial. La experiencia acumulada en esta faceta y su actitud emprendedora y visionaria, propició que fundara junto a otros compañeros la empresa Anafocus, que fue la primera start-up del IMSE.

En esta última etapa en la industria, Fernando no dejó nunca de lado su vínculo con nuestro instituto ni con nuestra universidad, compaginando su trabajo en la empresa con su actividad docente, su otra gran vocación y devoción, que siempre fue muy agradecida y apreciada por sus alumnos de tantas promociones y titulaciones que tuvieron la gran suerte de tenerle como profesor.

Todas estas virtudes y muchas más, unidas a su enorme calidad humana, su sentido del humor y optimismo, hizo que se ganara el cariño y el respeto de todos los que tuvimos el honor y la fortuna de compartir muchos momentos de trabajo y ocio con Fernando.

Muchas gracias Fernando. El IMSE nunca te olvidará y estará siempre en deuda contigo.

Descansa en paz, amigo. Estarás siempre en nuestra memoria y nuestro corazón.

♦ Defensa de Tesis Doctoral
Una aproximación multinivel al diseño sistemático de circuitos integrados de radiofrecuencia.
Fabio Moreira de Passos
13 Abril 2018
♦ Defensa de Tesis Doctoral
Digital Design for Neuromorphic Bio-Inspired Vision Processing.
Amirreza Yousefzadeh
4 Abril 2018
♦ Visitas al IMSE
IES Heliópolis
22 Marzo 2018
What has Deep Learning ever done for us? The Convis toolbox for modelling visual responses from retina to cortex built on PyTorch .
Jacob Huth, Institute of Vision, Paris (France)
13 Marzo 2018
Next-Generation Sigma-Delta Converters: Trends and Challenges in a Digital-Driven World.
José M. de la Rosa
Tyndall National Institute, Cork, Ireland.
27 Febrero 2018
University College Dublin, Ireland.
26 Febrero 2018

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Últimas publicaciones
Impact of TFET Reverse Currents Into Circuit Operation: A Case Study  »
Tunnel FET transistors (TFETs) are one of the most promising candidates to replace CMOS transistors for future integrated circuits. However TFET-based circuit design can exhibit significant limitations due to their reverse conduction currents caused by the direct bias of the intrinsic diode of these transistors. In this paper we analyze in depth this issue through the design of charge pump (DC-DC step up converters) circuits for energy harvesting applications. The proposed solution mitigates the impact of reverse conduction currents and, thus, improves power conversion efficiencies (PCE) compared to previous designs.

Conference - Joint Int. EUROSOI Workshop and Int. Conf. on Ultimate Integration on Silicon EUROSOI-ULIS 2018
J. Nuñez
A two-step surrogate modeling strategy for single-objective and multi-objective optimization of radiofrequency circuits  »
The knowledge-intensive radiofrequency circuit design and the scarce design automation support play against the increasingly stringent time-to-market demands. Optimization algorithms are starting to play a crucial role; however, their effectiveness is dramatically limited by the accuracy of the evaluation functions of objectives and constraints. Accurate performance evaluation of radiofrequency passive elements, e.g., inductors, is provided by electromagnetic simulators, but their computational cost makes their use within iterative optimization loops unaffordable. Surrogate modeling strategies, e.g., Kriging, support vector machines, artificial neural networks, etc., arise as a promising modeling alternative. However, their limited accuracy in this kind of applications has prevented a widespread use. In this paper, inductor performance properties are exploited to develop a two-step surrogate modeling strategy in order to evaluate the behavior of inductors with high efficiency and accuracy. An automated design flow for radiofrequency circuits using this surrogate modeling of passive components is presented. The methodology couples a circuit simulator with evolutionary computation algorithms such as particle swarm optimization, genetic algorithm or non-dominated sorting genetic algorithm (NSGA-II). This methodology ensures optimal performances within short computation times by avoiding electromagnetic simulations of inductors during the entire optimization process and using a surrogate model that has less than 1% error in inductance and quality factor when compared against electromagnetic simulations. Numerous real-life experiments of single-objective and multi-objective low-noise amplifier design demonstrate the accuracy and efficiency of the proposed strategies.

Journal Paper - Soft Computing, first online, 2018 SPRINGER
DOI: 10.1007/s00500-018-3150-9    ISSN: 1432-7643    » doi
F. Passos, R. González-Echevarría, E. Roca, R. Castro-López and F.V. Fernández
Embedding MATLAB Optimizers in SIMSIDES for the High-Level Design of ΣΔ Modulators  »
This brief shows how to combine SIMSIDES, a SIMULINK-based time-domain behavioral simulator, with different optimization engines available in MATLAB for the automated high-level design of ΣΔ modulators. To this purpose, an updated version of SIMSIDES has been developed, which includes a user-friendly interface that links the simulator with the optimizers, and guides designers through the main steps required to set the design variables, constraints and select the most suitable algorithm to maximize the performance of an arbitrary modulator topology for a given set of specifications. Several examples and results of the optimization procedure are shown to illustrate the benefits of the presented tool for the high-level synthesis of ΣΔ modulators.

Journal Paper - IEEE Transactions on Circuits and Systems II: Express Briefs, first online, 2018 IEEE
DOI: 10.1109/TCSII.2018.2820900    ISSN: 1549-7747    » doi
B. Cortés-Delgadillo, P.A. Rodríguez-Navas, L.I. Guerrero-Linares and J.M. de la Rosa
Securing Minutia Cylinder Codes for Fingerprints through Physically Unclonable Functions: An Exploratory Study  »
A number of personal devices, such as smartphones, have incorporated fingerprint recognition solutions for user authentication purposes. This work proposes a dual-factor fingerprint matching scheme based on P-MCCs (Protected Minutia Cylinder-Codes) generated from fingerprint images and PUFs (Physically Unclonable Functions) generated from device SRAMs (Static Random Access Memories). Combining the fingerprint identifier with the device identifier results in a secure template satisfying the discriminability, irreversibility, revocability, and unlinkability properties, which are strongly desired for data privacy and security. Experiments convey the benefits of the proposed dual-factor authentication mechanism in enhancing the security of personal devices that utilize biometric authentication schemes.

Conference - International Conference on Biometrics ICB 2018
R. Arjona, M.A. Prada-Delgado, I. Baturone and A. Ross
Dynamic range considerations for neural recording channels  »
Neural readout microelectronic interfaces are essential in implanted central nerve system prostheses aimed for brain-machine interfaces, the amelioration of disease effects, or the development of robotic mechanisms for the restitution/rehabilitation of abilities lost after injury or disease. Neural signals which can be recorded and used as biomarkers of the brain activity include local field potentials (LFPs) and action potentials (APs). They exhibit small amplitude (typically, below 1mV for LFPs and 100V for APs) and narrow band characteristics (0.5-200Hz for LFPs and 200Hz-7kHz for APs). A priori, these signals can be easily digitized with low-to-medium resolution ADCs, thus paving the way for neural prostheses with small area and power consumptions. However, along with the biomarkers, strong in band artifacts, which can be much larger that the signals of interest, may contaminate the recording or even preclude it altogether if the front-end saturates. Different causes can be at the origin of artifacts; for instance, they can be motion related or generated by electrical stimulations close to the recording sites. Coping with these large artifacts would demand for high dynamic range (of about 75dB) front-ends and data converters with large effective resolutions (beyond 13-14 bits). However, recent proposals for ADC resolution reduction techniques have demonstrated that modest ADCs can still be used for neural recording even in the presence of artifacts. This work reviews these proposals and also presents state-of-the-art techniques for the suppression of differential and common-mode artifacts from neural recordings.

Conference - IEEE CAS Singapore Chapter Workshop, 2018
M. Delgado-Restituto

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viernes, 20 de abril de 2018
Última actualización: 16.04.2018

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