2023 European Researchers' Night

We invite you to discover the most human side of research through direct contact with the experts themselves. It is the European Night of Researchers , which we celebrate this year on September 29 for the twelfth consecutive year and at the same time in almost 400 European cities.
September 25, 2023


Start of the QUBIP project

The kick-off meeting of the QUBIP project was held last September 12-13, 2023 in Torino (Italy). QUBIP is an EU-funded project (Horizon Europe programme - "Increased cybersecurity" cluster 3) that is coordinated by LINKS Foundation. In QUBIP, the IMSE participates leading the transition towards Post-Quantum Cryptography in the IoT pilot under the coordination of Dr. Piedad Brox.
September 25, 2023


Historical Edition of the Main Microelectronics Congress in Europe

The ESSCIRC/ESSDERC congress was held in Lisbon from September 11 to 14. which has been jointly organized by researchers from the UNINOVA Institute & NOVA School of Science (Lisbon), ST Microelectronics and the Instituto de Microelectrónica de Sevilla, a joint center of the Universidad de Sevilla and the Consejo Superior de Investigaciones Científicas.
September 21, 2023


The SPIRS project will participate in Security Research Event 2023

The European project SPIRS coordinated by Dr. Piedad Brox from Instituto de Microelectrónica de Sevilla has been selected by the European Commission to participate in the flagship security event called "Security Research Event 2023". The project consortium will show the achievements in a dedicated stand with live demos.
September 4, 2023


Dr Alloatti talk
Dr. Alloatti talk

Dr. Alloatti is the president of the Free Silicon Foundation devoted to promote free/libre and open-source EDA tools and hardware. He presented a talk entitled "Towards open-source silicon chips" on June 14 at Instituto de Microelectrónica de Sevilla.
June 15, 2023


SPIRS consortium
The results of the SPIRS project place Sevilla as a key in the development of security tools for ICT systems

The facilities of the Instituto de Microelectrónica de Sevilla, a joint research center of the Consejo Superior de Investigaciones Científicas CSIC) and the Universidad de Sevilla (US), host this June 1st the mid-term review of the SPIRS project (Secure Platform For ICT Systems Rooted at the Silicon Manufacturing Process).
June 1, 2023



New Director of the IMSE-CNM

IMSE researcher Teresa Serrano Gotarredona has been appointed as the new Director of the Instituto de Microelectrónica de Sevilla.


Education at IMSE

- Doctoral Studies
- Master Studies
- Degree Studies
- Final Degree Projects
- Internships


Recent publications

High-Level Design of Sigma-Delta Modulators using Artificial Neural Networks
P. Díaz-Lobo and J.M. de la Rosa
Journal Paper · IEEE International Symposium on Circuits and Systems ISCAS 2023
IEEE    ISSN: 2158-1525
abstract      doi      

This paper analyses the use of Artificial Neural Networks (ANNs) for the high-level synthesis and design of Sigma-Delta Modulators (ΣΔMs) . The presented methodology is based on training ANNs to identify optimum design patterns, so that they can learn to predict the best set of design variables for a given set of specifications. This strategy has been successfully applied in prior works to design basic analog building blocks, and it is explored in this work to automate the high-level sizing of ΣΔMs . Several ΣΔM case studies, which include both single-loop and cascade topologies as well as Switched-Capacitor (SC) and Continuous-Time (CT) circuit techniques are shown. The effect of ANN hyperparameters - such as the number of layers, neurons per layer, batch size, number of epochs, etc. - is analyzed in order to find out the best ANN architecture that finds an optimum design with less computational resources. A comparison with other optimization methods - such as genetic algorithms and gradient descent - is shown, demonstrating that the presented approach yields to more efficient design solutions in terms of performance metrics, power consumption and CPU time 1 1 This work was supported in part by Grant PID2019-103876RB-I00, funded by MCIN/AEI/10.13039/501100011033, by the European Union ESF Investing in your future, and by ’’Junta de Andalucía’’ under Grant P20-00599.

Bandpass ΔΣ Modulators with FIR Feedback
J. Gorji, S. Pavan and J.M. de la Rosa
Journal Paper · IEEE International Symposium on Circuits and Systems ISCAS 2023
IEEE    ISSN: 2158-1525
abstract      doi      

This paper investigates finite impulse response (FIR) feedback in bandpass delta-sigma modulators (BP- ΔΣMs ). FIR feedback in lowpass delta-sigma modulators (LP- ΔΣMs ) improves loop filter linearity and reduces the sensitivity of the modulator to clock jitter. We show that similar benefits can be obtained in a BP- ΔΣM if the FIR filter in the feedback path is made a bandpass one 1 1 This work was supported in part by Grant PID2019-103876RB-I00, funded by MCIN/AEI/10.13039/501100011033, by the European Union ESF Investing in your future, and by ’’Junta de Andalucía’’ under Grant P20-00599 and in part by the Center of Excellence in RF, Analog and Mixed-Signal ICs (CERAMIC), IIT Madras..


Using ANNs to predict the evolution of spectrum occupancy in cognitive-radio systems
P.I. Enwere, E. Cervantes-Requena, L.A. Camuñas-Mesa and J.M. de la Rosa
Journal Paper · Integration, vol. 93, 2023
ELSEVIER    ISSN: 0167-9260
abstract      doi      

This paper analyzes the use of Artificial Neural Networks (ANNs) to identify and predict the evolution of vacant portions or frequency holes of the radio spectrum in Cognitive Radio (CR) systems. The operating frequency of CR transceivers can be modified over the air according to the information provided by the ANN in order to establish the communication in the least occupied band. To this end, ANNs are trained with time-series datasets sensed from the electromagnetic environment. Several network architectures are considered in the study, including Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM) networks and hybrid combinations of them. These ANNs are modeled and compared in terms of their complexity, speed and accuracy of the prediction. Both simulations and experimental results are shown to validate the approach presented in this work.

A Low-Latency, Low-Power CMOS Sun Sensor for Attitude Calculation Using Photovoltaic Regime and On-Chip Centroid Computation
R. Gomez-Merchan, J. A. Leñero-Bardallo, M. López-Carmona and Á. Rodríguez-Vázquez
Journal Paper · IEEE Transactions on Instrumentation and Measurement, 2023
IEEE    ISSN: 0018-9456
abstract      doi      

The demand for sun sensors has skyrocketed in the last years due to the huge expected deployment of satellites associated with the New Space concept. Sun sensors compute the position of the sun relative to the observer and play a crucial role in navigation systems. However, the sensor itself and the associated electronics must be able to operate in harsh environments. Thus, reducing hardware and post-processing resources improves the robustness of the system. Furthermore, reducing power consumption increases the lifetime of microsatellites with a limited power budget. This work describes the design, implementation, and characterization of a proof-of-concept prototype of a low-power, high-speed sun sensor architecture. The proposed sensor uses photodiodes working in the photovoltaic regime and event-driven vision concepts to overcome the limitations of conventional digital sun sensors in terms of latency, data throughput, and power consumption. The temporal resolution of the prototype is in the microsecond range with an average power consumption lower than 100μW . Experimental results are discussed and compared with the state-of-the-art.


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What we do

Our main area of specialization is the design of CMOS analog and mixed-signal integrated circuits and their use in different application contexts such as wireless communications, data conversion, smart imagers & vision sensors, biomedical devices, cybersecurity, neuromorphic computing and space technologies.

The IMSE-CNM staff consists of approximately one hundred people, including scientists and support personnel. IMSE-CNM employees are involved in advancing scientific knowledge, designing high level scientific-technical solutions and in technology transfer.


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