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Research Units » Design of Digital and Mixed-Signal Integrated Circuits » Microelectronic Systems for Computational Intelligence

Microelectronic Systems for Computational Intelligence

Contact:

Santiago Sánchez Solano

santiagoimse-cnmcsices

Keywords: intelligent systems; soft-computing; neuro-fuzzy circuits; CAD tools; model-based design; fuzzy control; fuzzy image processing; internet of things

Description
This research line focuses on the development of new design methodologies and circuit elements for Computational Intelligence applications. Computational Intelligence includes a set of techniques inspired by natural processes that allow addressing complex problems more efficiently than through traditional approaches. Specifically, our interest is mainly focused towards efficient hardware implementation of neuro-fuzzy systems and its use in applications that take advantage of their ability to describe a system with linguistic terms, as well as to cope with the inaccurate, vague or incomplete information that appears in many real-world problems.
In recent years, the developed activities in this line have addressed the following three main objectives:
  1. The development of architectures for efficient implementation of fuzzy-inference systems on ASICs and FPGAs, as well as the proposal of a model-based design methodology that accelerates the stages of functional verification and synthesis of fuzzy modules and facilitates their integration in embedded systems.
  2. The generation of a development environment for fuzzy systems, Xfuzzy, which facilitates the tasks of design, verification and synthesis, both software and hardware, of fuzzy logic-based systems.
  3. The application of the above techniques and circuits to different problems of robotics, industrial control, food technology, communications systems, image processing, and intelligent device networks for applications related to the areas of safety and environmental control.
VLSI implementation of a 3-input 1-output fuzzy inference system using an active rule-based architecture
Components of the Xfuzzy environment, which integrates tools to facilitate the different stages involved in the design process of fuzzy logic-based systems
Research Highlights
I. Baturone, A. Barriga, S. Sánchez-Solano, C.J. Jiménez-Fernández and D.R. López, Microelectronic Design of Fuzzy Logic-Based Systems, CRC Press, 2000 » web
S. Sánchez-Solano, A. J. Cabrera, I. Baturone, F.J. Moreno-Velo and M. Brox, "FPGA Implementation of Embedded Fuzzy Controllers for Robotic Applications", IEEE Trans. on Industrial Electronics, vol. 54, no. 4, pp. 1937-1945, 2007 » doi
P. Brox, I. Baturone and S. Sánchez-Solano, "Fuzzy Logic-Based Algorithms for Video De-Interlacing", Series: Studies in Fuzziness and Soft Computing, vol. 246, Springer, 2010 » doi
S. Sánchez-Solano, E. del Toro, M. Brox, P. Brox and I. Baturone, "Model-Based Design Methodology for Rapid Development of Fuzzy Controllers on FPGAs", IEEE Trans. on Industrial Informatics, vol. 9, no. 3, pp. 1361-1370, 2013 » doi
S. Sánchez-Solano and M. Brox, "Hardware implementation of embedded fuzzy controllers on FPGAs and ASICs", in Fuzzy Modelling and Control: Theory and Applications, vol. 9, pp. 235-253, Atlantis Series on Computational Intelligence Systems, Springer-Verlag, 2014 » link
Key Research Projects & Contracts
Diseño microelectrónico de sistemas inteligentes para el procesado de información sensorial (TIC2001-1726-C02-01)
PI: Santiago Sánchez Solano
Funding Body: Gobierno de España
2001-2004
FVISION: Implementación microelectrónica de circuitos difusos para microsistemas inteligentes de visión (TEC2005-04359/MIC)
PI: Ángel Barriga Barros
Funding Body: Min. de Ciencia y Educación
Dec 2005 - Dec 2008
DIMISION: Diseño microelectrónico de sistemas de visión para redes de sensores inteligentes (TEC2008-04920)
PI: Santiago Sánchez Solano
Funding Body: Min. de Ciencia e Innovación
Jan 2009 - Jun 2012
SEIs: Diseño hardware para sistemas empotrados en entornos inteligentes (TEC2011-24319) » web
PI: Santiago Sánchez Solano
Funding Body: Min. de Ciencia e Innovación
Jan 2012 - Sep 2015
Predicción regional de potencia eólica a partir de Lógica Difusa
PI: Iluminada Baturone Castillo
Funding Body: EDP Renováveis
2014 - 2015