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- Listar Ponencias (Instituto de Microelectrónica de Sevilla (IMSE-CNM)) por autor
Listar Ponencias (Instituto de Microelectrónica de Sevilla (IMSE-CNM)) por autor "Navas González, Rafael"
Mostrando ítems 1-6 de 6
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Ponencia
A 16 Rules@2.5Mflips Mixed-Signal Programmable Fuzzy Controller CMOS-1μm Chip
Vidal Verdú, Fernando; Navas González, Rafael; Rodríguez Vázquez, Ángel Benito (Institute of Electrical and Electronics Engineers, 1996)We present a fuzzy inference chip capable to evaluate 16 programmable rules at a speed of 2.5Mflips (2.5 × 10 6 fuzzy ...
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Ponencia
A mixed-signal fuzzy controller and its application to soft start of DC motors
Navas González, Rafael; Vidal Verdú, Fernando; Rodríguez Vázquez, Ángel Benito (Institute of Electrical and Electronics Engineers, 2000)Presents a mixed-signal fuzzy controller chip and its application to control of DC motors. The controller is based on a ...
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Ponencia
A modular CMOS analog fuzzy controller
Vidal Verdú, Fernando; Navas González, Rafael; Rodríguez Vázquez, Ángel Benito (Institute of Electrical and Electronics Engineers, 1997)The low/medium precision required for many fuzzy applications makes analog circuits natural candidates to design fuzzy ...
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Ponencia
A multiplexed mixed-signal fuzzy architecture
Vidal Verdú, Fernando; Navas González, Rafael; Rodríguez Vázquez, Ángel Benito (Institute of Electrical and Electronics Engineers, 1998)Analog circuits provide better area/power efficiency than their digital counterparts for low-medium precision requirements. ...
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Ponencia
CMOS design of adaptive fuzzy ASICs using mixed-signal circuits
Vidal Verdú, Fernando; Navas González, Rafael; Rodríguez Vázquez, Ángel Benito (Institute of Electrical and Electronics Engineers, 1996)Analog circuits are natural candidates to design fuzzy chips with optimum speed/power figures for precision up to about ...
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Ponencia
Mixed signal CMOS high precision circuits for on chip learning
Vidal Verdú, Fernando; Navas González, Rafael; Rodríguez Vázquez, Ángel Benito (Institute of Electrical and Electronics Engineers, 1998)Learning algorithms have become of great interest to be applied not only to neural or hybrid neuro-fuzzy systems, but also ...