VLSI design of universal approximator neuro-fuzzy systems
|Baturone Castillo, María Iluminada
Sánchez Solano, Santiago
Barriga Barros, Ángel
Jiménez Fernández, Carlos Jesús
Senhadji Navarro, Raouf
López, Diego R.
|Universidad de Sevilla. Departamento de Electrónica y Electromagnetismo
|Neuro-fuzzy systems can theoretically solve any problem since they are universal approximators. Besides, they combine the advantages of the neuro and fuzzy paradigms. This paper describes and compares the different strategies ...
Neuro-fuzzy systems can theoretically solve any problem since they are universal approximators. Besides, they combine the advantages of the neuro and fuzzy paradigms. This paper describes and compares the different strategies that can be adopted to implement the learning and inference mechanisms involved in a neuro-fuzzy system. CAD tools, most of them integrated into the fuzzy system development environment Xfuzzy 2.0, have been developed to assist the designer in the implementation of neuro-fuzzy systems in FPGAs or ASICs.
|Comisión Interministerial de Ciencia y Tecnología (CICYT). España
European Commission (EC). Fondo Europeo de Desarrollo Regional (FEDER)
|Baturone Castillo, M.I., Sánchez Solano, S., Barriga Barros, Á., Jiménez Fernández, C.J., Senhadji Navarro, R. y López, D.R. (2001). VLSI design of universal approximator neuro-fuzzy systems. En XVI Conference on Design of Circuits and Integrated Systems (DCIS2001), Oporto.