Learning under hardware restrictions in CMOS fuzzy controllers able to extract rules from examples.

Vidal Verdú, Fernando, Navas-González, Rafael, and Rodríguez-Vázquez, Angel. "Learning under hardware restrictions in CMOS fuzzy controllers able to extract rules from examples.." Mathware and Soft Computing 3.3 (1996): 435-446. <http://eudml.org/doc/39096>.

@article{VidalVerdú1996,
abstract = {Fuzzy controllers are able to incorporate knowledge expressed in if-then rules. These rules are given by experts or skilful operators. Problems arise when there are no experts or/and rules are not easy to find. Author's proposal consists on an analog fuzzy controller which accepts structured language as well as input/output data pairs, thus rules can be extracted or tuned from human or software controller operation. Learning from data pairs has to be carried out under hardware restrictions in linearity, range and resolution. In this paper, modelling of building blocks arranged in a neuro-fuzzy architecture is made and issues related to on-chip learning are discussed. Computer simulations show that learning is possible for resolutions up to 6 bits, affordable with the cheapest VLSI technologies.},
author = {Vidal Verdú, Fernando, Navas-González, Rafael, Rodríguez-Vázquez, Angel},
journal = {Mathware and Soft Computing},
keywords = {Algoritmos de aprendizaje; Controladores difusos; Circuitos MOS; Circuitos no lineales; Circuito integrado específico; Circuito integrado gran escala; Sistemas expertos},
language = {eng},
number = {3},
pages = {435-446},
title = {Learning under hardware restrictions in CMOS fuzzy controllers able to extract rules from examples.},
url = {http://eudml.org/doc/39096},
volume = {3},
year = {1996},
}

TY - JOUR
AU - Vidal Verdú, Fernando
AU - Navas-González, Rafael
AU - Rodríguez-Vázquez, Angel
TI - Learning under hardware restrictions in CMOS fuzzy controllers able to extract rules from examples.
JO - Mathware and Soft Computing
PY - 1996
VL - 3
IS - 3
SP - 435
EP - 446
AB - Fuzzy controllers are able to incorporate knowledge expressed in if-then rules. These rules are given by experts or skilful operators. Problems arise when there are no experts or/and rules are not easy to find. Author's proposal consists on an analog fuzzy controller which accepts structured language as well as input/output data pairs, thus rules can be extracted or tuned from human or software controller operation. Learning from data pairs has to be carried out under hardware restrictions in linearity, range and resolution. In this paper, modelling of building blocks arranged in a neuro-fuzzy architecture is made and issues related to on-chip learning are discussed. Computer simulations show that learning is possible for resolutions up to 6 bits, affordable with the cheapest VLSI technologies.
LA - eng
KW - Algoritmos de aprendizaje; Controladores difusos; Circuitos MOS; Circuitos no lineales; Circuito integrado específico; Circuito integrado gran escala; Sistemas expertos
UR - http://eudml.org/doc/39096
ER -