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

 

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Opened Access Learning under hardware restrictions in CMOS fuzzy controllers able to extract rules from examples
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Author: Vidal Verdú, Fernando
Navas González, Rafael
Rodríguez Vázquez, Ángel Benito
Department: Universidad de Sevilla. Departamento de Electrónica y Electromagnetismo
Date: 1996
Document type: Article
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.
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URI: http://hdl.handle.net/11441/32479

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