Fuzzy classification by a CMAC network

Author

Li, Bai ; Elliman, Dave

Author_Institution

Dept. of Comput., Nottingham Trent Univ., UK

fYear

1997

Firstpage

392

Lastpage

395

Abstract

Describes a novel application of the CMAC (Cerebellar Model Articulation Controller) neural network. We have identified CMAC as an adaptive fuzzy system that can extract fuzzy rules from training data and use these rules for classifying a unknown input of a class. The extracted fuzzy rules are stored in the CMAC´s memory table and they do not need to be translated explicitly to be used for classification. We have also discovered that the CMAC´s network operations are equivalent to fuzzy operations. This means that the CMAC, which has so far only been recognized as a controller and a function modeller, is in fact also a neuro-fuzzy recognition system

Keywords

adaptive systems; cerebellar model arithmetic computers; fuzzy logic; fuzzy neural nets; pattern classification; CMAC network; adaptive fuzzy system; cerebellar model articulation controller; function modeller; fuzzy classification; fuzzy operations; fuzzy rule extraction; memory table; network operations; neuro-fuzzy recognition system; training data; unknown input; Adaptive systems; Data mining; Fuzzy logic; Fuzzy neural networks; Fuzzy sets; Fuzzy systems; Neural networks; Neurons; Production systems; Training data;

fLanguage

English

Publisher

ieee

Conference_Titel

Tools with Artificial Intelligence, 1997. Proceedings., Ninth IEEE International Conference on

Conference_Location

Newport Beach, CA

ISSN

1082-3409

Print_ISBN

0-8186-8203-5

Type

conf

DOI

10.1109/TAI.1997.632280

Filename

632280