Discovery of Linguistic Rules by Means of RBF Network for Fault Detection in Electronic Circuits

Jan Koszlaga,Pawel Strumillo

doi:10.1007/978-3-540-24844-6_29

Discovery of Linguistic Rules by Means of RBF Network for Fault Detection in Electronic Circuits

Jan Koszlaga, Pawel Strumillo

https://doi.org/10.1007/978-3-540-24844-6_29

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Publication Date: Jan 1, 2004

Citations: 7

Affiliation: University of Łódź, Lodz University of Technology

#Radial Basis Function Neural Network #Takagi-Sugeno Fuzzy System + Show 8 more

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Abstract

A neural network based knowledge discovery method for single fault detection in electronics circuits is presented. A functional equivalence of Radial Basis Function (RBF) neural network and Takagi-Sugeno (TS) fuzzy system is used in this process. A specially modified incremental RBF network training scheme suitable for rule discovery is used. Next, the RBF neural network is converted into the TS fuzzy system. A set of linguistic rules for detection of circuit catastrophic faults are obtained (100% detection accuracy was achieved for the tested electronic circuit).

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