Analog Circuit Fault Classification and Data Reduction Using PCA-ANFIS Technique Aided by K-means Clustering Approach

Analog Circuit Fault Classification and Data Reduction Using PCA-ANFIS Technique Aided by K-means Clustering Approach

The paper work aims to extract effectively the fault feature information of analog integrated circuits and to improve the performance of a fault classification process. Thus, a fault classification method based on principal component analysis (PCA) and adaptive neuro fuzzy inference system classif...

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Bibliographic Details
Main Authors: LAIDANI, I., BOUROUBA, N.
Format: Article
Language:English
Published: Stefan cel Mare University of Suceava 2022-11-01
Series:Advances in Electrical and Computer Engineering
Subjects:
analog integrated circuits
artificial neural networks
fault diagnosis
fuzzy logic
clustering methods
Online Access:http://dx.doi.org/10.4316/AECE.2022.04009

Internet

http://dx.doi.org/10.4316/AECE.2022.04009

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