Non-iterative Radial Basis Function Neural Networks to Quality Control via Image Processing

This paper presents non-iterative radial basis function network hybridized with factorial design 2k that optimizes the modelling phase for the network, to train the model is used only one iteration to generate online system and avoid the overtraining caused by the multiple iterations.

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Bibliographic Details
Published inRevista IEEE América Latina Vol. 13; no. 10; pp. 3447 - 3451
Main Authors Montes Dorantes, Pascual Noradino, Mendez, Gerardo Maximiliano
Format Journal Article
LanguageEnglish
Published IEEE 01.10.2015
Subjects
Artificial neural networks
artificial vision
Computational modeling
expert systems
Factorial design
Image processing
Iterative methods
Matrix converters
Networks
Neural networks
On-line systems
Quality control
Radial basis function
Radial basis function network
Radial basis function networks
RBFN
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Summary:This paper presents non-iterative radial basis function network hybridized with factorial design 2k that optimizes the modelling phase for the network, to train the model is used only one iteration to generate online system and avoid the overtraining caused by the multiple iterations.
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ISSN:1548-0992
1548-0992
DOI:10.1109/TLA.2015.7387253