MLPNN Training via a Multiobjective Optimization of Training Error and Stochastic Sensitivity

The training of a multilayer perceptron neural network (MLPNN) concerns the selection of its architecture and the connection weights via the minimization of both the training error and a penalty term. Different penalty terms have been proposed to control the smoothness of the MLPNN for better genera...

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Bibliographic Details
Published in:IEEE transactions on neural networks and learning systems, Vol. 27, No. 5 (2016), p. 978-92
Main Author: Yeung, Daniel S
Other Involved Persons: Li, Jin-Cheng ; Ng, Wing W Y ; Chan, Patrick P K
Format: electronic Article
Language:English
ISSN:2162-2388
Item Description:Date Completed 25.08.2016
Date Revised 22.04.2016
published: Print-Electronic
Citation Status PubMed-not-MEDLINE
Copyright: From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
Physical Description:Online-Ressource
DOI:10.1109/TNNLS.2015.2431251
Subjects:
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