Dynamic tunneling based regularization in feedforward neural networks

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Dynamic tunneling based regularization in feedforward neural networks

This paper presents a new regularization method based on dynamic tunneling for enhancing generalization capability of multilayered neural networks. The proposed method enables escape through undesired sub-optimal solutions on the composite error surface by means of dynamic tunneling. Undesired sub-o...

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Bibliographic Details
Main Authors:	Singh, Y.P., RoyChowdhury, Pinaki
Format:	Article
Language:	English
Published:	2001
Subjects:	QA75.5-76.95 Electronic computers. Computer science
Online Access:	http://shdl.mmu.edu.my/2685/ http://shdl.mmu.edu.my/2685/1/1926.pdf

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