DocumentCode
2705020
Title
Local minima and back propagation
Author
Poston, Timothy ; Lee, Chung-Nim ; Choie, YoungJu ; Kwon, YongHoon
Author_Institution
Dept. of Math., Pohang Inst. of Sci. & Technol., South Korea
fYear
1991
fDate
8-14 Jul 1991
Firstpage
173
Abstract
It is shown that, in a feedforward net of logistic units, if there are as many hidden nodes as patterns to learn then almost certainly a solution exists, and the error function has no local minima. A large enough feedforward net can reproduce almost any finite set of targets for almost any set of input patterns, and will almost certainly not be trapped in a local minimum while learning to do so
Keywords
learning systems; neural nets; back-propagation; error function; feedforward net; local minima; Equations; Feedforward neural networks; Logistics; Mathematics; Neural networks; Nonhomogeneous media; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1991., IJCNN-91-Seattle International Joint Conference on
Conference_Location
Seattle, WA
Print_ISBN
0-7803-0164-1
Type
conf
DOI
10.1109/IJCNN.1991.155333
Filename
155333
Link To Document