DocumentCode :
830015
Title :
Backpropagation neural nets with one and two hidden layers
Author :
De Villiers, Jacques ; Barnard, Etienne
Author_Institution :
Dept. of Electron. & Comput. Eng., Pretoria Univ., South Africa
Volume :
4
Issue :
1
fYear :
1993
fDate :
1/1/1993 12:00:00 AM
Firstpage :
136
Lastpage :
141
Abstract :
The differences in classification and training performance of three- and four-layer (one- and two-hidden-layer) fully interconnected feedforward neural nets are investigated. To obtain results which do not merely reflect performance on a particular data set, the networks are trained on various distributions, which are themselves drawn from a distribution of distributions. Experimental results indicate that four-layered networks are more prone to fall into bad local minima, but that three- and four-layered networks perform similarly in all other respects
Keywords :
backpropagation; feedforward neural nets; backpropagation; hidden layers; interconnected feedforward neural nets; multilayer neural nets; Backpropagation; Computer architecture; Computer networks; Feedforward neural networks; Network topology; Neural networks; Neurons; Particle measurements; Testing; Virtual colonoscopy;
fLanguage :
English
Journal_Title :
Neural Networks, IEEE Transactions on
Publisher :
ieee
ISSN :
1045-9227
Type :
jour
DOI :
10.1109/72.182704
Filename :
182704
Link To Document :
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