DocumentCode
3056997
Title
DRBP: dynamically reinforced BP-based ANN-training
Author
Cheng, Xiang S. ; Backer, Eric ; Gerbrands, Jan J.
Author_Institution
Philips CFT, Eindhoven, Netherlands
fYear
1992
fDate
30 Aug-3 Sep 1992
Firstpage
9
Lastpage
12
Abstract
Describes a new training method, the DRBP-algorithm, for sigmoid-function based multilayer networks. The key step in DRBP is the dynamical selection and autonomous control of the learning rate. Various experiments have shown that the DRBP-algorithm has achieved its goal of fast speed, secure stability and easy parameter selection in practice
Keywords
learning systems; neural nets; optimisation; DRBP-algorithm; dynamically reinforced backpropagation training; learning systems; multilayer networks; neural nets; parameter selection; sigmoid-function; stability; Algorithm design and analysis; Artificial neural networks; Computer vision; Feedforward systems; Laboratories; Machine vision; Multi-layer neural network; Neural networks; Stability; Training data;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition, 1992. Vol.II. Conference B: Pattern Recognition Methodology and Systems, Proceedings., 11th IAPR International Conference on
Conference_Location
The Hague
Print_ISBN
0-8186-2915-0
Type
conf
DOI
10.1109/ICPR.1992.201710
Filename
201710
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