DocumentCode
1842789
Title
Pattern grouping strategy makes BP algorithm less sensitive to learning rate
Author
Lu, Yingyang ; Xu, Shenchu ; Wu, Boxi ; Chen, Zhenxiang
Author_Institution
Dept. of Phys., Xiamen Univ., China
Volume
3
fYear
1999
fDate
1999
Firstpage
1753
Abstract
In the normal backpropagation learning process, the whole set of target patterns is learned again and again. We think that, the pattern grouping strategy (PGS), in which the patterns to be learned are divided into subgroups and are learned subgroup by subgroup, may be helpful for the BP training process. The investigation of the affect of the learning rate on the success rate of the BP learning process with PGS may serve as a proof
Keywords
backpropagation; feedforward neural nets; pattern recognition; learning rate sensitivity; pattern grouping strategy; success rate; target patterns; training process; Algorithm design and analysis; Expert systems; Humans; Jacobian matrices; Multidimensional systems; Neural networks; Physics; Sea surface; Shape; Switches;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1999. IJCNN '99. International Joint Conference on
Conference_Location
Washington, DC
ISSN
1098-7576
Print_ISBN
0-7803-5529-6
Type
conf
DOI
10.1109/IJCNN.1999.832642
Filename
832642
Link To Document