DocumentCode
354177
Title
Parallel training algorithm of BP neural networks
Author
Jun, Li ; Yuanxiang, Li ; Jingwen, Xu ; Jinbo, Zhang
Author_Institution
Lab. of Software Eng., Wuhan Univ., China
Volume
2
fYear
2000
fDate
2000
Firstpage
872
Abstract
As the training process of backpropagation neural networks converges slowly and immerses in local vibration frequently, an algorithm named the parallel training algorithm is proposed, which is based on the master/slave model and training learning samples in each search subspace at the same time. The experiment results show that this algorithm converges at high rate and reaches global minimum quickly
Keywords
backpropagation; convergence; neural nets; parallel algorithms; search problems; backpropagation; convergence; master/slave model; neural networks; parallel learning algorithm; search subspace; Feedforward neural networks; Laboratories; Master-slave; Multi-layer neural network; Neural networks; Software algorithms; Software engineering;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control and Automation, 2000. Proceedings of the 3rd World Congress on
Conference_Location
Hefei
Print_ISBN
0-7803-5995-X
Type
conf
DOI
10.1109/WCICA.2000.863356
Filename
863356
Link To Document