DocumentCode
285199
Title
A convenient method to prune multilayer neural networks via transform domain backpropagation algorithm
Author
Yang, Xiahua
Author_Institution
Dept. of Electron. Eng., Jiao Tong Univ., Shanghai, China
Volume
3
fYear
1992
fDate
7-11 Jun 1992
Firstpage
817
Abstract
It is proved that the transform domain backpropagation (BP) algorithm with a variable learning rate is an effective algorithm for accelerating the convergence of a multilayer neural network. It is shown that the transform domain BP algorithm can also be applied to prune neural networks conveniently and to accelerate the convergence to some extent. This is based on the fact the correlation within the input pattern of every layer can be removed via an orthogonal transform
Keywords
backpropagation; neural nets; correlation; multilayer neural networks; pruning; transform domain backpropagation; variable learning rate; Acceleration; Algorithm design and analysis; Backpropagation algorithms; Convergence; Discrete transforms; Frequency; Multi-layer neural network; Neural networks; Neurons;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1992. IJCNN., International Joint Conference on
Conference_Location
Baltimore, MD
Print_ISBN
0-7803-0559-0
Type
conf
DOI
10.1109/IJCNN.1992.227051
Filename
227051
Link To Document