DocumentCode
1752795
Title
A Hidden Trouble Theorem for Model Classing by BP Algorithm
Author
Yang, Guowei ; Xing, Rong ; Wang, Shoujue
Author_Institution
Qingdao Univ.
Volume
1
fYear
0
fDate
0-0 0
Firstpage
2742
Lastpage
2745
Abstract
First, two lemmas for classing ability of BP neural network are given and proved. Then, a hidden trouble theorem for model classing by BP algorithm is proposed and proved, which clears misty cognition about classing ability of BP neural network and offers theoretic direction for improving the structure and algorithm of BP neural network
Keywords
backpropagation; cognition; feedforward neural nets; pattern classification; backpropagation neural network; cognition; feedforward neural network; hidden trouble theorem; model classification; Artificial neural networks; Automation; Cognition; Electronic mail; Feedforward neural networks; Intelligent control; Laboratories; Neural networks; BP algorithm; BP neural network; feedforward neural network; model classing;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
Conference_Location
Dalian
Print_ISBN
1-4244-0332-4
Type
conf
DOI
10.1109/WCICA.2006.1712863
Filename
1712863
Link To Document