DocumentCode
2939163
Title
An analytical approach based on information theory for neural network architecture
Author
Seker, Serhat
Author_Institution
Dept. of Electr. Eng., Istanbul Tech. Univ., Turkey
Volume
1
fYear
1993
fDate
25-29 Oct. 1993
Firstpage
309
Abstract
In this study on the neural network architecture following its training period, with only one hidden layer and some constraints, the number of hidden nodes have been calculated by using the concepts of mean information quantity which was defined as an entropy, and the importance of sigmoid function has been emphasized as the necessary condition of analytical approach used.
Keywords
entropy; information theory; neural net architecture; neural nets; parallel architectures; analytical approach; constraints; entropy; hidden layer; hidden nodes; information theory; mean information quantity; necessary condition; neural network architecture; sigmoid function; training period; Entropy; Information analysis; Information theory; Neural networks; Uncertainty;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1993. IJCNN '93-Nagoya. Proceedings of 1993 International Joint Conference on
Print_ISBN
0-7803-1421-2
Type
conf
DOI
10.1109/IJCNN.1993.713919
Filename
713919
Link To Document