DocumentCode
2624027
Title
Estimation of a posteriori probability using neural network
Author
Ono, Yoshiyuki ; Nakagawa, Seiichi
Author_Institution
Dept. of Inf. & Comput. Sci., Toyohashi Univ. of Technol., Japan
fYear
1991
fDate
18-21 Nov 1991
Firstpage
789
Abstract
A feedforward neural network has been used for pattern classification. The network, trained with input-target mapping as training patterns, can represent the a posteriori probability of input data. The authors investigated its capability using the Gaussian distributions and the uniform distributions as probability density functions for some populations
Keywords
learning systems; neural nets; pattern recognition; probability; Gaussian distributions; a posteriori probability; feedforward; input data; input-target mapping; neural network; pattern classification; probability density functions; training patterns; uniform distributions; Backpropagation algorithms; Computer networks; Feedforward neural networks; Feeds; Gaussian distribution; Neural networks; Pattern classification; Probability density function; Signal mapping; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1991. 1991 IEEE International Joint Conference on
Print_ISBN
0-7803-0227-3
Type
conf
DOI
10.1109/IJCNN.1991.170497
Filename
170497
Link To Document