DocumentCode
324575
Title
Estimating conditional distributions by neural networks
Author
Kulczycki, Piotr ; Schioler, Henrik
Author_Institution
Fac. of Electr. Eng., Cracow Univ. of Technol., Poland
Volume
2
fYear
1998
fDate
4-9 May 1998
Firstpage
1344
Abstract
Neural networks for estimating conditional distributions and their associated quantiles are investigated in this paper. A basic network structure is developed on the basis of kernel estimation theory, and consistency property is considered from a mild set of assumptions. A number of applications within statistics, decision theory and signal processing are suggested
Keywords
data compression; decision theory; estimation theory; feedforward neural nets; probability; time optimal control; conditional distribution estimation; consistency; data compression; decision theory; estimation theory; feedforward neural networks; signal processing; statistics; time optimal control; Data compression; Decision theory; Density functional theory; Digital signal processing; Distribution functions; Equations; Erbium; Neural networks; Optimal control; Random variables;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks Proceedings, 1998. IEEE World Congress on Computational Intelligence. The 1998 IEEE International Joint Conference on
Conference_Location
Anchorage, AK
ISSN
1098-7576
Print_ISBN
0-7803-4859-1
Type
conf
DOI
10.1109/IJCNN.1998.685970
Filename
685970
Link To Document