DocumentCode
1817000
Title
Using feedforward networks to distinguish multivariate populations
Author
Stinchcombe, Maxwell ; White, Halbert
Author_Institution
California Univ., San Diego, La Jolla, CA, USA
Volume
1
fYear
1992
fDate
7-11 Jun 1992
Firstpage
788
Abstract
It is shown how feedforward neural networks can be used to construct convenient and informative tests for nonspecific differences between populations with multivariate attributes. The key to the power of these tests is of independent interest: under mild conditions, feedforward neural networks have the universal approximation property when parameterized by weights in arbitrarily small neighborhoods
Keywords
feedforward neural nets; feedforward networks; multivariate populations; neural networks; universal approximation property; Computer networks; Data analysis; Feedforward neural networks; Neural networks; Performance evaluation; Pharmaceuticals; Power generation economics; Stochastic processes; Testing; Training data;
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.1992.287091
Filename
287091
Link To Document