DocumentCode
288426
Title
A simplified statistical analysis of feedforward neural classifier
Author
Wang, Chuan ; Principe, Jose C.
Author_Institution
Dept. of Electr. Eng., Florida Univ., Gainesville, FL, USA
Volume
2
fYear
1994
fDate
27 Jun-2 Jul 1994
Firstpage
806
Abstract
We propose an analytical procedure to determine the parameters of a neural classifier. A cost function based on the input statistics is defined. We also suggest an approximation model to describe the output distribution of each nonlinear unit with Gaussian inputs. We show that the resulting parametric classifier can perform as well as a conventional neural classifier trained with the backpropagation algorithm to minimize the mean square error
Keywords
feedforward neural nets; pattern classification; statistical analysis; Gaussian inputs; approximation model; backpropagation algorithm; cost function; feedforward neural classifier; mean square error minimization; parametric classifier; simplified statistical analysis; Backpropagation algorithms; Cost function; Density functional theory; Gaussian distribution; Neural engineering; Neural networks; Neurons; Parametric statistics; Statistical analysis; Statistical distributions;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on
Conference_Location
Orlando, FL
Print_ISBN
0-7803-1901-X
Type
conf
DOI
10.1109/ICNN.1994.374282
Filename
374282
Link To Document