DocumentCode :
2428304
Title :
Estimating the mean and variance of the target probability distribution
Author :
Nix, David A. ; Weigend, Andreas S.
Author_Institution :
Dept. of Comput. Sci., Colorado Univ., Boulder, CO, USA
Volume :
1
fYear :
1994
fDate :
27 Jun-2 Jul 1994
Firstpage :
55
Abstract :
Introduces a method that estimates the mean and the variance of the probability distribution of the target as a function of the input, given an assumed target error-distribution model. Through the activation of an auxiliary output unit, this method provides a measure of the uncertainty of the usual network output for each input pattern. The authors derive the cost function and weight-update equations for the example of a Gaussian target error distribution, and demonstrate the feasibility of the network on a synthetic problem where the true input-dependent noise level is known
Keywords :
Gaussian distribution; feedforward neural nets; probability; Gaussian target error distribution; cost function; mean; target probability distribution; variance; weight-update equations; Cognitive science; Computer errors; Computer science; Cost function; Equations; Error correction; Feedforward systems; Measurement uncertainty; Noise level; Probability distribution;
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.1994.374138
Filename :
374138
Link To Document :
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