Referenced Items are not available for this document.
An analysis is made of the sensitivity of feedforward layered networks of Adaline elements (threshold logic units) to weight errors. An approximation is derived which expresses the probability of error for an output neuron of a large network (a network with many neurons per layer) as a function of the percentage change in the weights. As would be expected, the probability of error increases with the number of layers in the network and with the percentage change in the weights. The probability of error is essentially independent of the number of weights per neuron and of the number of neurons per layer, as long as these numbers are large (on the order of 100 or more)
Published in:
Neural Networks, IEEE Transactions on
(Volume:1
,
Issue:
1
)
Date of Publication: Mar 1990
- Page(s):
- 71 - 80
- ISSN :
- 1045-9227
- INSPEC Accession Number:
- 3665553
- Digital Object Identifier :
- 10.1109/72.80206
- Date of Current Version :
- 06 August 2002
- Issue Date :
- Mar 1990
- Sponsored by :
- IEEE Computational Intelligence Society
About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies
A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2013 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.
