Referenced Items are not available for this document.
Structural learning in multi layer, feedforward neural networks was studied using M. Ishikawa's (1994) modified backpropagation algorithm with forgetting of the connection weights. The proper choice of forgetting constant was investigated previously but no generally accepted method has been established yet. The generalization rate of the trained network is analyzed as a possible means of selecting optimum model parameters. The results are illustrated using R.A. Fisher's (1936) IRIS data and anomaly detection in time series
Published in:
Artificial Neural Networks and Expert Systems, 1995. Proceedings., Second New Zealand International Two-Stream Conference on
Date of Conference: 20-23 Nov 1995
- Page(s):
- 22 - 25
- Meeting Date :
- 20 Nov 1995-23 Nov 1995
- Print ISBN:
- 0-8186-7174-2
- INSPEC Accession Number:
- 5242802
- Conference Location :
- Dunedin
- Digital Object Identifier :
- 10.1109/ANNES.1995.499430
- Product Type:
- Conference Publications
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.
