Referenced Items are not available for this document.
The competitive learning technique is a well-known algorithm used in neural networks, which classifies the input vectors, so that the vectors (samples) belonging to the same class have similar characteristics. Dynamic competitive learning is an unsupervised learning technique, which consists of two additional parts related to conventional competitive learning: a method of generation of new units within a cluster; and a method of generating new clusters. The model is capable for the high-level storage of complex data structures, whose classification include exception handling.
Published in:
Machine Learning and Cybernetics, 2002. Proceedings. 2002 International Conference on
(Volume:1
)
Date of Conference: 2002
- Page(s):
- 126 - 128 vol.1
- Print ISBN:
- 0-7803-7508-4
- INSPEC Accession Number:
- 7597625
- Digital Object Identifier :
- 10.1109/ICMLC.2002.1176723
- 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.
