Referenced Items are not available for this document.
This paper presents expressions for the optimal step length to use when training a vector quantizer by stochastic approximation. By treating each update as an estimation problem, it provides a unified framework covering both batch and incremental training, which were previously treated separately, and extends existing results to the semibatch case. In addition, the new results presented provide a measurable improvement over results which were previously thought to be optimal
Published in:
Communications, IEEE Transactions on
(Volume:44
,
Issue:
4
)
Date of Publication: Apr 1996
- Page(s):
- 434 - 439
- ISSN :
- 0090-6778
- INSPEC Accession Number:
- 5259097
- Digital Object Identifier :
- 10.1109/26.489089
- Product Type:
- Journals & Magazines
- Date of Current Version :
- 06 August 2002
- Issue Date :
- Apr 1996
- Sponsored by :
- IEEE Communications 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.
