Skip Navigation

This Article
Right arrow Full Text (Print PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Wilkins, M. F.
Right arrow Articles by Boddy, L.
Right arrow Search for Related Content
PubMed
Right arrow Articles by Wilkins, M. F.
Right arrow Articles by Boddy, L.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© Oxford University Press

A comparison of Radial Basis Function and backpropagation neural networks for identification of marine phytoplankton from multivariate flow cytometry data

Malcolm F. Wilkins , Colin Morris 1 and Lynne Boddy *

School of Pure and Applied Biology, University of Wales Cardiff CF1 3TL, UK
1Department of Computer Studies, University of Glamorgan Treforest CF37 1DL, UK

*To whom offprint requests should be sent

Two artifical neural network classifiers, the well-known Multi-layer Perceptron (MLP) (also known as the ‘backpropagation network’), and the more recently developed Radial Basis Function (RBF) network, were evaluated and compared for their ability to identify multivariate flow cytometric data from five North Sea plankton groups (Dinoflagellidae, Bacillariophyceae, Prymnesiomonadida, Cryptomonadida, and other flagellates). RBF networks generally performed similarly to MLPs , and slightly better in cases where the data were markedly multimodal; RBF networks also have much shorter training times. The performance of MLPs was improved greatly by the use of a symmetrical bipolar ‘transfer function’ as opposed to the commonly-used asymmetric form. The issues of network optimisation and computational efficiency in use are discussed.


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?


This article has been cited by other articles:


Home page
 Appl. Environ. Microbiol.Home page
M. F. Wilkins, L. Boddy, C. W. Morris, and R. R. Jonker
Identification of Phytoplankton from Flow Cytometry Data by Using Radial Basis Function Neural Networks
Appl. Envir. Microbiol., October 1, 1999; 65(10): 4404 - 4410.
[Abstract] [Full Text]


Disclaimer:
Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.