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Proceedings Paper

Neural network classification of compound mixtures
Author(s): Jeffrey L. Blackmon; Steven K. Rogers
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Paper Abstract

This paper demonstrates the usefulness of neural networks in classifying environmental samples from compound mixture data. This problem was solved by careful determination of neural network learning parameters and forward sequential selection of input features. Finally, the fundamental limit of any classifier on this data was determined using Bayes error bounding.

Paper Details

Date Published: 4 April 1997
PDF: 10 pages
Proc. SPIE 3077, Applications and Science of Artificial Neural Networks III, (4 April 1997); doi: 10.1117/12.271538
Show Author Affiliations
Jeffrey L. Blackmon, Air Force Institute of Technology (United States)
Steven K. Rogers, Battelle Memorial Institute (United States)

Published in SPIE Proceedings Vol. 3077:
Applications and Science of Artificial Neural Networks III
Steven K. Rogers, Editor(s)

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