4 April 1997 Neural network classification of compound mixtures
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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.
© (1997) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jeffrey L. Blackmon, Steven K. Rogers, "Neural network classification of compound mixtures", Proc. SPIE 3077, Applications and Science of Artificial Neural Networks III, (4 April 1997); doi: 10.1117/12.271538; https://doi.org/10.1117/12.271538

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