Abstract
A new implementation of a multi-layer perceptron neural network is presented where activation levels within the network are encoded using Sigma-Delta modulation. Large, hardware networks can be constructed, which can be trained using the standard back-propagation algorithm. The network has been used to form a stand-alone electronic nose system capable of distinguishing between four odours.
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© 1995 Springer-Verlag/Wien
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James-Roxby, P.B. (1995). A Neural Network Implementation for a Electronic Nose. In: Artificial Neural Nets and Genetic Algorithms. Springer, Vienna. https://doi.org/10.1007/978-3-7091-7535-4_110
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DOI: https://doi.org/10.1007/978-3-7091-7535-4_110
Publisher Name: Springer, Vienna
Print ISBN: 978-3-211-82692-8
Online ISBN: 978-3-7091-7535-4
eBook Packages: Springer Book Archive