Abstract
This chapter deals with artificial neural networks for static modeling. Artificial neural networks were originally motivated by the biological structures in the brains of humans and animals, which are extremely powerful for such tasks as information processing, learning, and adaptation. Good overviews on the biological background can be found in [326, 328]. The most important characteristics of neural networks are
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large number of simple units,
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highly parallel units,
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strongly connected units,
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robustness against the failure of single units,
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learning from data.
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© 2001 Springer-Verlag Berlin Heidelberg
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Nelles, O. (2001). Neural Networks. In: Nonlinear System Identification. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-04323-3_10
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DOI: https://doi.org/10.1007/978-3-662-04323-3_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-08674-8
Online ISBN: 978-3-662-04323-3
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