Abstract
A description is given of the role of mathematics in shaping our understanding of how neural networks operate, and the curious new mathematical concepts generated by our attempts to capture neural networks in equations. A selection of relatively simple examples of neural network tasks, models and calculations, is presented.
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© 1998 Springer-Verlag London Limited
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Coolen, A.C.C. (1998). A Beginner’s Guide to the Mathematics of Neural Networks. In: Landau, L.J., Taylor, J.G. (eds) Concepts for Neural Networks. Perspectives in Neural Computing. Springer, London. https://doi.org/10.1007/978-1-4471-3427-5_2
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DOI: https://doi.org/10.1007/978-1-4471-3427-5_2
Publisher Name: Springer, London
Print ISBN: 978-3-540-76163-1
Online ISBN: 978-1-4471-3427-5
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