Abstract
Artificial neural networks attracted renewed interest over the last decade, mainly because new learning methods capable of dealing with large scale learning problems were developed. After the pioneering work of Rosenblatt and others, no efficient learning algorithm for multilayer or arbitrary feed forward neural networks was known. This led some to the premature conclusion that the whole field had reached a dead-end. The rediscovery of the backpropagation algorithm in the 1980s, together with the development of alternative network topologies, led to the intense outburst of activity which put neural computing back into the mainstream of computer science.
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© 1996 Springer-Verlag Berlin Heidelberg
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Rojas, R. (1996). Fast Learning Algorithms. In: Neural Networks. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-61068-4_8
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DOI: https://doi.org/10.1007/978-3-642-61068-4_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-60505-8
Online ISBN: 978-3-642-61068-4
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