Abstract
This chapter serves as an introduction to the main subject of this book — multi-layer perceptron (MLP) training1. The multi-layer perceptron is the most widely-used class of neural network. Much of the popularity of MLPs is attributable to the fact that they have been applied successfully to a wide range of information processing tasks, including pattern classification, function learning and time series prediction. Practical applications for MLPs have been found in such diverse fields as speech recognition, image compression, medical diagnosis, autonomous vehicle control and financial prediction; new applications are being discovered all the time. (For a useful survey of practical MLP applications, see Lisboa (1992).)
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© 1997 Springer-Verlag London Limited
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Shepherd, A.J. (1997). Multi-Layer Perceptron Training. In: Second-Order Methods for Neural Networks. Perspectives in Neural Computing. Springer, London. https://doi.org/10.1007/978-1-4471-0953-2_1
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DOI: https://doi.org/10.1007/978-1-4471-0953-2_1
Publisher Name: Springer, London
Print ISBN: 978-3-540-76100-6
Online ISBN: 978-1-4471-0953-2
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