Multilayer Perceptrons: Architecture and Error Backpropagation

Ke-Lin Du () and M. N. S. Swamy
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Ke-Lin Du: Concordia University, Department of Electrical and Computer Engineering
M. N. S. Swamy: Concordia University, Department of Electrical and Computer Engineering

Chapter Chapter 5 in Neural Networks and Statistical Learning, 2019, pp 97-141 from Springer

Abstract: Abstract Multilayer perceptron is one of the most important neural network models. It is a universal approximator for any continuous multivariate function. This chapter centers on the multilayer perceptron model, and the backpropagation learning algorithm. Some related topics, such as network architecture optimization, learning speedup strategies, and first-order gradient-based learning algorithms, are also introduced.

Date: 2019
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DOI: 10.1007/978-1-4471-7452-3_5

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