Multilayer Perceptrons: Architecture and Error Backpropagation

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.