Neural Networks
Barbara Hammer, CITEC centre of excellence, Bielefeld University, D-33594 Bielefeld, Germany, bhammer@techfak.uni-bielefeld.de
Abstract
Neural networks constitute a standard tool for diverse machine learning tasks in the supervised as well as the unsupervised domain, addressing issues such as function approximation, classification, dynamic system modeling, associative memory, etc. In this chapter, different types of neural networks which are used in machine learning are introduced, whereby we focus on supervised paradigms first, turning to self-organizing principles and unsupervised scenarios in the second half of the chapter. For both parts, the complexity of the considered neural network architectures serves as the ...
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