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What is Feed-Forward Artificial Neural Network

Encyclopedia of Artificial Intelligence
Artificial Neural Network whose graph has no cycles.
Published in Chapter:
Learning in Feed-Forward Artificial Neural Networks II
Lluís A. Belanche Muñoz (Universitat Politècnica de Catalunya, Spain)
Copyright: © 2009 |Pages: 6
DOI: 10.4018/978-1-59904-849-9.ch149
Abstract
Supervised Artificial Neural Networks (ANN) are information processing systems that adapt their functionality as a result of exposure to input-output examples. To this end, there exist generic procedures and techniques, known as learning rules. The most widely used in the neural network context rely in derivative information, and are typically associated with the Multilayer Perceptron (MLP). Other kinds of supervised ANN have developed their own techniques. Such is the case of Radial Basis Function (RBF) networks (Poggio & Girosi, 1989). There has been also considerable work on the development of adhoc learning methods based on evolutionary algorithms.
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Learning in Feed-Forward Artificial Neural Networks I
Artificial Neural Network whose graph has no cycles.
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Feed-Forward Artificial Neural Network Basics
Artificial Neural Network whose graph has no cycles.
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