Teaching Course on Artificial Neural Networks

  • J. Fulcher
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 36)


The more commonly used Artificial Neural Network models are first characterized. These characteristics — training parameters and the like — are related to high-level language constructs (C/C++). The necessity of Graphical User Interfaces, from an educational perspective, is highlighted. Experiences are then recounted gained from a decade of teaching a graduate-level course on ANNs. Representative public domain and commercial ANN software simulators are covered (some of the former types accompanying ANN textbooks). Particular emphasis is placed on BackPropagation/Multi-Layered Perceptrons using NeuralWare software.


Artificial Neural Network Hide Layer Artificial Neural Network Model Learn Vector Quantization Hopfield Network 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • J. Fulcher
    • 1
  1. 1.School of Information Technology and Computer ScienceUniversity of WollongongAustralia

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