Artificial neural networks

  • Robert Fullér
Part of the Advances in Soft Computing book series (AINSC, volume 2)


Artificial neural systems can be considered as simplified mathematical models of brain-like systems and they function as parallel distributed computing networks. However, in contrast to conventional computers, which are programmed to perform specific task, most neural networks must be taught, or trained. They can learn new associations, new functional dependencies and new patterns. Although computers outperform both biological and artificial neural systems for tasks based on precise and fast arithmetic operations, artificial neural systems represent the promising new generation of information processing networks.


Neural Network Artificial Neural Network Weight Vector Learning Rule Training Cycle 
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

  • Robert Fullér
    • 1
    • 2
  1. 1.Department of Operations ResearchEötvös Lorànd UniversityBudapestHungary
  2. 2.Institute of Advanced Management Systems ResearchÅbo Akademi UniversityTurkuFinland

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