Artificial Neural Networks

  • Andrea Tettamanzi
  • Marco Tomassini


THE functioning of the brain has always fascinated people. The human brain, and also the brain of some animals, is indeed capable of astonishing achievements such as remembering, recognizing patterns, and associating, among many others. The way in which these tasks are performed appears to be quite different in nature from standard computation as we know it, that is, in the Turing sense [146]. Indeed, the brain is a massively parallel, highly connected assemblage of an astronomical number of slow processing units that collectively work on these difficult tasks and allow us to function smoothly and effortlessly. These units or cells are called neurons, they are of several different types, and they work in an analog way by propagating electrical currents of chemical origin along connections. The details of how neurons function are very intricate and need not concern us here but the main points are simple and worth some study. The neuron has three main components: the soma, the dendrites, and the axon (Figure 2.1).


Artificial Neural Network Hide Layer Input Vector Boolean Function Artificial Neural Network Model 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Andrea Tettamanzi
    • 1
  • Marco Tomassini
    • 2
  1. 1.Information Technology DepartmentUniversity of MilanCrema (CR)Italy
  2. 2.Computer Science InstituteUniversity of LausanneLausanneSwitzerland

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