On Mathematical Modeling of Networks and Implementation Aspects

  • Regina Bernhaupt
  • Jochen Pfalzgraf
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2385)


Based on existing work where categorical and geometrical methods were used to establish a mathematical model of neural net structures, we develop a new very general model for artificial neural networks (ANN), where all basic components of a network are described abstractly. This mathematical model serves as a guideline for design and implementation of a new ANN-simulator. The proposed model of neuron types will be illustrated by the discussion of an example, using the Single Spiking Neuron Model (SSM). The main building blocks of the simulation tool, a new construction principle for ANN, and abstract modeling of connection weights are presented.


Multi Agent System Neuron Type Connection Structure Implementation Aspect Processing Entity 
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 2002

Authors and Affiliations

  • Regina Bernhaupt
    • 1
  • Jochen Pfalzgraf
    • 1
  1. 1.Department of Computer ScienceUniversity of SalzburgSalzburgAustria

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