Concurrent Object-Oriented Simulation of Neural Network Models

Gregory L. Heileman, Michael Georgiopoulos, William D. Roome

Research output: Chapter in Book/Report/Conference proceedingConference contribution


The analysis of complex neural network models via aneilytical techniques is often quite difficult due to the large numbers of components involved, and the nonlinearities associated with these components. For this reason, simulation is seen as an important tool in neural network research. In this paper we present a framework for simulating neural networks as discrete event nonlinear dynamical systems. This includes neurai network models whose components are described by continuous-time differential equations, or by discrete-time difference equations. Specifically, we consider the design and construction of a concurrent object-oriented discrete event simulation environment for neural networks. The use of an object-oriented language provides the data abstraction facilities necessary to support modification and extension of the simulation system at a high level of abstraction. Furthermore, the ability to specify concurrent processing supports execution on parallel architectures. The use of this system is demonstrated by simulating a specific neural network model on a general-purpose parallel computer.

Original languageEnglish (US)
Title of host publicationProceedings - 1992 International Joint Conference on Neural Networks, IJCNN 1992
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages7
ISBN (Electronic)0780305590
StatePublished - 1992
Externally publishedYes
Event1992 International Joint Conference on Neural Networks, IJCNN 1992 - Baltimore, United States
Duration: Jun 7 1992Jun 11 1992

Publication series

NameProceedings of the International Joint Conference on Neural Networks


Conference1992 International Joint Conference on Neural Networks, IJCNN 1992
Country/TerritoryUnited States

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence


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