Share Email Print
cover

Proceedings Paper

MONNET: a software system for modular neural networks based on object passing
Author(s): Rupert Lange; Reinhard Maenner
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

Modular neural networks integrate several neural networks and possibly standard processing methods. Tackling such models is a challenge, since various modules have to be combined, either sequentially or in parallel, and the simulations are time critical in many cases. For this, specific tools are prerequisite that are both flexible and efficient. We have developed the MONNET software system that supports the investigation of complex modular models. The design of MONNET is based on the object oriented paradigm, the environment is C++/UNIX. The basic concepts are dynamic modularity, object passing, scalability, reusability, and extensibility. MONNET features flexible and compact definition of complex simulations, and minimal overhead in order to run computationally demanding simulations efficiently.

Paper Details

Date Published: 2 September 1993
PDF: 12 pages
Proc. SPIE 1965, Applications of Artificial Neural Networks IV, (2 September 1993); doi: 10.1117/12.152539
Show Author Affiliations
Rupert Lange, Univ. Mannheim (Germany)
Reinhard Maenner, Univ. Mannheim and Univ. Heidelberg (Germany)


Published in SPIE Proceedings Vol. 1965:
Applications of Artificial Neural Networks IV
Steven K. Rogers, Editor(s)

© SPIE. Terms of Use
Back to Top