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eLoom: a specification, simulation and visualization engine for modeling arbitrary hierarchical neural architectures

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3 Author(s)
Yunhai Xiao ; Dept. of Electr. & Comput. Eng., New Mexico Univ., Albuquerque, NM, USA ; Caudell, T.P. ; Healy, M.J.

Visualization is a useful method for understanding both learning and computation in artificial neural networks. There are a large number of parameters in a neural network. By viewing these parameters pictorially, a better understanding can be gained of how a network maps inputs to outputs. eLoom is an open source graph simulation tool, developed at the University of New Mexico, that enables users to specify and simulate various neural network models. Its specification language enables users to construct and simulate arbitrary, potentially hierarchical network structures on serial and parallel processing systems. In addition, eLoom is integrated with UNM's Flatland, an open source virtual environment development tool to provide real-time visualizations of the network structure and activity. ART-1 and LAPART-II neural networks are presented to illustrate eLoom and Flatland's capabilities.

Published in:

Neural Networks, 2003. Proceedings of the International Joint Conference on  (Volume:4 )

Date of Conference:

20-24 July 2003

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