Integer-encoded massively parallel processing of fast-learning fuzzy ARTMAP neural networks

Hubert A. Bahr; Ronald F. DeMara; Michael Georgiopoulos

doi:10.1117/12.271530

4 April 1997 Integer-encoded massively parallel processing of fast-learning fuzzy ARTMAP neural networks

Hubert A. Bahr, Ronald F. DeMara, Michael Georgiopoulos

Proceedings Volume 3077, Applications and Science of Artificial Neural Networks III; (1997) https://doi.org/10.1117/12.271530
Event: AeroSense '97, 1997, Orlando, FL, United States

Abstract

In this paper we develop techniques that are suitable for the parallel implementation of Fuzzy ARTMAP networks. Speedup and learning performance results are provided for execution on a DECmpp/Sx-1208 parallel processor consisting of a DEC RISC Workstation Front-End and MasPar MP-1 Back-End with 8,192 processors. Experiments of the parallel implementation were conducted on the Letters benchmark database developed by Frey and Slate. The results indicate a speedup on the order of 1000-fold which allows combined training and testing time of under four minutes.

Citation Download Citation

Hubert A. Bahr, Ronald F. DeMara, and Michael Georgiopoulos "Integer-encoded massively parallel processing of fast-learning fuzzy ARTMAP neural networks", Proc. SPIE 3077, Applications and Science of Artificial Neural Networks III, (4 April 1997); https://doi.org/10.1117/12.271530

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