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Proceedings Paper

Applications of neural nets to munition systems
Author(s): Kwang-Shik Min; Hisook L. Min
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Paper Abstract

We formulated special Kohonen type associative memories and studied their utilization as the fast discriminator/classifier in munition systems. These nets are pretrainable and the response time for classification is minimal. The time required for adaptation is short. The applications investigated include [1] a targetaerosol discrimination problem and [2] change detection leading to an image based decision making in a realistic system. Appropriate pre-processing of the data are required for these methods to be effective. The outline of the algorithm for each application is described and the results obtained using generic data are illustrated. This work was supported by AFOSR under RIP and URRP programs. * On leave from East Texas State University Commerce Texas. ** On leave from Jarvis Christian College Hawkins Texas. 466 / SPIE Vol. 1294 Applications of Artificial Neural Networks (1990)

Paper Details

Date Published: 1 August 1990
PDF: 12 pages
Proc. SPIE 1294, Applications of Artificial Neural Networks, (1 August 1990); doi: 10.1117/12.21198
Show Author Affiliations
Kwang-Shik Min, U.S. Air Force Armament Lab. (United States)
Hisook L. Min, U.S. Air Force Armament Lab. (United States)

Published in SPIE Proceedings Vol. 1294:
Applications of Artificial Neural Networks
Steven K. Rogers, Editor(s)

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