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Proceedings Paper

Comparative analysis of statistical, fuzzy, and artificial neural pattern recognition techniques
Author(s): Jay B. Jordan; Howon Choe
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Paper Abstract

A common mathematical foundation for the comparative analysis of statistical, fuzzy, and artificial neural pattern recognition or decision making systems is presented. This development uses abstract algebraic techniques to characterize the functions generating decision surfaces and the learning/training processes involved in each technique.

Paper Details

Date Published: 9 July 1992
PDF: 11 pages
Proc. SPIE 1699, Signal Processing, Sensor Fusion, and Target Recognition, (9 July 1992); doi: 10.1117/12.138223
Show Author Affiliations
Jay B. Jordan, New Mexico State Univ. (United States)
Howon Choe, New Mexico State Univ. (United States)


Published in SPIE Proceedings Vol. 1699:
Signal Processing, Sensor Fusion, and Target Recognition
Vibeke Libby; Ivan Kadar, Editor(s)

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