Comparative analysis of statistical, fuzzy, and artificial neural pattern recognition techniques

Jay B. Jordan; Howon Choe

doi:10.1117/12.138223

9 July 1992 Comparative analysis of statistical, fuzzy, and artificial neural pattern recognition techniques

Jay B. Jordan, Howon Choe

Proceedings Volume 1699, Signal Processing, Sensor Fusion, and Target Recognition; (1992) https://doi.org/10.1117/12.138223
Event: Aerospace Sensing, 1992, Orlando, FL, United States

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.

Citation Download Citation

Jay B. Jordan and Howon Choe "Comparative analysis of statistical, fuzzy, and artificial neural pattern recognition techniques", Proc. SPIE 1699, Signal Processing, Sensor Fusion, and Target Recognition, (9 July 1992); https://doi.org/10.1117/12.138223

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