Abstract

A three unit artificial neural network (ANN) automatic target recognition (ATR) system is integrated within, and compared to, a recently AFIT developed conventional ATR system. The integration of ANN within this existing framework allows the determination of where the benefits of using these biologically motivated processing techniques lie. The integration and testing of ANN within each of the three units constitutes the major contribution of this research. The emphasis of this paper is in the area of effects of learning alternatives on ATR. Several alternative feedforward networks were compared in the classifier unit.

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