The authors discuss the applicability of multi-layer Neural Networks (NN) to automatic target classification in the challenging environment of Acquisition-Tracking-Pointing (ATP) systems. The merits of NN are discussed in the context of a limited training data base, which is characteristic of practical ATP situations. A computational method is reviewed which allows the quantification of large-scale NN performance for the important small-sample case. In addition; Perceptron learning for the classification of target stochastic images governed by the Poisson distribution is examined with the aid of computer simulations.
Application on artificial neural networks to ATP functions
Anwendung von neuronalen Netzen bei der Durchführung von ATP-Funktionen (Zielerkennung und -verfolgung)
1992
24 Seiten, 6 Bilder, 16 Quellen
Conference paper
English
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