An Application of Exponential Neural Networks to Event-Train Recognition.
Final rept. 5 Jan 1990-8 May 1992,
WRIGHT LAB WRIGHT-PATTERSON AFB OH
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The purpose of this project is to investigate neural networks for specific applications in passive electronic warfare EW involving restoration of deinterleaved pulse trains to their original broadcast form. The project took a generic event-train approach and focused on event-train recognition. It was determined that back propagation neural networks did not represent a logistically supportable means of training. Gaussian radial basis functions were found to be far superior. This report is composed of three chapters 1 summary of early experiments, 2 introduction to exponential neural networks, and 3 application to event-train recognition. Each chapter has its own references. We believe that the goal can be reached and that additional experiments, with greater data volumes, are warranted.