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Training Set Density Estimation For Trajectory Predictions Using Artificial Neural Networks, Zachary Reinke
Training Set Density Estimation For Trajectory Predictions Using Artificial Neural Networks, Zachary Reinke
Masters Theses
Demand on earth orbiting surveillance systems in increasing as more equipment is put into orbit. These systems rely on predictive techniques to periodically track objects. The demand on these systems may be reduced if object trajectory data to develop scalable training sets used for training artificial neural networks (ANNs) to predict trajectories of a dynamic system. These methods use multi-variable statistics to analyze data energy content to provide the ANN with low density, feature-rich, training data. The developed techniques have been shown to increase ANN prediction accuracy while reducing the size of the training set when applied to a linear …