Optimization of multiple model neural tracking filter for marine targets

The paper presents the research on optimizing multiple model neural filter with the use of Monte Carlo simulation. GRNN filters are used as elementary filters and different parameters of them are examined. The paper includes theoretical background of the research, analysis of a problem and a set of numerical experiments. The research was made with the use of Monte Carlo simulation. The results of the optimization can be used in further works with the filter and for final verification of the method.

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