Title:
ApplicationImproved--r-Algorithm
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Description: Particle filter algorithm for nonlinear systems is widely used, its accuracy depends on whether the target probability function and importance of the functions are similar, and sample degradation also affects the performance of the algorithm. For particle filter algorithm sample degradation problem, this paper proposes a particle filter algorithm based on singular value decomposition. The algorithm by using singular value decomposition of the importance of the probability density function method to get closer to the target probability distribution, reduce sample degradation, improve the accuracy of the filter, and then apply the algorithm in combination mathematical model train positioning system simulation experiments. The simulation
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ApplicationImproved r Algorithm.doc
