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Towards using particle filtering for increasing error correction accuracy in traffic surveillance applications

机译:致力于在交通监控应用中使用粒子滤波来提高纠错精度

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摘要

This paper analyzes and compares two error correction algorithms in context of traffic control applications. They are the Sequential Importance Sampling (SIS) and the Sequential Importance Resampling (SIR). Performances of both algorithms are analyzed and conclusions are drawn. Moreover, experimental results prove that algorithms' parameters have a great impact on their performances.
机译:本文分析并比较了交通控制应用中的两种纠错算法。它们是顺序重要性采样(SIS)和顺序重要性重采样(SIR)。分析了两种算法的性能并得出结论。此外,实验结果证明算法参数对其性能有很大影响。

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