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Research of Velocity Detection Based on the Adaptive Weighted Average Algorithm

机译:基于自适应加权平均算法的速度检测研究

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In recent years, the weighted average algorithm is discussed more and more. In order to maximize the Signal Noise Ratio (SNR) and minimize the variance of the signals, the weights are utilized. In this thesis, a traffic velocity detection of adaptive weighted-average is presented, in which, a reasonable result with enough precision could be got. Compared with other weighted average method, a large storage of data does not demanded in the adaptive weighted average algorithm. The simulation result is given too, which shows that the fitting curves of actual velocity and fused velocity is good enough to satisfy the actual demand of real-time completely.
机译:近年来,越来越多地讨论了加权平均算法。为了最大化信号噪声比(SNR)并最小化信号的方差,使用权重。在本文中,提出了自适应加权平均值的交通速度检测,其中,可以得到足够的精度的合理结果。与其他加权平均方法相比,在自适应加权平均算法中不需要大量存储数据。仿真结果也是给出的,这表明实际速度和稠合速度的拟合曲线足以满足完全实际的实际需求。

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