averaging filter

In theory, a temporal recursive low pass filter model is developed and used to update the background dynamically based on multi-frames moving weighted averaging and motion detecting. Actually, several proposals lie in the derivation of the parameter k in the model.

采用了多帧运动加权平均理论及运动检测理论建立了时域递归低通滤波算法模型，并将该模型应用于缓慢变化的背景预测。

Thesis analyzes superposition average algorithm of tradition and pointed out the limitations of the algorithm, the problems about that the residual interference noise and the incubation period of disturbance, proposes a superposition averaging algorithm based on the arc tangent function of the IIR filter.

论文分析传统叠加平均算法并指出该算法的局限，对残留干扰噪声及潜伏期的扰动问题，提出一种基于反正切函数的IIR滤波器叠加平均算法。

The algorithm smoothes magnetic time series using a variant length sliding-window averaging filter, then a PLA representation scheme is employed to extract the feature, which in turn is passed to a threshold detection module.

算法首先将磁敏数据时间序列经过变长滑动窗口滤波预处理，由PLA抽取平滑后的时间序列特征，用于车辆检测，从而获得相关的交通信息。