The optimal moving average filter for the linear stochastic controlled plant is developed from the viewpoint of the internal model of the deterministic disturbance.
从确定性干扰的内模观点导出了适用于线性随机受控对象的最优滑动滤波器。
Using the methods of time series spectral analysis and Kalman filter, this article discussed the additive problems of two stochastic processes, mainly Auto Regression Moving Average (ARMA) processes.
本文利用时间序列谱分析和卡尔曼滤波的方法讨论了两个随机过程，主要是自回归滑动平均(ARMA)过程，的叠加问题。
Experiments show that wavelet filtering can enhance the small fault detection capacity and detect more timely compared with exponentially weighted moving average (EWMA) filter.
实验表明，小波滤波法能提高小故障的检测能力，而且与指数权重滑动平均滤波法相比更具有故障检测的及时性。
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