Continuous-time Stochastic Processes 连续时间随机过程
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。
To characterize the properties and construction of multipfractal products of stochastic processes is important for capturing the traffic behavior at all time scales.
研究统计过程的复分形结构及其特征属性是研究网络业务全尺度下的行为的重要内容。
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