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An efficient ergodic simulation of multivariate stochastic processes with spectral representation

机译:具有频谱表示的多元随机过程的有效遍历仿真

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A simulation formula to generate stationary multivariate stochastic processes is derived from the Fourier-Stieltjes integral of spectral representation. It is proved that the proposed algorithm generates ergodic sample functions in the mean value and in the correlation when the sample length is equal to one period (the generated sample functions are periodic). The algorithm is very efficient computationally since it takes advantage of the fast Fourier transform technique. The simulation of longitudinal wind velocity fluctuations and the simulation of longitudinal and vertical wind fluctuating components on a bridge deck are performed. It has been noted that there are good agreements between the temporal and target auto-/cross-correlation functions of simulated wind velocities.
机译:从谱表示的傅里叶-斯蒂耶斯积分中导出了生成平稳多元随机过程的仿真公式。证明了该算法在样本长度等于一个周期(生成的样本函数是周期性的)时,以均值和相关性生成遍历样本函数。该算法在计算上非常有效,因为它利用了快速傅立叶变换技术。进行桥面纵向风速波动的模拟以及纵向和垂直风向波动分量的模拟。已经注意到,在模拟风速的时间和目标自相关/互相关函数之间有很好的一致性。

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