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Stochastic Model for Simulation of Ground-Motion Sequences Using Kernel-Based Smoothed Wavelet Transform and Gaussian Mixture Distribution

机译:基于内核平滑小波变换和高斯混合分布模拟地面运动序列模拟的随机模型

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摘要

In this paper, a stochastic-parametric model is developed for simulating the temporal and spectral nonstationary characteristics of ground motion sequences. In the proposed model, after extracting the wavelet coefficients of a ground motion sequence by using the complex discrete wavelet transform and smoothing them by the Normal kernel function, they are simulated by using the Gaussian mixture distribution. This model simulates multiple peaks in the time domain, several dominant frequency peaks at each time, the relaxation time between motions, and the steps of cumulative energy curve of ground motion sequences, while the previous models did not have these abilities.
机译:本文开发了一种随机参数模型,用于模拟地面运动序列的时间和光谱非间断特性。 在所提出的模型中,通过使用复杂的离散小波变换并通过正常的核功能平滑它们,通过使用高斯混合分布来模拟它们之后在接地运动序列的小波系数之后。 该模型在时域中模拟了多个峰,每次多个主频峰,运动之间的松弛时间,以及地面运动序列的累积能量曲线的步骤,而先前的模型没有这些能力。

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