Simulating nonstationary non-Gaussian vector process based on continuous wavelet transform

Han Hong

doi:10.1016/j.ymssp.2021.108340

Simulating nonstationary non-Gaussian vector process based on continuous wavelet transform

2022-02-01

31

PRE

AI

DOI：10.1016/j.ymssp.2021.108340

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In the present study, we propose a new iterative algorithm based on discretized continuous wavelet transform (CWT) to simulate nonstationary non-Gaussian vector process for prescribed marginal probability distribution functions and the time-scale power spectral density function matrix. The algorithm is designed for a CWT pair within the wavelet analysis framework. It can be used with analytical wavelets satisfying the admissibility condition and can cope with time dependent and time-independent coherence. The proposed algorithm is applied to generate nonstationary downburst winds and seismic ground motions at multiple sites within the wavelet analysis framework. The numerical validation analysis confirms that the proposed algorithm can lead to the simulated records matching the prescribed marginal probability distribution, marginal time-scale power spectral density function and coherence function.

Keyword:

Simulation

Continuous wavelet transform

Nonstationary

Non-Gaussian

Generalized Morse wavelets

Wavelet spectrum

Ground motions

Wind speed

Simulating nonstationary non-Gaussian vector process based on continuous wavelet transform

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