Journal ArticleDOI
Digital simulation of random processes and its applications
Masanobu Shinozuka,C.-M. Jan +1 more
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TLDR
In this article, the authors presented an efficient method for digital simulation of general homogeneous processes as a series of cosine functions with weighted amplitudes, almost evenly spaced frequencies, and random phase angles.About:
This article is published in Journal of Sound and Vibration.The article was published on 1972-11-08. It has received 1460 citations till now. The article focuses on the topics: Stochastic process & Random variable.read more
Citations
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Dynamics of a Duffing Oscillator With Two Time Delays in Feedback Control Under Narrow-Band Random Excitation
Yanfei Jin,Haiyan Hu +1 more
TL;DR: In this article, the primary resonance of a Duffing oscillator with two distinct time delays in the linear feedback control under narrow-band random excitation was analyzed and the analytical results were in well agreement with the numerical results.
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Stochastic Dynamics of a Nonlinear Misaligned Rotor System Subject to Random Fluid-Induced Forces
Zigang Li,Jun Jiang,Zhui Tian +2 more
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Research on parametric resonance in a stochastic van der Pol oscillator under multiple time delayed feedback control
X.L. Yang,Z.K. Sun +1 more
TL;DR: In this article, an analytical derivation and numerical calculations are employed to gain insight into the parametric resonance of a stochastically driven van der Pol oscillator with delayed feedback, which is the prototype of a self-excited system operating with a combination of narrow-band noise excitation and two time delayed feedback control.
Journal ArticleDOI
Stochastic simulation of the high-frequency wave propagation in a random medium
TL;DR: In this article, a stochastic model is proposed to simulate the propagation of an acoustic wave in a random medium characterized by weak velocity fluctuations, where the wave field becomes itself a random field.
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Distribution of the maximum of a Gaussian process by a Monte Carlo method
TL;DR: In this article, a simple practical procedure for approximating a stationary Gaussian process over a finite interval by a trigonometric polynomial with predetermined error is described, and the approximation is then used to calculate the distribution of the maximum, by using a novel Monte Carlo method with a control variable which drastically reduces the variance.
References
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Journal ArticleDOI
Stationary and Related Stochastic Processes
Journal ArticleDOI
Simulation of Multivariate and Multidimensional Random Processes
TL;DR: In this article, the authors present efficient and practical methods of simulating multivariate and multidimensional processes with specified cross-spectral density matrix, which can be expressed as the sum of cosine functions with random frequencies and random phase angles.