Digital simulation of two-dimensional random fields with arbitrary power spectra and non-Gaussian probability distribution functions.
نویسندگان
چکیده
Methods for simulation of two-dimensional signals with arbitrary power spectral densities and signal amplitude probability density functions are disclosed. The method relies on initially transforming a white noise sample set of random Gaussian distributed numbers into a corresponding set with the desired spectral distribution, after which this colored Gaussian probability distribution is transformed via an inverse transform into the desired probability distribution. In most cases the method provides satisfactory results and can thus be considered an engineering approach. Several illustrative examples with relevance for optics are given.
منابع مشابه
Digital simulation of an arbitrary stationary stochastic process by spectral representation.
In this paper we present a straightforward, efficient, and computationally fast method for creating a large number of discrete samples with an arbitrary given probability density function and a specified spectral content. The method relies on initially transforming a white noise sample set of random Gaussian distributed numbers into a corresponding set with the desired spectral distribution, af...
متن کاملOptimal power flow based on gray wolf optimization algorithm using probability density functions extraction considering wind power uncertainty
In recent years, utilization of the renewable based power plants has become widespread in the power systems. One of the most widely used renewable based power plants is wind power plants. Due to the utilization of wind energy to generate electricity, wind turbines have not emitted any environmental pollution. Thus, in addition to economic benefits, utilization of these power plants is of great ...
متن کاملPredictions of mixed non - Gaussian cosmological density fields for the cosmic microwave background radiation
We present simulations of the Cosmic Microwave Background Radiation (CMBR) power spectrum for a class of mixed, non-Gaussian, primordial random fields. We assume a skew positive mixed model with adiabatic inflation perturbations plus additional isocurvature perturbations possibly produced by topological defects. The joint probability distribution used in this context is a weighted combination o...
متن کاملStatistics of Fourier Modes in Non-Gaussian Fields
Fourier methods are fundamental tools to analyze random fields. Statistical structures of homogeneous Gaussian random fields are completely characterized by the power spectrum. In non-Gaussian random fields, polyspectra, higher-order counterparts of the power spectrum, are usually considered to characterize statistical information contained in the fields. However, it is not trivial how the Four...
متن کاملNumerical Simulation of Non-Gaussian Random Fields
The non-Gaussian random fields are used to modelling some dynamic loads generated by wind turbulence, ocean waves, earthquake ground motion etc. These fields also represent the uncertain properties of different materials (reinforced concrete, composite, soils etc.). This paper presents some methods and the corresponding algorithms to the numerical simulation of stationary non-Gaussian random fi...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- Applied optics
دوره 51 10 شماره
صفحات -
تاریخ انتشار 2012