Linear inverse Gaussian problems is traditionally solved using least squares based inversion. The center of the posterior Gaussian probability distribution is often chosen as the solution to such problems, while the solution is in fact the posterior Gaussian probability distribution itself. We present an algorithm, based on direct sequential simulation, which can be used to efficiently draw sam...

Non-Gaussian normal diffusion, i.e., the probability density function (PDF) is non-Gaussian but the mean squared displacement (MSD) depends on time linearly, has been observed in particle motions. Here we show by numerical simulations that this phenomenon may manifest itself in energy diffusion along a lattice at a nonzero, finite temperature. The studied model is a one-dimensional disordered l...

Intermittency in fluid turbulence can be evidentiated through the analysis of Probability Distribution Functions (PDF) for velocity fluctuations, which display a strong non–gaussian behavior at small scales. In this paper we investigate the occurrence of intermittency in plasma turbulence by studying the departure from the gaussian distribution of PDF for both velocity and magnetic fluctuations...

For a rational determination of safety factors, it is necessary to establish the probability density distribution function (pdf) of the structural strength. For perfectly ductile and perfectly brittle materials, the proper pdf’s of the nominal strength of structure are known to be Gaussian and Weibullian, respectively, and are invariable with structure size and geometry. However, for quasibritt...

In this paper the receiver for demodulation of M-FSK signals in the presence of Gaussian noise, intersymbol interference and Rice fading will be considered. Probability density function (PDF) of M-ary FSK signals in the presence of noise, interference and fading will be derived. Key-words: M-ary Frequency Shift Keying, Probability Density Function, Gaussian noise, Intersymbol Interference, Rice...

Two pdf models suitable for describing non-Gaussian iid noise are introduced. The models are used in the design of a LOD test for detecting weak signals in real non-Gaussian noise. Results obtained in the context of an underwater acoustic application are encouraging.

1.0 Rayleigh Distribution Using central limit theorem arguments, one can show that the I and Q channels on a mobile radio multipath fading channel are independent Gaussian (normal) random variables. Jakes [1] and others show that the envelope of two independent and identically distributed (iid) Gaussian random variables is Rayleigh distributed.1 Probability Density Function (pdf) (usual form fo...

There has been overwhelming evidence that coherent structures play a critical role in determining the overall transport in a variety of systems. We compute the probability distribution function (PDF) tails of momentum flux and heat flux in ion-temperature-gradient turbulence, by taking into account the interaction among modons, which are assumed to be coherent structures responsible for bursty ...

We present a computationally efficient method to generate random variables from a univariate conditional probability density function (PDF) derived from a multivariate α-sub-Gaussian (αSG) distribution. The approach may be used to sequentially generate variates for sliding-window models that constrain immediately adjacent samples to be αSG random vectors. We initially derive and establish vario...