An introductory survey of probability density function control
Probability density function (PDF) control strategy investigates the controller design approaches where the random variables for the stochastic processes were adjusted to follow the desirable distributions. In other words, the shape of the system PDF can
Mifeng Ren, Qichun Zhang, Jianhua Zhang
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Time-dependent probability density function for partial resetting dynamics
Stochastic resetting is a rapidly developing topic in the field of stochastic processes and their applications. It denotes the occasional reset of a diffusing particle to its starting point and effects, inter alia, optimal first-passage times to a target.
Costantino Di Bello +4 more
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Parameterizing deep convection using the assumed probability density function method [PDF]
Due to their coarse horizontal resolution, present-day climate models must parameterize deep convection. This paper presents single-column simulations of deep convection using a probability density function (PDF) parameterization.
R. L. Storer +7 more
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Prognostic assumed-probability-density-function (distribution density function) approach: further generalization and demonstrations [PDF]
A methodology for directly predicting the time evolution of the assumed parameters for distribution densities based on the Liouville equation, as proposed earlier, is extended to multidimensional cases and to cases in which the systems are constrained by
J.-I. Yano
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Replacing Histogram with Smooth Empirical Probability Density Function Estimated by K-Moments
Whilst several methods exist to provide sample estimates of the probability distribution function at several points, for the probability density of continuous stochastic variables, only a gross representation through the histogram is typically used.
Demetris Koutsoyiannis
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A Lagrangian-based flame index for the transported probability density function method
We propose a new flame index for the transported probability density function (PDF) method. The flame index uses mixing flux projections of Lagrangian particles on mixture fraction and progress variable directions as the metrics to identify the ...
Zhen Lu +4 more
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Visualization techniques for spatial probability density function data
Novel visualization methods are presented for spatial probability density function data. These are spatial datasets, where each pixel is a random variable, and has multiple samples which are the results of experiments on that random variable.
Udeepta D Bordoloi +2 more
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The Calculation of the Density and Distribution Functions of Strictly Stable Laws
Integral representations for the probability density and distribution function of a strictly stable law with the characteristic function in the Zolotarev’s “C” parametrization were obtained in the paper.
Viacheslav Saenko
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Best Probability Density Function for Random Sampled Data
The maximum entropy method is a theoretically sound approach to construct an analytical form for the probability density function (pdf) given a sample of random events.
Donald J. Jacobs
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SIMPLE APPROACH OF THE SERVER’S BUSY PERIOD FOR SELFSERVICE SYSTEM WITH FEEDBACK [PDF]
In this paper, we provide an easy method to obtain thedistribution of busy period for self-service queue with feedback. Usingprobability generating function we obtain the probability that there are nunits in the system at time t , pn ( t ) and the ...
S. E. Abou Karam, K. A. M. Kotb
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