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An introductory survey of probability density function control
Systems Science & Control Engineering, 2019 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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Best Probability Density Function for Random Sampled Data [PDF]
Entropy, 2009 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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Fusion of Probability Density Functions
Proceedings of the IEEE, 2022 Fusing probabilistic information is a fundamental task in signal and data processing with relevance to many fields of technology and science. In this work, we investigate the fusion of multiple probability density functions (pdfs) of a continuous random variable or vector.
Günther Koliander +3 more
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Time-dependent probability density function for partial resetting dynamics
New Journal of Physics, 2023 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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On the Probability Density Function of Baskets [PDF]
, 2015 The state price density of a basket, even under uncorrelated Black-Scholes dynamics, does not allow for a closed from density. (This may be rephrased as statement on the sum of lognormals and is especially annoying for such are used most frequently in Financial and Actuarial Mathematics.) In this note we discuss short time and small volatility ...
Bayer, Christian +2 more
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Parameterizing deep convection using the assumed probability density function method [PDF]
Geoscientific Model Development, 2015 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]
Nonlinear Processes in GeophysicsA 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
Sci, 2022 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
Theoretical and Applied Mechanics Letters, 2022 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
Data Science Journal, 2006 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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