Results 11 to 20 of about 2,561,356 (330)

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
doaj   +2 more sources

Probability Density Function [PDF]

Encyclopedia of Mathematical Geosciences, 2011
A. D. Nascimento
semanticscholar   +7 more sources

Fusion of Probability Density Functions [PDF]

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.
Koliander, Günther, El-Laham, Yousef, Djurić, Petar M., Hlawatsch, Franz   +3 more
openaire   +3 more sources

Deep learning for presumed probability density function models [PDF]

Combustion and Flame, 2019
In this work, we use machine learning (ML) techniques to develop presumed probability density function (PDF) models for large eddy simulations (LES) of reacting flows.
M. H. D. Frahan, S. Yellapantula, R. King, M. Day, R. Grout   +4 more
semanticscholar   +1 more source

A probability density function generator based on neural networks

Physica A: Statistical Mechanics and its Applications, 2020
In order to generate a probability density function (PDF) for fitting the probability distributions of practical data, this study proposes a deep learning method which consists of two stages: (1) a training stage for estimating the cumulative ...
Chi-Hua Chen, Fang-Quan Song, F. Hwang, Ling Wu   +3 more
semanticscholar   +1 more source

Deep-Based Conditional Probability Density Function Forecasting of Residential Loads

IEEE Transactions on Smart Grid, 2020
This paper proposes a direct model for conditional probability density forecasting of residential loads, based on a deep mixture network. Probabilistic residential load forecasting can provide comprehensive information about future uncertainties in ...
M. Afrasiabi, M. Mohammadi, Mohammad Rastegar, L. Stanković, Shahabodin Afrasiabi, M. Khazaei   +5 more
semanticscholar   +1 more source

A new approach on fractional calculus and probability density function

AIMS Mathematics, 2020
In statistical analysis, oftentimes a probability density function is used to describe the relationship between certain unknown parameters and measurements taken to learn about them.
Shu-Bo Chen, S. Rashid, M. Noor, Rehana Ashraf, Y. Chu   +4 more
semanticscholar   +1 more source

Multivariate quantile mapping bias correction: an N-dimensional probability density function transform for climate model simulations of multiple variables

Climate Dynamics, 2017
Most bias correction algorithms used in climatology, for example quantile mapping, are applied to univariate time series. They neglect the dependence between different variables.
Alex J. Cannon
semanticscholar   +1 more source

The Calculation of the Density and Distribution Functions of Strictly Stable Laws

Mathematics, 2020
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
doaj   +1 more source

The Probability Density Function of Bearing Obtained From a Cartesian-to-Polar Transformation

IEEE Access, 2022
The problem of tracking a two-dimensional Cartesian state of a target using polar observations is well known. At a close range, a traditional extended Kalman filter (EKF) can fail owing to nonlinearity introduced by the Cartesian-to-polar transformation ...
Kevin R. Ford, Anton J. Haug
doaj   +1 more source