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Probability Density Function (pdf)

Parameterizing deep convection using the assumed probability density function method

Parameterizing deep convection using the assumed probability density function method

... Deep convection has often been parameterized by the use of mass-flux schemes (e.g., Arakawa and Schubert, 1974; Kain and Fritsch, 1990; Donner, 1993; Zhang and Mc- Farlane, 1995; Arakawa, 2004; Kain, 2004; Gerard, 2007; ...

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Application of Rayleigh Probability Density Function in Electromagnetic Wave Propagation

Application of Rayleigh Probability Density Function in Electromagnetic Wave Propagation

... Rayleigh Probability Density Function (Rayleigh PDF) is used for the cases in which there is non-line of sight (NLOS)[1] between transmitters and receivers for the communication networks and channel ...

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Probability density function estimation using orthogonal forward regression

Probability density function estimation using orthogonal forward regression

... the probability density function (PDF) based on a realisation sample drawn from the underlying density is based on a non-parametric approach ...non-parametric density estimation ...

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Modelling and control of the flame temperature distribution using probability density function shaping

Modelling and control of the flame temperature distribution using probability density function shaping

... This paper presents three control algorithms for the output probability density function (PDF) control of the 2D and 3D flame distribution systems. For the 2D flame distribution systems, control ...

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AK P: An Active Learning Method Combing Kriging and Probability Density Function for Reliability Analysis

AK P: An Active Learning Method Combing Kriging and Probability Density Function for Reliability Analysis

... performance function has been a key research ...performance function with highly nonlinear input-output relationships ...with probability density function in this ...

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Minimization of the Difference between the Theoretical Mean of the Rayleigh Probability Density Function and the Mean Obtained from its Plot

Minimization of the Difference between the Theoretical Mean of the Rayleigh Probability Density Function and the Mean Obtained from its Plot

... Rayleigh Probability Density Function and the mean of the plot of Rayleigh function, we modified the equation (10) and obtained the equation (14) as the ultimate expression for the ...

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Shaping of molecular weight distribution by iterative learning probability density function control strategies

Shaping of molecular weight distribution by iterative learning probability density function control strategies

... Though the first-principle model has the ability of predicting MWD dynamically, it will not be used directly in MWD control. Instead, a B-spline approx- imation model is established from the data produced by the ...

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Robust Scale Estimation for the Generalized Gaussian Probability Density Function

Robust Scale Estimation for the Generalized Gaussian Probability Density Function

... However, in most applications, the scale parameter cannot be inferred, and needs to be estimated in parallel to θ with a much lower breakdown than 50%. Recently several strate- gies involving nonparametric ...

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The New Kumaraswamy Kumaraswamy Weibull Distribution with Application

The New Kumaraswamy Kumaraswamy Weibull Distribution with Application

... The probability density function (pdf), the cumulative distribution function (cdf), moments, quantiles, the median, the mode, the mean deviation, the entropy, order statistics, L-moments, ...

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201q_lect4.pdf

201q_lect4.pdf

... a probability distribution function, continuous random variables are characterized by a probability density ...a probability density function is equal to 1, and the area ...

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Seismic Hazard Analysis based on the Joing Probability Density Function of PGA and PGV

Seismic Hazard Analysis based on the Joing Probability Density Function of PGA and PGV

... low probability are affected by the decrease in correlation ...high probability are not affected, since seismic hazard with high probability is dominated by the small earthquakes which possess large ...

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Linear location estimators : the dependence of their quality on the shape of the probability density function, and their robustness

Linear location estimators : the dependence of their quality on the shape of the probability density function, and their robustness

... TABLE 2.6.6 The Coefficients W[I] and Variances of the Best Linear Estimators for N = 8 for the 10% Contaminated Normal Distribution and two Nearby Distributions with Cutpoints 0·~5 and [r] ...

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Some results on a generalized ω Jacobi transform

Some results on a generalized ω Jacobi transform

... new probability density function (pdf) involv- ing the generalized ω-Jacobi function in the third ...distribution function, survival function, characteristic function, and ...

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Mathamatics syllabus grade12and 13.pdf

Mathamatics syllabus grade12and 13.pdf

... Probability distribution of a discrete random variable Probability density function of a continuous random variable.. 5.8 Interprets the mathematical expectation of a random variable.[r] ...

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A generalized beta function and associated probability density

A generalized beta function and associated probability density

... new probability density function (pdf) involving this new generalized beta ...generating function, mean residue function, and hazard rate function are ...rate function, ...

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A Probability Density Function Generator Based on Deep Learning

A Probability Density Function Generator Based on Deep Learning

... as activation functions in the hidden layers of the proposed deep learning model for learning actual.. 151[r] ...

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Probability density function estimation using orthogonal forward regression

Probability density function estimation using orthogonal forward regression

... Outline o Motivations/overview for sparse kernel density estimation o Proposed sparse kernel density estimator: m Convert unsupervised density learning into constrained regression by ado[r] ...

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THE DISTRIBUTION OF THE SUM OF MIXED INDEPENDENT RANDOM VARIABLES PERTAINING TO SPECIAL FUNCTIONS

THE DISTRIBUTION OF THE SUM OF MIXED INDEPENDENT RANDOM VARIABLES PERTAINING TO SPECIAL FUNCTIONS

... different probability density functions. One with probability density function defined in finite range and the other with probability density function defined in ...

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Understanding Probability

Understanding Probability

... Definition 11.1 The continuous random variables X and Y are said to have a joint probability density function f x, y if the joint cumulative probability distribution function PX :Sa, Y :[r] ...

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Recursive parameter estimation for semimartingales

Recursive parameter estimation for semimartingales

... The kernel function and convolution-smoothing methods developed to estimate a probability density function and distribution are essen- tially a way of smoothing the empirical distributio[r] ...

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