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density function

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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Unwrapped phase estimation via normalized probability density function for multibaseline InSAR

Unwrapped phase estimation via normalized probability density function for multibaseline InSAR

... ABSTRACT Interferometric synthetic aperture radar (InSAR) is a powerful technique for obtaining terrain information based on the interferometric phase. Multibaseline (MB) InSAR is an extension of the conven- tional InSAR ...

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An Error Controlled Method to Determine the Stellar Density Function in a Region  of the Sky

An Error Controlled Method to Determine the Stellar Density Function in a Region of the Sky

... stellar density function in a region of the sky with complete error controlled ...the density stellar function due to the variance of the least squares solutions ...

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Non-Stationary Statistics with Amplitude Probability Density Function for Exposure and Energy Density Reporting Near a Mobile Phone Running 4G Applications

Non-Stationary Statistics with Amplitude Probability Density Function for Exposure and Energy Density Reporting Near a Mobile Phone Running 4G Applications

... probability density function capability of a real-time spectrum analyzer and on computing the integrated energy density in air (at incidence to the ...

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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

... realized a closed-loop control system of the boiler flame by the radiant energy obtained from the temperature of the flame. Serial control was employed to solve the large inertia problem through the radiant energy as an ...

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Estimating the Spectral Power Density Function of Non-Gaussian Second Order Autoregressive Model

Estimating the Spectral Power Density Function of Non-Gaussian Second Order Autoregressive Model

... Spectral Density Function (PSD) of Non-Gaussian second order autoregressive model AR(2)when the random error of model follows Non-Gaussian distribution (discrete and continuous)for different sample sizes ...

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Robust Kernel Density Function Estimation

Robust Kernel Density Function Estimation

... of density function as initial similarity (or distance) measure of observations with the ...estimate density function ...kernel function to formulate the robust density ...

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Probability density function estimation using orthogonal forward regression

Probability density function estimation using orthogonal forward regression

... 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 ...kernel ...

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Forecasting Density Function: Application in Finance

Forecasting Density Function: Application in Finance

... ksdensity function of Matlab on the S&P 500 data, we found out that over 40% of the fitted density function contains many extremely small (less than ...fitted density functions that ...

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Robust Scale Estimation for the Generalized Gaussian Probability Density Function

Robust Scale Estimation for the Generalized Gaussian Probability Density Function

... The main idea of this article is to consider the generation of new variables whose distribu- tions show relevant properties for the estimation of an unknown parameter of the original variable. In particular, modes or ...

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Application of Rayleigh Probability Density Function in Electromagnetic Wave Propagation

Application of Rayleigh Probability Density Function in Electromagnetic Wave Propagation

... 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

... 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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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

... length distribution control in paper industries [41], flame temperature distribution control in combustion processes [42], etc. Unlike the mean and variance control in Gaussian processes, the output PDF is a ...

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Elucidating Cellular Population Dynamics by Molecular Density Function Perturbations

Elucidating Cellular Population Dynamics by Molecular Density Function Perturbations

... The heat maps are arranged in increasing magnitude of peak sensitivities (i.e. scaling factor shown in the bottom right corner).. Supplementary Figure S6: Spearman correlations of [r] ...

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A Herschel-SPIRE survey of the Mon R2 giant molecular cloud: analysis of the gas column density probability density function

A Herschel-SPIRE survey of the Mon R2 giant molecular cloud: analysis of the gas column density probability density function

... greybody function and an optimal beta value of ...column density histogram, or column density probability distribution function (N-PDF), is lognormal below ∼10 21 cm − 2 ...column ...

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Elucidating Cellular Population Dynamics by Molecular Density Function Perturbations

Elucidating Cellular Population Dynamics by Molecular Density Function Perturbations

... apoptosis model during post-MOMP (after 1.76 hours), Figure S5: MDFP analysis of non-apoptotic Hela. 361[r] ...

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Deep-based conditional probability density function forecasting of residential loads

Deep-based conditional probability density function forecasting of residential loads

... probability density forecasting of residential loads, based on a deep mixture ...mixture density network (MDN) to directly predict probability density functions ...loss function in the direct ...

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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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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

... Limiting the number of indices, however, gives large uncertainty in the estimation of annual failure probability that is given by convolving seismic hazard curve and seismic fragility c[r] ...

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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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