Probability density
Non-Stationary Statistics with Amplitude Probability Density Function for Exposure and Energy Density Reporting Near a Mobile Phone Running 4G Applications
... energy density (IED) evolution in time. Using the amplitude probability density (APD) function capability of a real-time spectrum analyzer, we demonstrate the differences in exposure due to five ...
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Modelling and control of the flame temperature distribution using probability density function shaping
... To improve the efficiency and safety of various boilers used in industries, the flame temperature distribution (FTD) must be well controlled (Fu et al., 1989). Generally, the source fuels of the boiler can be either ...
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Nonparametric Estimation of Probability Density Functions of Random Persistence Diagrams
... kernel density centered at a particular persistence ...a probability density function (pdf) of a random persistence ...kernel density is centered at a persistence diagram and describes each ...
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Unwrapped phase estimation via normalized probability density function for multibaseline InSAR
... The MLE method [25], estimating the phase values of each pixel separately, can adapt to the view angle and the topo- graphic slope, even at the lack of priori information about the observed scene. Extensive research on ...
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Low Complexity Algorithm for Probability Density Estimation Applied in Big Data Analysis
... for probability density esti- mation, one of most important problems and widely applied in telecommunication traffic analysis, predictor agent and ...
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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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Audio Query by Example Using Similarity Measures between Probability Density Functions of Features
... This paper proposes a query by example system for generic audio. Section 2 gives an overview of the system and previous similarity measures. We observe that the similarity of audio signals can be measured by the di ff ...
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Reconstruction of one-dimensional chaotic maps from sequences of probability density functions
... Abstract In many practical situations, it is impos- sible to measure the individual trajectories generated by an unknown chaotic system, but we can observe the evolution of probability density functions ...
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Robust Scale Estimation for the Generalized Gaussian Probability Density Function
... mixture model. This method is based on the definition of two random variables Y and Z computed from the samples of variable X using a non-linear transformation. The distributions of those new variables have properties ...
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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 ...kernel ...
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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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A refined statistical cloud closure using double-Gaussian probability density functions
... a probability density function (PDF)-based scheme to parameterize cloud fraction, average liquid water and liquid water flux in large-scale models, that is developed from and tested against large-eddy ...
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Cloud discrimination in probability density functions of limb-scattered sunlight measurements
... clouds. Probability density functions of scattering residuals show the distribution is not a continuum measurement; there is a distinction between the cloudy and cloud-free ...
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Deep-based conditional probability density function forecasting of residential loads
... conditional probability density forecasting of residential loads, based on a deep mixture ...mixture density network (MDN) to directly predict probability density functions ...kernel ...
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A generalized beta function and associated probability density
... 4. The probability density function. In a systematic study of generalized pdf and their statistical properties, special functions have played a significant role [2, 3, 6, 7, 10]. Chaudhry and Zubair [5, 4] ...
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Time-Dependent Probability Density Functions and Attractor Structure in Self-Organised Shear Flows
... The extension of refs. [17,18] solved a stochastic differential equation with a fourth-order stochastic Runga–Kutta method for Gaussian coloured noise in 1D and showed the transition from an unimodal stationary ...
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Exact and Approximate Weighted Model Integration with Probability Density Functions Using Knowledge Compilation
... In the initial work on weighted model integration (Belle, Passerini, and Van den Broeck 2015) the authors perform weighted model integration on piecewise polynomials by it- eratively generating models by adding the ...
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Shaping of molecular weight distribution by iterative learning probability density function control strategies
... The control efforts in the above discussions should be regarded as open-loop control in terms of the MWD property because the optimal profiles relating to the desired MWD are determined in an off-line manner. To realize ...
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Time-Dependent Probability Density Functions and Attractor Structure in Self-Organised Shear Flows
... The extension of refs. [17,18] solved a stochastic differential equation with a fourth-order stochastic Runga–Kutta method for Gaussian coloured noise in 1D and showed the transition from an unimodal stationary ...
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Inconsistency of Probability Density in Quantum Mechanics and Its Solution
... the probability density and have discovered its inconsitency for all quantum me- chanical systems which can be solved ...of probability density may give rise confusion for students and readers ...
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