The Experts below are selected from a list of 177 Experts worldwide ranked by ideXlab platform
C.c. Wackerman - One of the best experts on this subject based on the ideXlab platform.
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The modified Beta Density function as a model for synthetic aperture radar clutter statistics
IEEE Transactions on Geoscience and Remote Sensing, 1991Co-Authors: A.l. Maffett, C.c. WackermanAbstract:The authors show that the modified Beta distribution function is an adequate model for the underlying distribution function of the random variable used to model synthetic-aperture radar (SAR) image data. The model represents a range of SAR returns from different sea ice types by using a simple change in its parameter. The ability is explained by describing the distribution functions in, width. modified skewness space where the modified Beta function covers a region while the other, more common, distribution functions cover only a curve. A procedure for comparing simple distribution functions with analytical functions specifically for digitized SAR data is presented. >
Luis Diez - One of the best experts on this subject based on the ideXlab platform.
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System for automated diagnosis in cellular networks based on performance indicators
European Transactions on Telecommunications, 2005Co-Authors: Raquel Barco, V. Wille, Luis DiezAbstract:This paper presents a system for automated diagnosis of problems in a cellular network, which comprises a method and a model. The reasoning method, based on a naive Bayesian classifier, can be applied to the identification of the fault cause in GSM/GPRS, 3G or multi-systems networks. A diagnosis model for GSM/GPRS radio access networks is also described, whose elements are available in the network management systems (NMSs) of most networks. It is shown that the statistical relations among the elements, that is the quantitative part of the model, under certain assumptions, can be completely specified by means of the parameters of Beta Density functions. In order to support the theoretical concepts, a model has been built based on data from a real network and the automated diagnosis system has been used to classify problems in a cellular network, showing that the solution is easily implemented and that the diagnosis accuracy is very high, therefore leading to a reduction in the operational costs of running the network. Copyright © 2005 AEIT.
A.l. Maffett - One of the best experts on this subject based on the ideXlab platform.
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The modified Beta Density function as a model for synthetic aperture radar clutter statistics
IEEE Transactions on Geoscience and Remote Sensing, 1991Co-Authors: A.l. Maffett, C.c. WackermanAbstract:The authors show that the modified Beta distribution function is an adequate model for the underlying distribution function of the random variable used to model synthetic-aperture radar (SAR) image data. The model represents a range of SAR returns from different sea ice types by using a simple change in its parameter. The ability is explained by describing the distribution functions in, width. modified skewness space where the modified Beta function covers a region while the other, more common, distribution functions cover only a curve. A procedure for comparing simple distribution functions with analytical functions specifically for digitized SAR data is presented. >
Arakaparampil M. Mathai - One of the best experts on this subject based on the ideXlab platform.
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Erdélyi-Kober fractional integral operators from a statistical perspective -II
Cogent Mathematics, 2017Co-Authors: Arakaparampil M. Mathai, Hans J. HauboldAbstract:In this paper we examine the densities of a product and a ratio of two real positive definite matrix-variate random variables X1 and X2, which are statistically independently distributed, and we consider the Density of the product U1=X212X1X212 as well as the Density of the ratio U2=X212X1-1X212. We define matrix-variate Kober fractional integral operators of the first and second kinds from a statistical perspective, making use of the derivation in the predecessor of this paper for the scalar variable case, by deriving the densities of product cand ratios where one variable has a matrix-variate type-1 Beta Density and the other matrix variable has an arbitrary Density, in the sense, any real-valued scalar function f(X) of matrix argument X, such that f(X) is non-negative for all X and the total integral over all X, on the support of f(X), is unity. A number of generalizations are considered, by using pathway models, by appending matrix variate hypergeometric series etc. During this process matrix-variate ...
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M-convolutions of products and ratios, statistical distributions and fractional calculus
Analysis, 2016Co-Authors: Arakaparampil M. MathaiAbstract:AbstractIt is shown that Mellin convolutions of products and ratios in the real scalar variable case can be considered as densities of products and ratios of two independently distributed real scalar positive random variables. It is also shown that these are also connected to Krätzel integrals and to the Krätzel transform in applied analysis, to reaction-rate probability integrals in astrophysics and to other related aspects when the random variables have gamma or generalized gamma densities, and to fractional calculus when one of the variables has a type-1 Beta Density and the other variable has an arbitrary Density. Matrix-variate analogues are also discussed. In the matrix-variate case, the M-convolutions introduced by the author are shown to be directly connected to densities of products and ratios of statistically independently distributed positive definite matrix random variables in the real case and to Hermitian positive definite matrices in the complex domain. These M-convolutions reduce to Mellin convolutions in the scalar variable case.
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Erdelyi-Kober Fractional Integral Operators from a Statistical Perspective -III
arXiv: Classical Analysis and ODEs, 2013Co-Authors: Arakaparampil M. Mathai, Hans J. HauboldAbstract:In this article we examine the densities of a product and a ratio of two real positive definite matrix-variate random variables $X_1$ and $X_2$, which are statistically independently distributed, and we consider the Density of the product $U_1=X_2^{1\over2}X_1X_2^{1\over2}$ as well as the Density of the ratio $U_2=X_2^{1\over2}X_1^{-1}X_2^{1\over2}$. We define matrix-variate Kober fractional integral operators of the first and second kinds from a statistical perspective, making use of the derivation in the predecessor of this paper for the scalar variable case, by deriving the densities of products and ratios where one variable has a matrix-variate type-1 Beta Density and the other variable has an arbitrary Density. Various types of generalizations are considered, by using pathway models, by appending matrix variate hypergeometric series etc. During this process matrix-variate Saigo operator and other operators are also defined and properties studied.
Andreas Schumann - One of the best experts on this subject based on the ideXlab platform.
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Incorporating structural uncertainty of hydrological models in likelihood functions via an ensemble range approach
Hydrological Sciences Journal, 2016Co-Authors: C. Tyralla, Andreas SchumannAbstract:ABSTRACTModel ensembles are possibly the most powerful tool to assess uncertainties in runoff predictions stemming from inadequacies in model structure. But in many applications little knowledge is gained about the specific weaknesses of the individual models. Here we introduce the ensemble range approach (ERA). Compared to other ensemble techniques, ERA is primarily intended to facilitate hydrological reasoning about model structural uncertainty. This is attempted by separate modelling of data uncertainty and structural uncertainty with two different error Density functions that are combined in one likelihood function. The width of the structural error Density is in accordance with the range of runoff predictions calculated by a small model ensemble at each individual time step. Albeit not the only choice, this study is restricted on the use of a modified Beta Density to represent structural uncertainty. The performance of ERA is assessed in some synthetic and real data case studies. Ensembles of two str...