where y is the random vector with m double difference code and phase observations, a the n-vector with unknown integer carrier phase ambiguities, i.e. a2Z, b is a p-vector with the unknown real-valued parameters, and e is the noise vector. The real-valued parameters are referred to as the baseline unknowns, although b may also contain for example atmospheric delays. The covariance matrix of the...

Understanding the mesoscopic behavior of dynamical systems described by Langevin equations with colored noise is a fundamental challenge in a variety of fields. We propose a new approach to derive closed-form equations for joint and marginal probability density functions of state variables. This approach is based on a so-called large-eddy-diffusivity closure and can be used to model a wide clas...

The CANDID project (Comparison Algorithm for Navigating Digital Image Databases) employs probability density functions (PDFs) of localized feature information to represent the content of an image for search and retrieval purposes. A similarity measure between PDFs is used to identify database images that are similar to a user-provided query image. Unfortunately, signature comparison involving P...

A new sparse kernel probability density function (pdf) estimator based on zero-norm constraint is constructed using the classical Parzen window (PW) estimate as the target function. The so-called zero-norm of the parameters is used in order to achieve enhanced model sparsity, and it is suggested to minimize an approximate function of the zero-norm. It is shown that under certain condition, the ...

In this article we propose a method of performing arithmetic operations on variables with unknown distribution. The approach to the evaluation results of arithmetic operations can select probability intervals of the algebraic equations and their systems solutions, of differential equations and their systems in case of histogram evaluation of the empirical density distributions of random paramet...

The maximum entropy method is a theoretically sound approach to construct an analytical form for the probability density function (pdf) given a sample of random events. In practice, numerical methods employed to determine the appropriate Lagrange multipliers associated with a set of moments are generally unstable in the presence of noise due to limited sampling. A robust method is presented tha...

in order to restrain the potential of wind energy, the first step is to determine the wind energy potential. in this study the wind data was used from the three-hour frequency recording of 10-year period (2002-2011). to predict the occurrence probability of each wind speed, the two-parameter weibull function was used. the goodness of fit test by chi-square test showed that the wind speed distri...

Novel visualization methods are presented for spatial probability density function data. These are spatial datasets, where each pixel is a random variable, and has multiple samples which are the results of experiments on that random variable. We use clustering as a means to reduce the information contained in these datasets; and present two different ways of interpreting and clustering the data...

In this study, signal voltage obtained at the receiver is investigated by taking the Rayleigh Probability Density Function into account. Probability of received signal and occurrence of incoming signal between two levels are also studied. Success percentage, requirement of how much the receiver is to be modified and variation of voltage or power at the output with respect to time are simulated ...

The asymptotic probability density function of nonlinear phase noise, often called the Gordon-Mollenauer effect, is derived analytically when the number of fiber spans is very large. The nonlinear phase noise is the summation of infinitely many independently distributed noncentral chi-square random variables with two degrees of freedom. The mean and standard deviation of those random variables ...