The aim of this reported work is to extend a recent, simple and effective algorithm for the estimation of the probability density function and cumulative density function to the case of bidimensional random vectors. The algorithm is based on an information maximisation approach. The nonlinear bidimensional function involved in the algorithm is adaptively modified during learning and is implemen...

0360-8352/$ see front matter Published by Elsevier doi:10.1016/j.cie.2010.01.008 q This manuscript was processed by Area Editor E.A * Tel.: +1 845 938 5988. E-mail address: [email protected] A variation of maximum likelihood estimation (MLE) of parameters that uses probability density functions of order statistic is presented. Results of this method are compared with traditional maximum like...

Summarizing the whole support of a random variable into minimum volume sets of its probability density function is studied in the paper. We prove that the level sets of a probability density function correspond to minimum volume sets and also determine the conditions for which the inverse proposition is verified. The distribution function of the level cuts of a density function is also introduc...

We investigate the statistics of flat-top solitary wave parameters in the presence of weak multiplicative dissipative disorder. We consider first propagation of solitary waves of the cubic-quintic nonlinear Schrödinger equation (CQNLSE) in the presence of disorder in the cubic nonlinear gain. We show by a perturbative analytic calculation and by Monte Carlo simulations that the probability-dens...

In this paper, a novel method for estimating a precise object region using a given rough object region is proposed. For determining whether each pixel belongs to an object or not, the proposed method estimates a joint probability density function (joint p.d.f.) of position, color, and class (object or background). For each pixel, the class with a higher joint p.d.f. is selected. The joint p.d.f...

In 1986 S. Sattolo introduced a simple algorithm for uniform random generation of cyclic permutations on a fixed number of symbols. Recently, H. Prodinger analysed two important random variables associated with the algorithm, and found their mean and variance. H. Mahmoud extended Prodinger’s analysis by finding limit laws for the same two random variables.The present article, starting from the ...

Since the domain of crystallographic orientations is three-dimensional and spherical, their insightful rendering or rendering of related probability density functions requires (i) to exploit the effect of a given orientation on crystallographic axes, (ii) to consider spherical means of the orientation probability density function with respect to lower–dimensional manifolds, and (iii) to apply p...

Accurate and fast estimation of probability density functions is crucial for satisfactory computational performance in many scientiic problems. When the type of density is known a priori, then the problem becomes statistical estimation of parameters from the observed values. In the non-parametric case, usual estimators make use of kernel functions. If X j ; j = 1; 2; : : : ; n is a sequence of ...

Estimation of probability density functions (pdf) is one major topic in pattern recognition. Parametric techniques rely on an arbitrary assumption on the form of the underlying, unknown distribution. Nonparametric techniques remove this assumption In particular, the Parzen Window (PW) relies on a combination of local window functions centered in the patterns of a training sample. Although effec...

Techniques from numerical bifurcation theory are very useful to study transitions between steady fluid flow patterns and the instabilities involved. Here, we provide computational methodology to use parameter continuation in determining probability density functions of systems of stochastic partial differential equations near fixed points, under a small noise approximation. Key innovation is th...