نتایج جستجو برای: flow statistical featur

تعداد نتایج: 841297  

Journal: :Annals OR 2009
Natalia M. Markovich Jorma Kilpi

We approximate the distribution of the TCP-flow rate by deriving it from the joint bivariate distribution of the flow sizes and flow durations of a given access network. The latter distribution is represented by a bivariate extreme value distribution using the Pickand’s dependence A-function. We estimate the A-function to measure the dependencies of random pairs: TCP-flow size and duration, the...

1996
Joachim Denzler Volker Schless Dietrich Paulus Heinrich Niemann

2008
Anton Šurda

Statistical mechanics of a small system of cars on a single-lane road is developed. The system is not characterized by a Hamiltonian but by a conditional probability of a velocity of a car for the given velocity and distance of the car ahead. Distribution of car velocities for various densities of a group of cars are derived as well as probabilities of density fluctuations of the group for diff...

2016
Yusuke Kawamoto Fabrizio Biondi Axel Legay

Analysis of a probabilistic system often requires to learn the joint probability distribution of its random variables. The computation of the exact distribution is usually an exhaustive precise analysis on all executions of the system. To avoid the high computational cost of such an exhaustive search, statistical analysis has been studied to efficiently obtain approximate estimates by analyzing...

Journal: :Ultrasonics 2000
S Bjaerum H Torp

The filter used to separate blood signals from the tissue clutter signal is an important part of a color flow system. In this paper, statistical detection theory is used to evaluate the quality of the most commonly used clutter filters. The probability of falsely classifying a sample volume as containing blood is kept below a specified threshold. With this constraint, the probability of correct...

2000
Ronan Fablet Patrick Bouthemy

In this paper, we propose an original approach for content-based video indexing and retrieval. It relies on the tracking of entities of interest and the analysis of their apparent motion. To characterize the dynamic information attached to these objects, we consider a probabilistic modeling of the spatio-temporal distribution of the optic flow field computed within the tracked area after cancel...

1994
Mike West

{ Gravity models are a class of log-linear regressions that have been used in studies of traac ows between geographical zones. Stochastic parameter variations on these models, and their Bayesian analyses via stochastic simulation, are explored here in connection with the development of approaches to studying variability questions in established traac ow network equilibrium models. In addition t...

1997
Michael M. Daniel

The development of accurate mathematical models describing the flow of groundwater is an important problem due to the prevalence of contaminants in or near groundwater supplies. An important parameter of these models is hydraulic conductivity, which describes the ability of the subsurface geology to conduct water flow. Because hydraulic conductivity is a function of the earth's subsurface, dire...

Journal: :IEEE transactions on image processing : a publication of the IEEE Signal Processing Society 1999
Charles Kervrann Fabrice Heitz

We present a statistical method for the motion-based segmentation of deformable structures undergoing nonrigid movements. The proposed approach relies on two models describing the shape of interest, its variability, and its movement. The first model corresponds to a statistical deformable template that constrains the shape and its deformations. The second model is introduced to represent the op...

2002
Akira Hayashi Ryuji Nakashima Toshihiko Kanbara Nobuo Suematsu

This paper presents a method to classify scenes based on motion information. While they use object trajectories or optical flow field as motion information in previous work, we use the instantaneous motions of multiple objects in each image. In order to deal with variable number of objects in a scene, we use moment statistics as features. Our approach is based on clustering, a form of unsupervi...

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