Search results for "Functions"
showing 10 items of 1066 documents
A robust evolutionary algorithm for the recovery of rational Gielis curves
2013
International audience; Gielis curves (GC) can represent a wide range of shapes and patterns ranging from star shapes to symmetric and asymmetric polygons, and even self intersecting curves. Such patterns appear in natural objects or phenomena, such as flowers, crystals, pollen structures, animals, or even wave propagation. Gielis curves and surfaces are an extension of Lamé curves and surfaces (superquadrics) which have benefited in the last two decades of extensive researches to retrieve their parameters from various data types, such as range images, 2D and 3D point clouds, etc. Unfortunately, the most efficient techniques for superquadrics recovery, based on deterministic methods, cannot…
Greedy and K-Greedy algoritmhs for multidimensional data association
2011
[EN] The multidimensional assignment (MDA) problem is a combinatorial optimization problem arising in many applications, for instance multitarget tracking (MTT). The objective of an MDA problem of dimension $d\in\Bbb{N}$ is to match groups of $d$ objects in such a way that each measurement is associated with at most one track and each track is associated with at most one measurement from each list, optimizing a certain objective function. It is well known that the MDA problem is NP-hard for $d\geq3$. In this paper five new polynomial time heuristics to solve the MDA problem arising in MTT are presented. They are all based on the semi-greedy approach introduced in earlier research. Experimen…
Generalized person-by-person optimization in team problems with binary decisions
2008
In this paper, we extend the notion of person by person optimization to binary decision spaces. The novelty of our approach is the adaptation to a dynamic team context of notions borrowed from the pseudo-boolean optimization field as completely local-global or unimodal functions and sub- modularity. We also generalize the concept of pbp optimization to the case where the decision makers (DMs) make decisions sequentially in groups of m, we call it mbm optimization. The main contribution are certain sufficient conditions, verifiable in polynomial time, under which a pbp or an mbm optimization algorithm leads to the team-optimum. We also show that there exists a subclass of sub-modular team pr…
Indefinite integrals of some special functions from a new method
2015
A substantial number of indefinite integrals of special functions are presented, which have been obtained using a new method presented in a companion paper [Conway JT. A Lagrangian method for deriving new indefinite integrals of special functions. Integral Transforms Spec Funct. 2015; submitted to]. The method was originally derived from the Euler–Lagrange equations but an elementary proof is also presented in [Conway JT. A Lagrangian method for deriving new indefinite integrals of special functions. Integral Transforms Spec Funct. 2015; submitted to]. Sample results are presented here for Bessel functions, Airy functions and hypergeometric functions. More extensive results are given for th…
"Table 45" of "Measurement of jet fragmentation in Pb+Pb and $pp$ collisions at $\sqrt{s_{NN}} = 5.02$ TeV with the ATLAS detector"
2020
The D(pT) distributions in different centrality intervals in PbPb and in pp for 158.49 < pTjet < 199.53 and 0.8 < eta < 1.2.
"Table 57" of "Measurement of jet fragmentation in Pb+Pb and $pp$ collisions at $\sqrt{s_{NN}} = 5.02$ TeV with the ATLAS detector"
2020
The D(pT) distributions in different centrality intervals in PbPb and in pp for 199.53 < pTjet < 251.19 and 0.3 < eta < 0.8.
"Table 81" of "Measurement of jet fragmentation in Pb+Pb and $pp$ collisions at $\sqrt{s_{NN}} = 5.02$ TeV with the ATLAS detector"
2019
The D(pT) distributions in different centrality intervals in PbPb and in pp for 251.19 < pTjet < 316.22 and 1.2 < eta < 2.1.
"Table 5" of "Measurement of jet fragmentation in Pb+Pb and $pp$ collisions at $\sqrt{s_{NN}} = 5.02$ TeV with the ATLAS detector"
2020
The D(pT) distributions in different centrality intervals in PbPb and in pp for 158.49 < pTjet < 199.53 and 0.0 < eta < 0.3.
"Table 13" of "Measurement of jet fragmentation in Pb+Pb and $pp$ collisions at $\sqrt{s_{NN}} = 5.02$ TeV with the ATLAS detector"
2020
The D(pT) distributions in different centrality intervals in PbPb and in pp for 251.19 < pTjet < 316.22 and 0.0 < eta < 2.1.
"Table 1" of "Measurement of jet fragmentation in Pb+Pb and $pp$ collisions at $\sqrt{s_{NN}} = 5.02$ TeV with the ATLAS detector"
2020
The D(pT) distributions in different centrality intervals in PbPb and in pp for 126.00 < pTjet < 158.49 and 0.0 < eta < 2.1.