Results 161 to 170 of about 411,141 (342)

An note on the maximization of matrix valued Hankel determinants with application [PDF]

In this note we consider the problem of maximizing the determinant of moment matrices of matrix measures. The maximizing matrix measure can be characterized explicitly by having equal (matrix valued) weights at the zeros of classical (one dimensional ...
Dette, Holger, Studden, W. J.
core  

Neural Geometry Processing via Spherical Neural Surfaces

Computer Graphics Forum, EarlyView.
Abstract Neural surfaces (e.g., neural map encoding, deep implicit, and neural radiance fields) have recently gained popularity because of their generic structure (e.g., multi‐layer perceptron) and easy integration with modern learning‐based setups. Traditionally, we have a rich toolbox of geometry processing algorithms designed for polygonal meshes to
Romy Williamson, Niloy J. Mitra
wiley   +1 more source

Multiphysics Simulation Methods in Computer Graphics

Computer Graphics Forum, EarlyView.
Abstract Physics simulation is a cornerstone of many computer graphics applications, ranging from video games and virtual reality to visual effects and computational design. The number of techniques for physically‐based modeling and animation has thus skyrocketed over the past few decades, facilitating the simulation of a wide variety of materials and ...
Daniel Holz, Stefan Rhys Jeske, Fabian Löschner, Jan Bender, Yin Yang, Sheldon Andrews   +5 more
wiley   +1 more source

Five-diagonal matrices and zeros of orthogonal polynomials on the unit circle [PDF]

arXiv, 2002
It is shown that monic orthogonal polynomials on the unit circle are the characteristic polynomials of certain five-diagonal matrices depending on the Schur parameters. This result is achieved through the study of orthogonal Laurent polynomials on the unit circle.
arxiv  

Linearization of Arbitrary products of classical orthogonal polynomials [PDF]

, 2000
Mahouton Norbert Hounkonnou, S. Belmehdi, A. Ronveaux   +2 more
openalex   +1 more source

Dual equations and classical orthogonal polynomials

Journal of Mathematical Analysis and Applications, 1968
Abstract : Dual integral equations involving Bessel functions and dual series equations involving Jacobi polynomials occur in several branches of applied mathematics and large classes of these equations can now be solved. We show how many dual sequence equations involving Jacobi and Laguerre polynomials can be solved by similar methods. (Author)
openaire   +2 more sources

How much are we willing to pay for quality wine? A meta‐analysis and meta‐regression analysis

Journal of Economic Surveys, EarlyView.
Abstract This paper performs a meta‐analysis and a meta‐regression analysis on the price semi‐elasticity of wine quality ratings in the context of estimating hedonic price functions. To do so, we thoroughly search for publications that have estimated hedonic functions in this market, resulting in 223 articles estimating 1595 functions, although not all
Jacobo Núñez, David Martín‐Barroso, Juan A. Núñez‐Serrano, Francisco J. Velázquez   +3 more
wiley   +1 more source

Mixed orthogonality graphs for continuous‐time state space models and orthogonal projections

Journal of Time Series Analysis, EarlyView.
In this article, we derive (local) orthogonality graphs for the popular continuous‐time state space models, including in particular multivariate continuous‐time ARMA (MCARMA) processes. In these (local) orthogonality graphs, vertices represent the components of the process, directed edges between the vertices indicate causal influences and undirected ...
Vicky Fasen‐Hartmann, Lea Schenk
wiley   +1 more source

On classical orthogonal polynomials on bi-lattices

Analysis and Mathematical Physics
In [J. Phys. A: Math. Theor. 45 (2012)], while looking for spin chains that admit perfect state transfer, Vinet and Zhedanov found an apparently new sequence of orthogonal polynomials, that they called para-Krawtchouk polynomials, defined on a bilinear lattice.
Castillo, K., Filipuk, G., Mbouna, D.
openaire   +2 more sources

Markov Determinantal Point Process for Dynamic Random Sets

Journal of Time Series Analysis, EarlyView.
ABSTRACT The Law of Determinantal Point Process (LDPP) is a flexible parametric family of distributions over random sets defined on a finite state space, or equivalently over multivariate binary variables. The aim of this paper is to introduce Markov processes of random sets within the LDPP framework. We show that, when the pairwise distribution of two
Christian Gouriéroux, Yang Lu
wiley   +1 more source