Search results for "Hull"

Classification of cat ganglion retinal cells and implications for shape-function relationship

2002

This article presents a quantitative approach to ganglion cell classification by considering combinations of several geometrical features including fractal dimension, symmetry, diameter, eccentricity and convex hull. Special attention is given to moment and symmetry-based features. Several combinations of such features are fed to two clustering methods (Ward's hierarchical scheme and K-Means) and the respectively obtained classifications are compared. The results indicate the superiority of some features, also suggesting possible biological implications.

On some close to convex functions with negative coefficients

2007

In this paper we propose for study a class of close to convex functions with negative coefficients defined by using a modified Salagean operator. .

Strictly convex metric spaces with round balls and fixed points

2005

An upper bound for nonlinear eigenvalues on convex domains by means of the isoperimetric deficit

2010

We prove an upper bound for the first Dirichlet eigenvalue of the p-Laplacian operator on convex domains. The result implies a sharp inequality where, for any convex set, the Faber-Krahn deficit is dominated by the isoperimetric deficit.

On dependence of sets of functions on the mean value of their elements

2009

The paper considers, for a given closed bounded set M ⊂ R m and K = (0,1) n ⊂ R n , the set M = {h ϵ L2 (K;R m ) | h(x) ϵ M a.e.x ϵ K} and its subsets It is shown that, if a sequence {hk } ⊂ coM converges to an element hk ϵ M(hk ) there is h‘k ϵ M(ho ) such that h'k - hk → 0 as k → ∞ . If, in addition, the set M is finite or M is the convex hull of a finite set of elements, then the multivalued mapping h → M(h) is lower semicontinuous on coM. First published online: 14 Oct 2010

R Code for Hausdorff and Simplex Dispersion Orderings in the 2D Case

2010

This paper proposes a software implementation using R of the Hausdorff and simplex dispersion orderings. A copy can be downloaded from http://www.uv.es/~ayala/software/fun-disp.R . The paper provides some examples using the functions exactHausdorff for the Hausdorff dispersion ordering and the function simplex for the simplex dispersion orderings. Some auxiliary functions are commented too.

Weak convergence theorems for asymptotically nonexpansive mappings and semigroups

2001

The project scheduling polyhedron: Dimension, facets and lifting theorems

1993

Abstract The Project scheduling with resource constraints can be formulated as follows: given a graph G with node set N, a set H of directed arcs corresponding to precedence relations, and a set H′ of disjunctive arcs reflecting the resource incompatibilities, find among the subsets of H′ satisfying the resource constraints the set S that minimizes the longest path in graph (N, H ∪ S). We define the project scheduling polyhedron Qs as the convex hull of the feasible solutions. We investigate several classes of inequalities with respect to their facet-defining properties for the associated polyhedron. The dimension of Qs is calculated and several inequalities are shown to define facets. For …

Experiments with an adaptive Bayesian restoration method

1989

Abstract This paper describes a Bayesian restoration method applied to two-dimensional measured images, whose detector response function is not completely known. The response function is assumed Gaussian with standard deviation depending on the estimate of the local density of the image. The convex hull of the K -nearest neighbours ( K NN) of each ‘on’ pixel is used to compute the local density. The method has been tested on ‘sparse’ images, with and without noise background.

Enclosure method for the p-Laplace equation

2014

We study the enclosure method for the p-Calder\'on problem, which is a nonlinear generalization of the inverse conductivity problem due to Calder\'on that involves the p-Laplace equation. The method allows one to reconstruct the convex hull of an inclusion in the nonlinear model by using exponentially growing solutions introduced by Wolff. We justify this method for the penetrable obstacle case, where the inclusion is modelled as a jump in the conductivity. The result is based on a monotonicity inequality and the properties of the Wolff solutions.