In topographical global optimization a sample of points that superuniformly cover the region of interest, A, is used in combination with the function evaluations in these points to obtain a topographical graph of A from which candidate points are easily extracted for local minimizations. This paper discusses some of the problems in obtaining such a cover and presents some solutions. These solut...

The exploration of the human connectome, a term denoting the global structural connectivity of the brain, is accessible to MRI at millimeter and centimeter scales. In this paper, we propose a methodology to map the connectome by constructing normalized whole-brain structural connection matrices derived from diffusion spectrum MRI tractography. Using a template-based approach, we propose a robus...

In this paper a combination of Evolution Programming and Branching is used to solve some typical problems in space trajectory design: finding a number of possible minimum cost transfers, including the global one, between two celestial bodies. The idea is to use a limited population evolving for a small number of generations, according to some specific evolution rules, in subregions of the solut...

Energy and environmental issues are crucially interrelated. There are two concurrent problems which may determine the future of the human society; depletion of the resources such as oil, and environmental damages associated with the resource use. Resources once utilized are ultimately transformed to differerent forms of wastes whereas some of them are accumulated in air and water, causing persi...

An equation adjoint to the luminance equation for describing the global illumination can be formulated using the notion of a surface potential to illuminate the region of interest This adjoint equation which we shall call as the potential equation is fundamental to the adjoint radiosity equation used to devise the importance driven radiosity algorithm In this paper we rst brie y derive the adjo...

Identifying and exploiting classes of nonconvex constraints whose feasible region is convex after branching can reduce the time to compute global solutions for nonlinear optimization problems. We develop techniques for identifying quadratic and nonlinear constraints whose feasible region can be represented as the union of a finite number of second-order cones, and we provide necessary and suffi...

In this paper, we will present a general pattern based on contractor programming for designing a global optimization solver. This approach allows to solve problems with a wide variety of constraints. The complexity and the performance of the algorithm rely on the construction of contractors which characterize the feasible region.

It is usually not known in advance whether a nonlinear set of constraints has zero, one, or multiple feasible regions. Further, if one or more feasible regions exist, their locations are usually unknown. We propose a method for exploring the variable space quickly using Constraint Consensus to identify promising areas that may contain a feasible region. Multiple Constraint Consensus solution po...

Through the installation of a monocular vision sensor on a target and shooting sequence images of the floor, combined with the characteristics of the sequence images, an indoor mobile visual localization algorithm based on Harris-SIFT is proposed. The algorithm is first to establish first-order DOG scale space of sequence images of the floor, to extract feature points in each layer images of DO...