Sequence transformations based on Tchebycheff approximations

Multi Agent Collaborative Search based on Tchebycheff decomposition

This paper presents a novel formulation ofMulti Agent Collaborative Search, for multi-objective optimization, based on Tchebycheff decomposition. A population of agents combines heuristics that aim at exploring the search space both globally (social moves) and in a neighborhood of each agent (individualistic moves). In this novel formulation the selection process is based on a combination of Tc...

Sil Transformations on Sequence Edges

Variational Approximations for Renormalization Group Transformations

A p p r o x i m a t e r ecur s ion re la t ions wh ich give uppe r a n d lower b o u n d s on the free energy are descr ibed. Op t i ma l ca lcula t ions o f the free energy can t hen be ob ta ined by t rea t ing pa r ame t e r s wi th in the r eno rma l i za t ion equat ions var ia t ional ly . As an example , a par t icular ly s imple lower b o u n d a p p r o x i m a t i o n which preserves ...

Fast Color Space Transformations Using Minimax Approximations

Color space transformations are frequently used in image processing, graphics, and visualization applications. In many cases, these transformations are complex nonlinear functions, which prohibits their use in time-critical applications. In this paper, we present a new approach called Minimax Approximations for Color-space Transformations (MACT). We demonstrate MACT on three commonly used color...

On a class of weak Tchebycheff systems

In this paper we study the approximation power, the existence of a normalized B-basis and the structure of a degree-raising process for spaces of the form span < 1, x, . . . , x, u(x), v(x) >, requiring suitable assumptions on the functions u and v. The results about degree raising are detailed for special spaces of this form which have been recently introduced in the area of CAGD.