ON THE DYNAMIC PROBABILISTIC INVENTORY PROBLEMS WITH PIECEWISE COST FUNCTIONS WHICH MAY NOT BE PIECEWISE SMOOTH

Piecewise-smooth Refinable Functions

Univariate piecewise-smooth refinable functions (i.e., compactly supported solutions of the equation φ( 2 ) = ∑N k=0 ckφ(x−k)) are classified completely. Characterization of the structure of refinable splines leads to a simple convergence criterion for the subdivision schemes corresponding to such splines, and to explicit computation of the rate of convergence. This makes it possible to prove a...

Approximating Piecewise-Smooth Functions

We consider the possibility of using locally supported quasi-interpolation operators for the approximation of univariate non-smooth functions. In such a case one usually expects the rate of approximation to be lower than that of smooth functions. It is shown in this paper that prior knowledge of the type of ’singularity’ of the function can be used to regain the full approximation power of the ...

Network Design Problems with Piecewise Linear Cost Functions

ix Introduction xi On the General Framework and Piecewise Linear Cost Functions . . . . . . . . . . xi The Structure of the Thesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xiii 1 A Literature Review on Discrete Facility Location with Non-Standard Cost Functions 1 1.

Optimal Approximations by Piecewise Smooth Functions and Associated Variational Problems

The purpose of this paper is to introduce and study the most basic properties of three new variational problems which are suggested by applications to computer vision. In computer vision, a fundamental problem is to appropriately decompose the domain R of a function g ( x , y) of two variables. To explain this problem, we have to start by describing the physical situation whch produces images: ...

Spectral Reconstruction of Piecewise Smooth Functions