A selection of unfolding methods commonly used in High Energy Physics is compared. The methods discussed here are: bin-by-bin correction factors, matrix inversion, template fit, Tikhonov regularisation and two examples of iterative methods. Two procedures to choose the strength of the regularisation are tested, namely the L-curve scan and a scan of global correlation coefficients. The advantage...

We show that X-ray scattering techniques can be used for the assessment of individual layer thicknesses inside complicated semi-conductor heterostructures dedicated to the opto-electronic domain. To this end, we propose methods to overcome two main drawbacks coming from: (1) the complexity of the X-ray profiles and, hence the difficulty to use model-dependent tools such as fitting procedures an...

In the 1980s, a version of a marginal problem considered in this paper was connected, with the necessity to cope with a task of knowledge integration in probabilistic expert systems. In practical situations, marginal distributions representing pieces of local knowledge are often inconsistent. The present paper introduces an interval-valued solution, which always exists, of a marginal problem ev...

This paper defines a distance function that measures the dissimilarity between planar geometric figures formed with straight lines. This function can in turn be used in partial matching of different geometric figures. For a given pair of geometric figures that are graphically isomorphic, one function measures the angular dissimilarity and another function measures the edge length disproportiona...

We applied hyperspectral imaging to measure spatially-resolved diffuse reflectance spectra in the visible range and an iterative inversion method based on forward Monte Carlo modeling to quantify optical properties of two-layered tissue models. We validated the inversion method using spectra experimentally measured from liquid tissue mimicking phantoms with known optical properties. Results of ...

The iterative proportional fitting procedure (IPF-P) is an algorithm to compute approximately probability measures with prescribed marginals. We propose two extensions of the IPF-P, called conditional iterative proportional fitting procedures (CIPF-P), so that, additionally, given conditional distributions are taken into account. This modification is carried out by using the geometrical interpr...

A novel high-speed fluorescence lifetime imaging (FLIM) analysis method based on artificial neural networks (ANN) has been proposed. In terms of image generation, the proposed ANN-FLIM method does not require iterative searching procedures or initial conditions, and it can generate lifetime images at least 180-fold faster than conventional least squares curve-fitting software tools. The advanta...

Simple algorithms for probabilistic inversion are proposed, based on iterative sample re-weighting. One of these, iterative proportional fitting (IP F), dates from the 1930's and has been studied extensively with regard to contingency tables. A new algorithm is shown to converge even when IP F is infeasible.

We demonstrate, for the first time, successful S-matrix to potential inversion for spin one projectiles with non-diagonal S j ll ′ yielding a T R interaction. The method is a generalization of the iterative-perturbative, IP, method. We present a test case indicating the degree of uniqueness of the potential. The method is adapted, using established procedures, into direct observable to potentia...

Unshifted and shifted multiscaling functions are used as mathematical models for curve fitting of irregularly sampled data. This pre-processing procedure combined with multiwavelet neural networks for data-adaptive curve fitting is shown to perform well in the case of high resolution. In the case of low resolution it is more accurate than numerical integration and cheaper than matrix inversion....