In many real-life data processing situations, we only know the values of the inputs with interval uncertainty. In such situations, it is necessary to take this interval uncertainty into account when processing data. Most existing methods for dealing with interval uncertainty are based on interval arithmetic, i.e., on the formulas that describe the range of possible values of the result of an arithmetic operation when the inputs are known with interval uncertainty. For most arithmetic operations, this range is also an interval, but for division, the range is sometimes a disjoint union of two semi-infinite intervals. It is therefore desirable to extend the formulas of interval arithmetic to the case when one or both inputs is such a union. Th...
When we have only interval ranges [xi-,xi+] of sample values x1,...,xn, what is the interval [V-,V+]...
When we usually process data, we, in effect, implicitly assume that we know the exact values of all ...
Linear systems represent the computational kernel of many models that describe problems arising in t...
In many practical applications, we are interested in the values of the quantities y1, ..., ym which ...
Interval arithmetic is the mathematical structure, which for real intervals defines operations analo...
It is well known that interval computations are very important, both by themselves (as a method for ...
AbstractIt is well known that interval computations are very important, both by themselves (as a met...
In many real-life situations, we are interested in the value of a physical quantity y that is diffic...
In many practical situations, we only know the upper bound D on the (absolute value of the) measurem...
Brânzei R, Dimitrov D, Pickl S, Tijs S. How to cope with division problems under interval uncertaint...
We are concerned with interval constraints: solving constraints among real unknowns in such a way th...
In many practical situations, the only information that we have about measurement errors is the uppe...
: This paper presents an approach to solving the long-standing dependency problem in interval arithm...
In many practical situations, the quantity of interest is difficult to measure directly. In such sit...
In many real-life situations, we are interested in the physical quantities that are difficult or eve...
When we have only interval ranges [xi-,xi+] of sample values x1,...,xn, what is the interval [V-,V+]...
When we usually process data, we, in effect, implicitly assume that we know the exact values of all ...
Linear systems represent the computational kernel of many models that describe problems arising in t...
In many practical applications, we are interested in the values of the quantities y1, ..., ym which ...
Interval arithmetic is the mathematical structure, which for real intervals defines operations analo...
It is well known that interval computations are very important, both by themselves (as a method for ...
AbstractIt is well known that interval computations are very important, both by themselves (as a met...
In many real-life situations, we are interested in the value of a physical quantity y that is diffic...
In many practical situations, we only know the upper bound D on the (absolute value of the) measurem...
Brânzei R, Dimitrov D, Pickl S, Tijs S. How to cope with division problems under interval uncertaint...
We are concerned with interval constraints: solving constraints among real unknowns in such a way th...
In many practical situations, the only information that we have about measurement errors is the uppe...
: This paper presents an approach to solving the long-standing dependency problem in interval arithm...
In many practical situations, the quantity of interest is difficult to measure directly. In such sit...
In many real-life situations, we are interested in the physical quantities that are difficult or eve...
When we have only interval ranges [xi-,xi+] of sample values x1,...,xn, what is the interval [V-,V+]...
When we usually process data, we, in effect, implicitly assume that we know the exact values of all ...
Linear systems represent the computational kernel of many models that describe problems arising in t...