Uncertainty is inevitable in any reliability analysis of complex engineering systems due to uncertainties present in models, parameters of the model, phenomena and assumptions. Uncertainties at the component level are propagated to quantify uncertainty at the system level reliability. It is very important to identify all the uncertainties and treat them effectively to make reliability studies m...

We consider systems satisfying a matching condition which are functionally known up to a L2 measure of uncertainty. A modified L2 performance measure is given, and the performance of a class of model based adaptive controllers is studied. An upper perfor­ mance bound is derived in terms of the uncertainty measure and measures of the approximation error of the model. Asymptotic analyses of the b...

In many real-life situations, uncertainty can be naturally described as a combination of several components, components which are described by probabilistic, fuzzy, interval, etc. granules. In such situations, to process this uncertainty, it is often beneficial to take this granularity into account by processing these granules separately and then combining the results. In this paper, we show th...

Evaluating the Contribution of Uncertainty Management to a Fusion System Report Title By its very nature, fusion requires managing uncertainty. While uncertainty management is built into many standard low-level fusion algorithms, and the importance of uncertainty management is widely recognized at all levels of the JDL hierarchy, there is less commonality of approaches to uncertainty management...

We present an application of the measure of entropy for credal sets: as a branching criterion for constructing classification trees based on imprecise probabilities which are determined with the imprecise Dirichlet model. We also justify the use of upper entropy as a global uncertainty measure for credal sets and present a deduction of this measure. We have carried out several experiments in wh...

1.2 REMARK ON INTERPRETATIONS OF THE SHANNON ENTROPY There are standard ways to interpret the Shannon entropy. For instance, the quantity H(p) can be viewed as a measure of the amount of uncertainty in a random experiment described by the probability mass function p, or as a measure of the amount of information one gains by learning the value of such an experiment. Indeed, it is possible to sta...

This paper introduces a measure of uncertainty in the determination of the Shapley value, illustrates it with examples, and studies some of its properties. The introduced measure of uncertainty quantifies random variations in a player’s marginal contribution during the bargaining process. The measure is symmetric with respect to exchangeable substitutions in the players, equal to zero for dummy...

We introduce the fuzzy measure as a unifying structure for modeling knowledge about an uncertain variable. We show that a large class of well established types of uncertainty representation can be modeled in this framework. A measure of entropy associated with a fuzzy measure is introduced and its manifestation for different fuzzy measures is described. The problem of uncertain decision making ...

In this paper we address the problem of automatic arrangement of cameras in a 3D system to enhance the performance of depth acquisition procedure. Lacking ground truth or a priori information, a measure of uncertainty is required to assess the quality of reconstruction. The mathematical model of iso-disparity surfaces provides an efficient way to estimate the depth estimation uncertainty which ...