Uncertainty Measures for Continuous-Valued Information Systems

Entropy measures and granularity measures for set-valued information systems

Set-valued information systems are generalized models of single-valued information systems. In this paper, we propose two new relations for set-valued information systems. Based on these two relations, the concepts of knowledge information entropy, knowledge rough entropy, knowledge granulation and knowledge granularity measure are defined in set-valued information systems, and some properties ...

Measures of Uncertainty and Information

This contribution overviews the approaches results and history of attempts at measuring uncertainty and information in the various theories of imprecise prob abilities The main focus however is on the theory of belief functions or the Dempster Shafer theory and the possibility theory as most of the devel opment so far has happened there Due to the limited space I am focusing on the main ideas a...

Egoroff Theorem for Operator-Valued Measures in Locally Convex Cones

In this paper, we define the almost uniform convergence and the almost everywhere convergence for cone-valued functions with respect to an operator valued measure. We prove the Egoroff theorem for Pvalued functions and operator valued measure θ : R → L(P, Q), where R is a σ-ring of subsets of X≠ ∅, (P, V) is a quasi-full locally convex cone and (Q, W) is a locally ...

Information Entropy and Information Granulation-based Uncertainty Measures in Incomplete Information Systems

In this paper, concepts of information entropy and information granulation-based uncertainty measures are introduced in incomplete information/decision systems, and based on maximal consistent block technique, some variants of information entropy and information granulation are presented to measure the discernibility ability of an incomplete information system. Then, some important properties o...

Information Measures for Multisensor Systems