Article ID Journal Published Year Pages File Type
405173 Knowledge-Based Systems 2013 8 Pages PDF
Abstract

Integral inequalities play important roles in classical probability and measure theory. Universal integrals provide a useful tool in many problems in engineering and non-linear systems where the aggregation of data is required. We discuss several inequalities including Hardy, Berwald, Barnes–Godunova–Levin, Markov and Chebyshev for a monotone measure-based universal integral. Some recent results are obtained as corollaries. Finally, we provide some applications of our results in intelligent decision support systems, estimation and information fusion.

Related Topics
Physical Sciences and Engineering Computer Science Artificial Intelligence
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