Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
405173 | Knowledge-Based Systems | 2013 | 8 Pages |
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
Authors
Hamzeh Agahi, Adel Mohammadpour, Radko Mesiar, S. Mansour Vaezpour,