When upper probabilities are possibility measures
Fuzzy Sets and Systems - Special issue dedicated to Professor Claude Ponsard
Digital Signal Filtering, Analysis and Restoration (Telecommunications Series)
Digital Signal Filtering, Analysis and Restoration (Telecommunications Series)
On the granularity of summative kernels
Fuzzy Sets and Systems
Unifying practical uncertainty representations -- I: Generalized p-boxes
International Journal of Approximate Reasoning
Unifying practical uncertainty representations. II: Clouds
International Journal of Approximate Reasoning
Practical representations of incomplete probabilistic knowledge
Computational Statistics & Data Analysis
Probability boxes on totally preordered spaces for multivariate modelling
International Journal of Approximate Reasoning
| Hi-index | 0.00 |
Selecting a particular summative (i.e., formally equivalent to a probability distribution) kernel when filtering a digital signal can be a difficult task. To circumvent this difficulty, one can work with maxitive (i.e., formally equivalent to a possibility distribution) kernels. These kernels allow to consider at once sets of summative kernels with upper bounded bandwith. They also allow to perform a robustness analysis without additional computational cost. However, one of the drawbacks of filtering with maxitive kernels is sometimes an overly imprecise output, due to the limited expressiveness of summative kernels. We propose to use a new uncertainty representation, namely cloud, to achieve a compromise between summative and maxitive kernels, avoiding some of their respective shortcomings. The proposal is then experimented on a simulated signal.