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In this paper, we propose a new method to generate a continuous belief functions from a multimodal probability distribution function defined over a continuous domain. We generalize Smets' approach in the sense that focal elements of the resulting continuous belief function can be disjoint sets of the extended real space of dimension . We then derive the continuous belief function from multimodal probability density functions using the least commitment principle. We illustrate the approach on two...
In this paper, we propose a new method to generate a continuous
belief functions from a multimodal probability distribution function defined
over a continuous domain. We generalize Smets' approach in the sense that
focal elements of the resulting continuous belief function can be disjoint sets
of the extended real space of dimension . We then derive the continuous
belief function from multimodal probability density functions using the least
commitment principle. We illustrate the approach on two...
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