Information fractals for evidential pattern classification

Proposed is a novel model of belief functions based on fractal theory. The model is first justified in qualitative, intuitive terms, then formally defined. Also, the application of the model to the design of an evidential classifier is described. The proposed classification scheme is illustrated by a simple example dealing with robot sensing. The approach followed is motivated by applications to the design of intelligent systems, such as sensor-based dexterous manipulators, that must operate in unstructured, highly uncertain environments. Sensory data are assumed to be (1) incomplete and (2) gathered at multiple levels of resolution.<
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