DISCRIMINATION BETWEEN MULTI-DIMENSIONAL MODELS USING DIFFERENCE DISTRIBUTIONS

摘要

Multi-dimensional models are discriminated, or distinguished, based on difference distribution histograms. One or more models having multiple attributes are received. Each model includes at least one non-spatial attribute, such as a physical, chemical, and/or dynamic attribute. A sampling function is selected and applied to the received models to generate difference distribution histograms that represent the models. Once multiple difference distribution histograms have been generated, two or more histograms are compared by applying a distribution test function to the histograms. Based on the comparison, the similarity of the models represented by the histograms may be determined.