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In this paper, a comparison of the Choquet and Sugeno integrals is presented. The proposed methods enable the calculation of the Choquet and Sugeno integrals to combine multiple source of information with a degree of uncertainty. The methods are used to combine the modules output of a modular neural network for face recognition and a comparison is performed. In this paper, the focus is on aggregation...
In this paper, a comparison of the Choquet and Sugeno integrals is presented. The proposed methods enable the calculation of the Choquet and Sugeno integrals for combining multiple source of information with a degree of uncertainty. The methods are used to combine the modules output of a modular neural network for face recognition. In this paper, the focus is on aggregation operators that use measures...
In this paper a new method for response integration, based on the Choquet Integral with Interval type-2 Sugeno measures is presented. The Choquet integral is used as a method to integrate the outputs of the modules of the modular neural networks (MNN). The fuzzy Sugeno measures of the Choquet integral are represented by an interval type-2 fuzzy system. A database of faces was used to perform the preprocessing,...
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