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• W2024186318 abstract "In this paper, a novel function approximation approach based on a combination of conventional Neural Networks and tile coding approximators is proposed. The proposed approach can maintain the desired features of both approaches whiles eliminates the deficiencies of each method. The combination will reduce the sharpness of tile coding. It will also provide an easy way to adjust the accuracy/complexity of the approximation according to the function being approximated (adaptive tiling) and the subspace used on. In this algorithm, it is possible to construct the approximator with specified and various approximation accuracies in different subspaces. This feature enables us to allocate an arbitrary accuracy/complexity wherever a more accurate approximation is needed. Finally simulation studies are presented to show the efficiency of and applicability of the proposed approach." @default.
• W2024186318 created "2016-06-24" @default.
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• W2024186318 date "2011-10-01" @default.
• W2024186318 modified "2023-09-22" @default.
• W2024186318 title "Adaptive tiled Neural Networks" @default.
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• W2024186318 doi "https://doi.org/10.1109/icsmc.2011.6084059" @default.
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