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- W1575102914 abstract "There have been many studies of mathematical models of neural networks. However, there always arises a problem of determining their optimal structures due to the lack of prior information. We propose a procedure for the structure clarification of neurofuzzy GMDH model whose building blocks are represented by the radial basis functions network. The proposed method prunes the unnecessary links and units from the larger network to identify, as well as to clarify the network structure by minimizing the Minkowski norm of the derivatives of the building blocks." @default.
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- W1575102914 date "2002-11-27" @default.
- W1575102914 modified "2023-09-27" @default.
- W1575102914 title "Structural learning of neurofuzzy GMDH with Minkowski norm" @default.
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- W1575102914 doi "https://doi.org/10.1109/kes.1998.725899" @default.
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