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- W2134999009 abstract "We propose a hierarchical self-organizing neural network with adaptive architecture and simple topological organization. This network combines features of Fritzke's growing cell structures and traditional hierarchical clustering algorithms. The height and width of the tree structure depend on the user-specified level of error desired, and the weights in upper layers of the network do not change in later phases of the learning algorithm." @default.
- W2134999009 created "2016-06-24" @default.
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- W2134999009 date "2002-12-24" @default.
- W2134999009 modified "2023-09-24" @default.
- W2134999009 title "Hierarchical growing cell structures" @default.
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- W2134999009 doi "https://doi.org/10.1109/icnn.1996.549149" @default.
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