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- W1489114182 abstract "In this paper, we propose a new self-growing hierarchical principal components analysis self-organizing neural networks model. This dynamically growing model expands the ability of the PCASOM model that represents the hierarchical structure of the input data. It overcomes the shortcoming of the PCASOM model in which the fixed the network architecture must be defined prior to training. Experiment results showed that the proposed model has better performance in the tradition clustering problem." @default.
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- W1489114182 date "2006-01-01" @default.
- W1489114182 modified "2023-09-27" @default.
- W1489114182 title "Growing Hierarchical Principal Components Analysis Self-Organizing Map" @default.
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- W1489114182 doi "https://doi.org/10.1007/11759966_103" @default.
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