Principal component analysis of fuzzy data using autoassociative neural networks.
This paper describes an extension of principal component analysis (PCA) allowing the extraction of a limited number of relevant features from high-dimensional fuzzy data. Our approach exploits the ability of linear autoassociative neural networks to perform information compression in just the same w...
| Publicat a: | IEEE Transactions on fuzzy systems 12, 3 (2004). |
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| Autor principal: | |
| Format: | Article |
| Idioma: | English |
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