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Error-Gated Hebbian Rule: A Local Learning Rule for Principal and Independent Component Analysis
We developed a biologically plausible unsupervised learning algorithm, error-gated Hebbian rule (EGHR)-β, that performs principal component analysis (PCA) and independent component analysis (ICA) in a single-layer feedforward neural network. If parameter β = 1, it can extract the subspace that major...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Nature Publishing Group UK
2018
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5789861/ https://www.ncbi.nlm.nih.gov/pubmed/29382868 http://dx.doi.org/10.1038/s41598-018-20082-0 |