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Biologically Plausible Online Principal Component Analysis Without Recurrent Neural Dynamics
[article]
2018
arXiv
pre-print
Artificial neural networks that learn to perform Principal Component Analysis (PCA) and related tasks using strictly local learning rules have been previously derived based on the principle of similarity matching: similar pairs of inputs should map to similar pairs of outputs. However, the operation of these networks (and of similar networks) requires a fixed-point iteration to determine the output corresponding to a given input, which means that dynamics must operate on a faster time scale
arXiv:1810.06966v2
fatcat:ul7clkmgtrhxtll7mk4wpcg4gm