Storage of correlated patterns in a perceptron
classification
❄️ cond-mat
keywords
patternsstoragealphacapacitycorrelatedperceptronagreementcalculate
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We calculate the storage capacity of a perceptron for correlated gaussian patterns. We find that the storage capacity $\alpha_c$ can be less than 2 if similar patterns are mapped onto different outputs and vice versa. As long as the patterns are in general position we obtain, in contrast to previous works, that $\alpha_c \geq 1$ in agreement with Cover's theorem. Numerical simulations confirm the results.
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