Training a perceptron by a bit sequence: Storage capacity
classification
❄️ cond-mat
keywords
capacityperceptronsequencestoragealphaanalysisbitsclassification
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A perceptron is trained by a random bit sequence. In comparison to the corresponding classification problem, the storage capacity decreases to alpha_c=1.70\pm 0.02 due to correlations between input and output bits. The numerical results are supported by a signal to noise analysis of Hebbian weights.
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