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Learning by Dilution in a Neural Network Learning by Dilution in a Neural Network

A perceptron with N random weights can store of the order of N patterns by removing a fraction of the weights without changing their strengths. The critical storage capacity as a function of the concentration of the remaining bonds for random outputs and for outputs given by a teacher perceptron is calculated. A simple Hebb{ like dilution algorithm is presented which in the teacher case reaches the optimal generalization ability.