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arXiv · cond-mat/9611130

Learning by dilution in a Neural Network

B. Lopez·W. Kinzel
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Abstract

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.

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B. Lopez, W. Kinzel. 1996-11-18. Learning by dilution in a Neural Network. https://doi.org/10.1088/0305-4470%2F30%2F22%2F014

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