The complexity of Boolean functions
The complexity of Boolean functions
What size net gives valid generalization?
Neural Computation
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IEEE Transactions on Computers - Special issue on artificial neural networks
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Neural Computation
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IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
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ICANN '08 Proceedings of the 18th international conference on Artificial Neural Networks, Part II
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The relationship between generalization ability, neural network size and function complexity have been analyzed in this work. The dependence of the generalization process on the complexity of the function implemented by neural architecture is studied using a recently introduced measure for the complexity of the Boolean functions. Furthermore an association rule discovery (ARD) technique was used to find associations among subsets of items in the whole set of simulations results. The main result of the paper is that for a set of quasi-random generated Boolean functions it is found that large neural networks generalize better on high complexity functions in comparison to smaller ones, which performs better in low and medium complexity functions.