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**1 - 1**of**1**### N-Parity and its Solution with an Incremental Neural Network

"... Abstract. The N-dimensional parity problem is frequently a difficult classification task for Neural Networks. We found an expression for the minimum number of errors nf as function of N for this problem, performed by a perceptron. We verified this quantity experimentally for N 1;...; 15 using an op ..."

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Abstract. The N-dimensional parity problem is frequently a difficult classification task for Neural Networks. We found an expression for the minimum number of errors nf as function of N for this problem, performed by a perceptron. We verified this quantity experimentally for N 1;...; 15 using an optimal train perceptron. With a constructive approach we solved the full N-dimensional parity problem using a minimal feedforward neural network with a single hidden layer of h N units. Key words. classification tasks, minimerror, monoplan, parity problem, perceptrons, supervised learning