Advantage analysis of sigmoid based RBF networks

By introducing an extra dimension to the inputs, sigmoid function can simulate the behavior of traditional RBF units. This paper introduces a sigmoid based RBF neuron and compares it with traditional RBF neuron. Neural networks composed of these neurons are trained with ErrCor algorithm on two classic experiments. Comparison results are presented to show advantages of the sigmoid based RBF model.

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