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We propose a new training method for a feedforward neural network having theactivation functions with the geometric contraction property. The methodconsists of constructing a new functional that is less nonlinear in comparisonwith the classical functional by removing the nonlinearity of the activationfunction from the output layer. We validate this new method by a series ofexperiments that show an improved learning speed and better classificationerror.

A New Training Method for Feedforward Neural Networks Based on Geometric Contraction Property of Activation Functions