Efficient use of training data in the n-tuple recognition method

A simple technique is presented for improving the robustness of the n-tuple recognition method against inauspicious choices of architectural parameters, guarding against the saturation problem, and improving the use of small data sets. Experiments are reported which confirm that the method significantly improves performance and reduces saturation in character recognition problems.