Performance enhancement using nonlinear preprocessing
Tommy W. S. Chow, Chi-Tat Leung · IEEE Transactions on Neural Networks · 1996
Describes a nonlinear preprocessing method to enhance the output performance of a network. The introduction of the nonlinear preprocessing method redistributes the distributions of input and output vectors, and makes the input and output variables more "orthogonal" that results in facilitating the network optimization. In some of the examples, this nonlinear preprocessing technique enables test set error to be reduced by a magnitude of 98%. Three applications of time-series predictions applied to evaluate the performance of the proposed method are presented.