Title :
Performance enhancement using nonlinear preprocessing
Author :
Chow, Tommy ; Leung, Chi-Tat
Author_Institution :
Dept. of Electron. Eng., City Polytech. of Hong Kong, Kowloon, Hong Kong
fDate :
7/1/1996 12:00:00 AM
Abstract :
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
Keywords :
feedforward neural nets; forecasting theory; function approximation; multilayer perceptrons; optimisation; prediction theory; time series; network optimization; nonlinear preprocessing; output performance; performance enhancement; time-series predictions; Data preprocessing; Dynamic range; Ear; Function approximation; Humans; Neural networks; Neurons; Optimization methods; Redundancy; Testing;
Journal_Title :
Neural Networks, IEEE Transactions on