Neural Network Toolbox

Preprocessing and Postprocessing Functions

Preprocessing the network inputs and targets improves the efficiency of neural network training. Postprocessing enables detailed analysis of network performance. Neural Network Toolbox provides preprocessing and postprocessing functions and Simulink blocks that enable you to:

• Reduce the dimensions of the input vectors using principal component analysis
• Perform regression analysis between the network response and the corresponding targets
• Scale inputs and targets so that they fall in the range [-1,1]
• Normalize the mean and standard deviation of the training set
• Use automated data preprocessing and data division when creating your networks