Neural network having an optimized transfer function for each neuron

摘要

The characteristic data for determining the characteristics of the transfer functions (for example, sigmoid functions) of the neurons of the hidden layer and the output layer (the gradients of the sigmoid functions) of a neural network are learned and corrected in a manner similar to the correction of weighting data and threshold values. Since at least one characteristic data which determines the characteristics of the transfer function of each neuron is learned, the transfer function characteristics can be different for different neurons in the network independently of the problem and/or the number of neurons, and be optimum. Accordingly, a learning with high precision can be performed in a short time.