information entropy is introduced as penalty function and imposed to the backpropagation cost function. After training
more organized hidden unit activation patterns are obtained and few hidden units respond for each input sample. The scale of the neural network is reduced ther using the pruningmethod proposed in this paper
and its generalization performance and computational efficiency are improved atthe same time.