Active learning algorithm of neural network

In training a neural network one usually has to create a set of learning samples, which is a number of sample problem and desired output pairs. However sometimes it is difficult to provide an effective learning sample especially when the structure of the pattern space is complex. In this paper the authors introduce an algorithm that can actively self produce the effective sample pattern while advancing the learning process.