1995 Volume 1995 Pages 137-142
The feedforward layered neural networks have been applied to the various classification problem and control. The generalization capability of neural networks is one of the most important properties to be acquired such that it depends on the numbers of units or weights. In this paper, we propose a fast and effective structural learning algorithm to construct a suitable structure for neural networks and apply to the pattern recognition problem for handwritten numerical characters. At every learning step evaluations for unknown data are computed , and decide the stopping time of learning (test set validation). Furthermore we consider the validity to select an optimal neural network model by information criteria.
