AN ADAPTIVE NEURAL-NETWORK - APPLICATION TO CHARACTER-RECOGNITION ON X-RAY-FILMS

In this paper, we propose a hyper-spherical surface interactive interc onnections (HSII) learning method for category learning. This method g enerates the number of hidden units based on the same algorithm as a r estricted coulomb energy (RCE) network and updates weights and biases by the error backpropagation algorithm (EBP). The HSII method adapts d esired features of RCE and EBP methods. The HSII (1) optimizes the net work size, (2) learns samples quickly, and (3) has well generalized pe rformance on untrained inputs. We demonstrate application of the HSII to recognition of characters on X-ray films. We also compared performa nces of the HSII with the RCE using receiver operating characteristic analysis.