A Neural Network Algorithm for Large Scale Pattern Recognition Problems

Many practical pattern recognition problems, such as recognition of handwritten Chinese characters belong to the pattern recognition problems of large scale. Now conventional ANN (artificial neural network) algorithms cannot solve this set of problems efficiently. In this paper, a neural network algorithm based on the sphere neighborhood model is introduced, aiming at enhancing the neural network's ability to solve the pattern recognition problems of large scale. The performance of the algorithm is tested with the handwritten Chinese character recognition problem. Experimental results show that the proposed algorithm is competent and has well prospects to this set of problems.