ELLIPTIC BASIS FUNCTION PROBABILISTIC NEURAL NETEORK FOR CHARACTER RECOGNITION
用于字符识别的椭圆基函数概率神经网络

An Elliptic Basis Function Probabilistic Neural Network (EBPNN)model for character recognition with noise was proposed, which uses selective attentional parameters extracted from statistic features of characters as elliptic basis function parameters. EBPNN is not only used for binary pattern recognition, but also for continuous pattern recognition. The experiments show that the recognition rate of EBPNN is better than that of other neural networks, especially under the noise circumstances.