Based on discrete Hopfield neural network and wavelet transform character recognition

Character recognition is a branch of pattern recognition, the problem of noisy character image recognition is solved by discrete Hopfield neural network which is used as associative memory and the wavelet transform theory in the paper. The important original data is extracted from each character image, which is learning data of neural network. The character image is recognized by discrete Hopfield neural network and de-noising by the wavelet transform theory. Noisy samples of character recognition show that the method is accurate and efficient.