Research on Pattern Recognition Method of Online English Education Based on Feature Self Learning

Aiming at the problem of low accuracy of pattern recognition in online English education, a pattern recognition method based on feature self-learning is proposed. Using feature self-learning algorithm and convolution neural network, the feature extraction model of online English education is established, and the basic features and depth features of online English education are extracted. Z transform is introduced to standardize the feature data set of English online education, and Laplace gradient function is used to clean the wrong and missing data of English online education features. The fuzzy logic theory is used to infer the important parameters of English online education. According to the determined characteristics and parameter values of English online education, the difference between the characteristics and parameter values of English online education is calculated, and the mode of English online education is identified. The experimental results show that: This study of English online education pattern recognition method, can identify all the patterns of English online education, and English online education pattern recognition accuracy is high.