Wavelet neural networks model on threshold electric field of field emission from thin films
薄膜场发射开启电场的小波神经网络预测模型研究

In this paper, characteristics of field emission from thin films have been studied based on extracting features of wavelet transforms from experimental data and neural networks self-learning,and the forecasting model of wavelet neural networks in combination with the characteristics of cold cathode materials has been established. The data of diamond thin film on threshold electric field in field emission is used to test this model, and the results show that the absolute value of the relative error of the model is within 1.30%. This result implies that the wavelet neural network is a useful tool for studying characteristics of field emission from thin films.