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基于小波变换的特征信息的提取和神经网络的自学习能力研究了薄膜场发射的特性 ,结合阴极薄膜场发射的特点 ,建立了薄膜场发射开启电场的小波神经网络预测模型 .并用金刚石薄膜场发射开启电场数据进行了验证 ,结果表明该模型预测的相对误差小于 1 30 % .这一结论预示着小波神经网络是一种研究薄膜场发射特性的方法 .
Based on the feature extraction of wavelet transform and the self-learning ability of neural network, the characteristics of thin film field emission are studied. Combined with the characteristics of cathode thin film field emission, a wavelet neural network prediction model of thin film field emission electric field is established. The results of the model show that the relative error of this model is less than 130%, which indicates that the wavelet neural network is a method to study the field emission characteristics of thin films.