中文摘要：

针对内部结构不详、器件参数未知的复杂电子电路电磁脉冲响应建模这一难点问题，笔者采用NARX神经网络建立动力学模型，并提出了采用正弦波扫频信号及其电路响应作为训练数据的方法，同时给出了NARX神经网络建模的理论基础及设计步骤，证明了集总参数电路响应模型可用NARX神经网络所建立的动力学模型替代，从而得到了基于数据的电子电路电磁脉冲响应建模方法。运用ADS软件完成滤波器电路及射频放大电路的设计与仿真。建ANARX神经网络模型并得到了较好的预测效果，验证了该方法适用于集总参数电路的电磁脉冲响应预测。对NARX神经网络的缺陷进行简要分析，并提出使用遗传算法优化网络参数和使用支持向量机或极限学习机替代NARX神经网络中前馈神经网络部分的改进方法，为后续研究工作指引方向。

英文摘要：

To build electromagnetic pulse response models for complex electronic circuits without knowing their internal structure and parameters, a dynamic model based on NARX neural network is established, and the sine wave sweep frequency signal and the circuit response are taken as training data. The theoretical basis and design steps of the modelling with NARX neural network are proposed, and it is proved that the response model of lumped parameter circuit can be replaced by the present dynamic model. The filter circuit and radio-frequency amplifier circuit are designed and simulated by ADS software. The satisfactory simulation results indicate that the proposed method can be applied to predicting the electromagnetic pulse response of lumped parameter circuit. In addition, the defects of NARX neural network are analyzed, and the corresponding improvement method is suggested by using genetic algorithm to optimize the network parameters and by using support vector machine （SVM） or extreme learning machine （ELM） to take the place of the feedforward neural network section in NARX neural network.