非对称带状线间隙的人工神经网络模型

Artificial Neural Network Models for Gap Discon Discontinuities in Asymmetrical Striplines

采用多层感知器神经网络模型模拟非对称带状线中的间隙不连续性。由时域有限差分方法计算得到一系列按全因素试验设计采样的训练数据，利用这些训练数据训练产生多层感知器神经网络模型，训练结束时存储工作空间。并采用未参加训练的ＦＤＴＤ

Gap discontinuities appear in many stripline circuits, such as the multilayer microwave monolithic ICs and the interconnect systems in high speed digital circuits. In this paper, a multilayer perceptron neural network(MLPNN) is used to model the gap discontinuities in stripline circuits. The MLPNN is electromagnetically developed with a set of training data that are produced by the full wave finite difference time domain method. The full factor design of experiments is used for determining the size of the training data.