天线方向性图的神经网络建模

Modeling the Radiation Patterns of Antennas with Neural Networks

为了探索多层前传神经网络模型对天线方向性图的建模能力与特性 ,用多层前传神经网络模型对对称振子天线及二元对称振子天线阵的方向性图进行建模试验 .实验表明 ,多层前传神经网络模型可以有效地对天线的方向性图进行建模 ,可用于天线的计算机辅助设计 (CAD) .

In order to investigate the ability and the characteristic of multi_layer feed forward neural networks in modeling the radiation pattern of antennas, the multi_layer feed forward neural networks are used to model the radiation patterns of a dipole antenna and a two element array of dipole antennas. The experiments show that the multi_layer feed forward neural networks can model the radiation patterns of the antennas efficiently and are suitable for the CAD of antennas.