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首页> 外文期刊>Electromagnetics >Artificial Neural Networks for the Resonant Resistance Calculation of Electrically Thin and Thick Rectangular Microstrip Antennas
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Artificial Neural Networks for the Resonant Resistance Calculation of Electrically Thin and Thick Rectangular Microstrip Antennas

机译:人工神经网络用于电薄和厚矩形微带天线的谐振电阻计算

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摘要

A new method for calculating the resonant resistance of electrically thin and thick rectangular Microstrip patch antennas, based on the artificial neural networks, is presented. The four learning algorithms, the backpropagation, the delta-bar-delta, the quick propagation, and the extended-delta-bar-delta, are used to train the networks. The theoretical resonant resistance results obtained by using this method are in very good agreement with the experimental results available in the literature.
机译:提出了一种基于人工神经网络的矩形薄带电矩形薄板天线的谐振电阻计算方法。反向传播,delta-bar-delta,快速传播和扩展delta-bar-delta这四种学习算法用于训练网络。通过这种方法获得的理论谐振电阻结果与文献中提供的实验结果非常吻合。

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