Application of neural networks to analyses of nonlinearly loaded antenna arrays including mutual coupling effects

Kun Chou Lee, Tsung Nan Lin

研究成果: Article同行評審

26 引文 斯高帕斯(Scopus)

摘要

In this paper, radial basis functions based neural networks (RBF-NN) are applied to the scattering of finite and infinite nonlinearly loaded antenna arrays including mutual coupling effects. The nodes in the input layer represent the parameters of antenna arrays or magnitudes of incident fields. There exist some nodes in the hidden layer for nonlinear mapping. The nodes in the output layer represent the magnitude of voltage at the input terminals of antennas at different harmonic frequencies. Numerical examples show that the scattering responses predicted by the trained RBF-NN models are very consistent with those calculated from the harmonic balance techniques. The trained RBF-NN models for the scattering of nonlinearly loaded antenna arrays are very efficient and the array mutual coupling effects are included.

原文English
頁(從 - 到)1126-1132
頁數7
期刊IEEE Transactions on Antennas and Propagation
53
發行號3
DOIs
出版狀態Published - 2005 3月

All Science Journal Classification (ASJC) codes

  • 電氣與電子工程

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