Design and optimization of microstrip patch antenna using artificial neural networks

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Abstract

In this paper a Neural Network model for the design of a Microstrip Patch Antenna for an Ultra-wideband frequency range is presented. The reduced ground size is used to enhance bandwidth in proposed design. The results obtained from the proposed method are compared with the results of EM simulation software and are found to be in good agreement. The advantage of the proposed method lies with the fact that the various parameters required for the design of a Microstrip Patch Antenna at a particular frequency of interest can be easily extracted without going into the rigorous time consuming, iterative design procedures using a costly software package. In the paper staircase patch design is considered for ultra-wideband matching of Antenna. The results obtained from artificial neural network when compared with experimental and simulation results, found satisfactory and also it is concluded that Radial Basis Function (RBF) network is more accurate and fast for the proposed design.

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Kaur, S., Khanna, R., Sahni, P., & Kumar, N. (2019). Design and optimization of microstrip patch antenna using artificial neural networks. International Journal of Innovative Technology and Exploring Engineering, 8(9 Special Issue), 611–616. https://doi.org/10.35940/ijitee.I1097.0789S19

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