Parametric Optimization of Wired Bowtie Antenna Using Artificial Neural Networks
نویسندگان
چکیده
In this paper a novel technique is proposed to design Bowtie using Artificial Neural Networks (ANN). ANN models are developed to calculate the antenna Gain for the given frequency and dimensions. ANN is designed using Feed forward back propagation neural network (FFBPNN) architecture and trained by LevenbergMarquardt training algorithm. ANN can be trained to provide the best and worst case precisions of an antenna design problem defined by these parameters. We have trained the network using 400 MHz frequency with different values of length and width. The results obtained by FFBPNN are compared with the results of 4NEC-2 simulation and the errors founds by these are of very low order 5.4266E-06.
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