Wednesday 20th of September 2017
 

Efficient Computation of Resonant Frequency of Rectangular Microstrip Antenna using a Neural Network Model with Two Stage Training


Guru Pyari Jangid, Gur Mauj Saran Srivastava and Ashok Jangid

Artificial neural networks (ANNs) with two stage training have been proposed for efficient computation of resonant frequency of rectangular microstrip antenna. In the proposed approach in first stage the ANN model trained with empirical relation of resonant frequency with structural and substrate parameters of antenna then in second stage the model has been trained with the actual experimental data. The proposed approach has been validated using experimental published data and compared with results of other models published in different research papers. The result shows that the proposed approach is more accurate than the models developed using experimental data only. The results of the two stage training are in very good agreement with the measurements, and better accuracy than other ANN models developed using experimental data only.

Keywords: Artificial neural networks (ANNs), computer aided design (CAD), learning algorithms, microstrip antenna, microwave device modeling.

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ABOUT THE AUTHORS

Guru Pyari Jangid
Department of Physics and Computer Science Dayalbagh Educational Institute (Deemed University) Dayalbagh Agra 282005, INDIA

Gur Mauj Saran Srivastava
Department of Physics and Computer Science Dayalbagh Educational Institute (Deemed University) Dayalbagh Agra 282005, INDIA

Ashok Jangid
Department of Physics and Computer Science Dayalbagh Educational Institute (Deemed University) Dayalbagh Agra 282005, INDIA


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