Investigation of Switching Behavior of Microstrip Triangular Patch Antenna through Neural Network
||International Journal of Computer Trends and Technology (IJCTT)||
|© 2017 by IJCTT Journal|
|Year of Publication : 2017|
|Authors : N K Saxena, R.K. Verma, N. Kumar, P.K.S. Pourush1|
|DOI : 10.14445/22312803/IJCTT-V48P124|
N K Saxena1, R.K. Verma, N. Kumar, P.K.S. Pourush "Investigation of Switching Behavior of Microstrip Triangular Patch Antenna through Neural Network". International Journal of Computer Trends and Technology (IJCTT) V48(3):118-122, June 2017. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.
Switching behavior of microstrip equilateral triangular patch antenna printed on ferrite substrate is investigated using general artificial neural network (ANN) analysis. Using ferrite as substrate with applied external magnetic field perpendicularly, microstrip antennas offered switchable behavior due to negative permeability constant which causes extraordinary wave decaying or attenuating. In this communication the study of negative permeability and external magnetic field which are only responsible for this switching behavior is done with help of ANN. Both synthesis and analysis are mainly focused on the switchabilty of antenna. In this work Radial Basis Function (RBF) networks is used in ANN models. Synthesis is defined as the forward side and then analysis as the reverse side of the problem. Here the analysis is considered as a final stage of the design procedure, therefore the parameters of the analysis ANN network are determined by the data obtained reversing the input-output data of the synthesis network. In the RBF network, the spread value was chosen as 0.01, which gives the best accuracy. RBF is trained with 100 samples but tested only for particular cutoff 15 samples.
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Microstrip antennas, switchability, ferrite material, artificial neural networks, reverse modeling.