scholarly journals Design of rectangular microstrip antenna with rectangular aperture in the ground plane using artificial neural networks

2015 ◽  
Author(s):  
Siham Benkouda ◽  
Tarek Fortaki ◽  
Sami Bedra ◽  
Abdelkrim Belhedri
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Microstrip Antenna ◽  
Ground Plane ◽  
Rectangular Aperture ◽  
Artificial Neural ◽  
Rectangular Microstrip Antenna

Design of a wideband microstrip antenna and the use of artificial neural networks in parameter calculation

2005 ◽  
Vol 47 (3) ◽  
pp. 60-65 ◽  
Author(s):  
D.K. Neog ◽  
S.S. Pattnaik ◽  
D.C. Panda ◽  
S. Devi ◽  
B. Khuntia ◽  
...  
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Microstrip Antenna ◽  
Parameter Calculation ◽  
Artificial Neural

scholarly journals Adaptive Forming of the Beam Pattern of Microstrip Antenna with the Use of an Artificial Neural Network

2012 ◽  
Vol 2012 ◽  
pp. 1-13 ◽  
Author(s):  
Janusz Dudczyk ◽  
Adam Kawalec
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Artificial Neural Networks ◽  
Microstrip Antenna ◽  
Microstrip Antennas ◽  
Emission Source ◽  
Application Systems ◽  
Artificial Neural ◽  
Selection Of ◽  
Made In

Microstrip antenna has been recently one of the most innovative fields of antenna techniques. The main advantage of such an antenna is the simplicity of its production, little weight, a narrow profile, and easiness of integration of the radiating elements with the net of generators power systems. As a result of using arrays consisting of microstrip antennas; it is possible to decrease the size and weight and also to reduce the costs of components production as well as whole application systems. This paper presents possibilities of using artificial neural networks (ANNs) in the process of forming a beam from radiating complex microstrip antenna. Algorithms which base on artificial neural networks use high parallelism of actions which results in considerable acceleration of the process of forming the antenna pattern. The appropriate selection of learning constants makes it possible to get theoretically a solution which will be close to the real time. This paper presents the training neural network algorithm with the selection of optimal network structure. The analysis above was made in case of following the emission source, setting to zero the pattern of direction of expecting interference, and following emission source compared with two constant interferences. Computer simulation was made in MATLAB environment on the basis of Flex Tool, a programme which creates artificial neural networks.

Pole discontinuity removal using artificial neural networks for microstrip antenna design

2011 ◽  
Vol 98 (12) ◽  
pp. 1711-1720 ◽  
Author(s):  
Sanjeev Kulshrestha ◽  
Deven J. Chheda ◽  
S.B. Chakrabarty ◽  
Rajeev Jyoti ◽  
S.B. Sharma
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Microstrip Antenna ◽  
Antenna Design ◽  
Artificial Neural
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