Hankel transform domain analysis of dual-frequency stacked circular microstrip antennas

1997 ◽  
Vol 2 (4) ◽  
pp. 443-447
Author(s):  
Huang Jingxi ◽  
Fan Zhibo
Keyword(s):  
Domain Analysis ◽  
Hankel Transform ◽  
Microstrip Antennas ◽  
Transform Domain ◽  
Dual Frequency

scholarly journals Prediction of Slot Shape and Slot Size for Improving the Performance of Microstrip Antennas Using Knowledge-Based Neural Networks

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Taimoor Khan ◽  
Asok De
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Prior Knowledge ◽  
Neural Model ◽  
Microstrip Antennas ◽  
Performance Parameters ◽  
Dual Frequency ◽  
Knowledge Based ◽  
Slot Size ◽  
Good Agreement

In the last decade, artificial neural networks have become very popular techniques for computing different performance parameters of microstrip antennas. The proposed work illustrates a knowledge-based neural networks model for predicting the appropriate shape and accurate size of the slot introduced on the radiating patch for achieving desired level of resonance, gain, directivity, antenna efficiency, and radiation efficiency for dual-frequency operation. By incorporating prior knowledge in neural model, the number of required training patterns is drastically reduced. Further, the neural model incorporated with prior knowledge can be used for predicting response in extrapolation region beyond the training patterns region. For validation, a prototype is also fabricated and its performance parameters are measured. A very good agreement is attained between measured, simulated, and predicted results.

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