Neurocomputational Model for Analysis Microstrip Antennas for Wireless Communication

Jagtar S. Sivian, Amarpartap S. Pharwaha, and Tara S. Kamal


Microstrip, Antenna, Neurocomputaional, Back-propagation, Design parameter


Modern wireless and mobile communication systems requires antenna which should have light weight, low profile, low cost, and easy to be integrated with rf devices .this demand is completed by microstrip antennas. In this paper rectangular microstrip patch antenna is designed using ie3d software and the frequency at which different sizes of rectangular microstrip antennas should operate is estimated by using neurocomputational approach. A comparative evaluation of different variants of back-propagation training algorithm for estimating the resonant frequency of rectangular microstrip antenna using artificial neural network (ann) with particular attention paid to the speed of computation and accuracy.

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