Design and Analysis of Microstrip Line Feed Toppled T Shaped Microstrip Patch Antenna using Radial Basis Function Neural Network

  • Aneesh, Mohammad ;
  • Kumar, Anil ;
  • Singh, Ashish ;
  • Kamakshi, Kamakshi ;
  • Ansari, J.A.
  • Received : 2014.05.20
  • Accepted : 2014.10.20
  • Published : 2015.03.01


This paper deals with the design of a microstrip line feed toppled T shaped microstrip patch antenna that gives dualband characteristics at 4 GHz and 6.73 GHz respectively. The simulation of proposed antenna geometry has been performed using method of moment based IE3D simulation software. A radial basis function neural network (RBFNN) is used for the estimation of bandwidth for dualband at 4 GHz and 6.73 GHz respectively. In RBFNN model, antenna parameters such as dielectric constant, height of substrate, and width are used as input and bandwidth of first and second band is considered as output of the network. To validate the RBFNN output, an antenna has been physically fabricated on glass epoxy substrate. The fabricated antenna can be utilized in S and C bands applications. RBFNN results are found in close agreement with simulated and experimental results.


Artificial neural network;Microstrip patch antenna;Radial basis function;Bandwidth


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