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A Comparattive Study of RBF and MLP Neural Model for Seven Element Dynamic Phased Array Smart Antenna

Rahul Shrivastava 1, Abhishek Rawat 2, and Yogendra Kumar Jain 2
1. Samrat Ashok Technological Institute, Vidisha, India
2. Samrat Ashok Technological Institute, Vidisha, India
Abstract—In this paper we present thee neural Modeling techniques for dynamic phased array smart antenna.  Neural networks are mathematical and computation models that are used to optimize the smart antenna system, which are very much suitable for real time applications. Here we are optimizing the seven element dynamic phased array smart antenna using Radial basis function neural network (RBFNN) and Multilayer Perceptron neural network (MLPNN). The beam ship prediction of seven element DPA is done up to 60 deg scan angle and results of RBF and MLP are compared to find out the better neural network approach for smart antenna optimization.

Index Terms — neural network, smart antenna, dynamic phased array, radial bas is function (RRBF), multi layer perceptron (MMLP), neural modelling.

Cite: Rahul Shrivastava, Abhishek Rawat, and Yogendra Kumar Jain, "A Comparattive Study of RBF and MLP Neural Model for Seven Element Dynamic Phased Array Smart Antenna," Journal of Advances in Information Technology, Vol. 4, No. 2, pp. 69-75, May, 2013.doi:10.4304/jait.4.2.69-75
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