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Title: Artificial Neural Network application in Parameter Optimization of Rectangular Microstrip Patch Antenna
Authors: Mr. Malmathanraj Ramanathan, Dr. Thamarai Selvi Somasundaram
Printed microstrip antennas and arrays are known to have limitations in terms of bandwidth and efficiency, all imposed by the very presence of the dielectric substrate. The paper deals with the design of a probe fed and edge fed rectangular microstrip patch antenna with the basic parameters W,h,L,er,fo to achieve better bandwidth and directivity with efficient radiation pattern and Gain. The analytical results for various possible dimensions and different dielectric values were calculated for achieving bandwidth and directivity without any structural complexities .The analytical results were tested by simulating with basic design software PCAAD,MSTRIP40. To obtain an optimum value for the design parameters of the microstrip antenna Support Vector Machines (SVM), Generalised Regularisation Neural Network (GRNN) and Back Propagation Network (BPN) were implemented to train the network to attain optimized values to yield wide bandwidth and better directivity with high Gain. The application of artificial neural network ensures an optimum design methodology for microstrip antenna design which is revealed when comparing the results with analytical methods and the results of the simulation softwares.