Title :
Neural network based particle swarm optimizer for design of dual resonance X/Ku band stacked patch antenna
Author :
Jain, S.K. ; Patnaik, A. ; Sinha, S.N.
Author_Institution :
Electron. & Comput. Eng. Dept., Indian Inst. of Technol. Roorkee, Roorkee, India
Abstract :
With the increase in number of layers in a stacked patch microstrip antenna, for multiband operation, the number of parameters, deciding the frequency of operation, increases. Then it becomes a difficult task to optimize all the parameters simultaneously for specified frequencies of operation. In this paper, a particle swarm optimization (PSO) based algorithm have been developed to decide the patch dimensions of dual band square stacked patch antenna (SPA) operating in the X/Ku band. The cost function for the PSO is evaluated with the help of trained neural network (NN) to reduce the lengthy simulation time. The results from this PSO based CAD model have been cross verified with the experimental results for some typical stacked patch antennas.
Keywords :
electrical engineering computing; learning (artificial intelligence); microstrip antennas; neural nets; particle swarm optimisation; PSO based CAD model; dual band square SPA; dual band square stacked patch antenna; dual resonance X-Ku band stacked patch microstrip antenna design; multiband operation; neural network based PSO; neural network based particle swarm optimization; Artificial neural networks; Cost function; Microstrip; Microstrip antennas; Patch antennas; Resonant frequency; neural network; particle swarm optimization; stacked patch antenna;
Conference_Titel :
Antennas and Propagation (APSURSI), 2011 IEEE International Symposium on
Conference_Location :
Spokane, WA
Print_ISBN :
978-1-4244-9562-7
DOI :
10.1109/APS.2011.5997142
