Designs Of Antennas Based On Genetic Algorithms And Neural Network

Microstrip antennas have several advantages for mobile communications in size,weight and compact structure. How to make them compact and broadband is a valuable focus. Besides, fractal antennas and antennas loading MEMS (Micro-Electro-MechanicalSystems ) switches have attracted more and more attentions.Today, optimizing the design of antennas using Genetic Algorithms(GA) is a focus.As a common search method,GA can be used easily in the antenna design and get good effect without the boundary in initialization values.When using GA,we get the fitness values by some mathematics methods or simulations.But the former method is too complicate to realize when the antenna is intricate in structure ,and the latter would consuming a lot of time.To solving this problem,we bring forward the using of neural network (NN) to establish a good mapping relation between the structure and the performance,in this way ,we can save much time.In this paper,carried on a research on the integrating of GA and NN and using them in the optimization of antennas .First we picked some samples and calculate the performance parameter with High Frequency Structure Simulator (HFSS) and output the results.Then establish the NN modal using the former results to map the relation between the structure and the performance .After that,we use the GA to search the one satisfying our requirement ,adopting different fitness functions.By utilizing this set of optimization program, several antennas including PIFA with parasite elements, triangle shape microstip antenna and so on.Also try to explore in a fractal MEMS Reconfiguable antenna.