Optimal Filter Design Based On Improved Genetic Algorithm

It has been a hot research spot to adopt genetic algorithms (GA) for optimal filter design recently. The primary research of this paper concentrates mainly on the optimization design of active filters with improved genetic algorithm and the approximation problem of head-related transfer function (HRTFs).The thesis first expounds the related theory of genetic algorithms, such as the basic concept, components, characteristics and the improved technology of genetic algorithms. Second, it carries out some exploring research in the aspect of genetic algorithm's optimal design on filters. The major contributions made by the research are as follows:1. Further research into the design theory of filter. Active filters is widely applied for its advantages, such as small volume and easy integration, thus showing great significance to the improvement method of the active filters. Genetic algorithm is a probability search algorithm formed by simulating life's descendiblity and evolution process in nature; Global optimization method of the circuit parameter design, which is based on total transfer function, carries out design of circuit parameters. This thesis combines genetic algorithm and the idea of global optimization together to design the Chebyshev low pass. The results show that this idea overcomes some shortcomings of traditional methods and has obvious improvement.2. This thesis puts forward the idea that the improved genetic algorithm approximates HRTFs. To solve the problem that there is a big error caused by the traditional genetic algorithm, this research makes use of the outcomes of space hearing and provides new solutions to chromosome coding, population initialization, the designing of fitness function and genetic operations, and decoding chromosome as well. Examples are adopting improved ways of choosing, putting forward adaptive genetic algorithm, elite selection strategy and best guide strategy. In the late period of the function of genetic algorithm, properly enlarging the degree of fitness of individuals, broadening difference between the best individual fitness and that of other individuals serve to increase the competition among individuals. As is revealed from the results of the experiment, the approximation of improved genetic algorithm is obviously better than that of the traditional algorithm or Prony.3. Coupler is a kind of microwave circuit applied widely, which can compose filter , such as dual directional coupler can compose optical comb filter.After filtering, for the signal broadband transmission, we should use the directional coupler, which is the multi-port device. This paper uses genetic algorithm in optimum design of the multiple grade branch directional coupler and makes some improvements in algorithms. The design abandons the limit of balance between the main line and branches, which leads to strengthening the freedom of design work. The optimum design method determines the characteristic impedance of both main lines and braches, as a result of which the bandwidth of the directional coupler is broadened. Based on the standard genetic algorithm, the best storage strategy and fitness genetic operations are brought in to improve the performance of the algorithm. Simulation shows that multiple grade branch directional coupler designed with this method performs better than any other design method.The thesis finally makes conclusions about the research that has been done and puts forward as well the direction for further research.