Optimal Design Of Dual-passband Digital Filter Based On Evolutionary Algorithm

Nowadays,the digital filter has already occupied the indispensable position in the electronic technology domain and is widely used in the speech transmission,the image analysis,the radio survey,the aerospace and the medical application.The performance of digital filter optimization work is also particularly important.In the design of analog filters,the required high-precision,multi-index and other requirements make the design process not only more complex but also easily affected by the outside world.It is difficult to achieve the target requirements.Nowadays with the development of computer technology and the continuous development of integrated circuit technology,we can use computer software to meet our requirements to design a digital filter.However,with the continuous improvement of the performance of the digital filter,the structure of the digital filter becomes more and more complex so that the general design method is difficult to achieve success.So in the work of digital filter optimization,it is also particularly important.In recent years,the intelligent algorithms for digital filter optimization process is widely used.The main contributions are as follows: Genetic Algorithm(GA),Neural Network Algorithm(NEA),Immune Clonal Selection Algorithm(ICSA),Particle Swarm Optimization(PSO)and Ant Colony Optimization Ant Colony Optimization,ACO)and so on.These optimization algorithms are based on the performance requirements of the digital filter corresponding to the system transfer function.We can obtain the structure of the digital filter by the system transfer function,and then the structure of the digital filter is optimized analysis according to the characteristics of each algorithm.In this paper,the genetic algorithm and particle swarm optimization algorithm are respectively used to optimize the structure of the digital filter,and then we compare this two experiments to get the much better optimized algorithm.In order to optimize the digital filter,the genetic algorithm is used to obtain the optimal filter structure,and the digital filter parameters are further optimized by the differential evolution algorithm.This article mainly carries on the following several aspects of research work:(1)A brief introduction to the design method of digital filter is drawn.(2)Genetic algorithm and particle swarm algorithm are used to design the digital filter structure respectively.(3)We optimize the performance of digital filters through the genetic algorithm and particle swarm optimization algorithm and compare this two experimental data for comparative analysis.(4)At last,the research results are summarized and the work is prospected.Through the experimental results in this paper,it can be proved that the optimal design method of digital filters based on genetic algorithm can obtain better experimental results than PSO can.According to the target characteristic of the filter,the filter structure can be directly designed.It is a more effective method in the design of the filter,and the evolutionary algorithm has wide applicability.