改进的遗传算法在数字滤波器优化应用研究

摘要

研究数字滤波器自动生成优化问题.针对传统的数字滤波器在优化设计时,容易往往出现难以调整波形系数,与硬件接口程序复杂,开发周期长等问题缺陷,为了解决上述问题,提出了一种采用改进的遗传算法应用于FPGA数字滤波器的优化设计中,利用了遗传算法全局优化概率检索的优点,求解复杂系统优化问题.把求解滤波器参数的问题数学化为性能指标优化模型,采用改进的遗传算法求得特性符合要求的滤波器参数值,仿真结果表明,设计系统软件界面可以根据用户设定的滤波参数,自动设计出符合要求的数字滤波器RTL.系统性能高效,能够大大提高滤波器的设计效率.数值仿真表明了算法的有效性.%The paper deals with automatic generations of the digital filter FPCA system problems. Traditional digital filters have some defects and other issues in optimal designing, such as, it is difficult to adjust the form factors, the hardware interfaces are complex, and the development cycle is long. In order to solve the problem, the paper proposed an improved genetic algorithm for FPCA Digital Filter optimized design. The algorithm takes the advantages of global optimization and the probability retrieve of genetic algorithms to solve the complex optimization problems. The problem of solving filter parameters was mathematically turned into an optimization model of performance index. Then the improved genetic algorithm was used to obtained the filter parameter values which can meet the requirements of characteristics. Simulation results show that the system provides users with software interface and can automatically design a digital filter based on the filter parameters given by users. This system is easy, efficient, and can greatly enhance the efficiency of filter design.