论文部分内容阅读
针当前群智能优化算法在IIR数字滤波器设计存在的易陷入最优解,收敛速度慢等不足,提出了一种改进群智能优化算法的IIR数字滤波器设计方法。首先根据引领蜂和跟随蜂选择食物源的行为方式不同的,对跟随蜂在食物源邻域的搜索行为进行改进,使其更加准确地描述出跟随蜂的行为,然后采用其对IIR数字滤波器设计问题进行求解,最后采用仿真实验测试其性能。实验结果表明,相对于其它群智能优化算法,本文算法均取得更好的IIR数字滤波器设计效果,验证了本文方法的优越性。
Current group intelligent optimization algorithm IIR digital filter design is easy to fall into the optimal solution, the convergence speed is slow and so on, proposed an improved group intelligent optimization algorithm IIR digital filter design method. Firstly, based on the different behaviors of leading bees and following bees in selecting food sources, the search behavior of bees in the neighborhood of food sources is improved to describe the behavior of bees following the bees more accurately, and then its performance on IIR digital filters Design problems to solve, and finally use simulation experiments to test its performance. The experimental results show that compared with other intelligent optimization algorithms, the proposed algorithm achieves better IIR digital filter design results and verifies the superiority of the proposed method.