Improvement Swarm Intelligence Optimization Algorithm And Its Application In Digital Filter Design

Many scientific research, engineering and economical management problems need the optimization of a set of parameters with the aim of minimizing or maximizing the objective function. To optimize the strategy and the algorithm research into recent years prepares one of research aims which is paid attention the scientific workers.The social animal (such as ant colony, swarm, bird group, school of fish etc.) has aroused people's universal interest from the organization behavior inspiration, many scholars carry on mathematics modeling and to this behavior carry on the simulation with the computer to it. From then on, it has built a new research field—Swarm Intelligence (SI), mainly includes the genetic algorithm, the ant colony optimization, particle swarm optimization and artificial fish swarm algorithm and so on.This article in to the existing swarm intelligence theory domain main algorithm elementary theory, the system model, the parameter establishment and the experimental simulation conducts the analysis research in the foundation, proposed a algorithm which combined particle swarm optimization ,the ant colony optimization, the genetic algorithm and the simulation annealing algorithm, and applies it in the IIR digital filter and adaptive notch filter design application, analyzes from the experiment on looked, has obtained certain effect, then indicated through the simulation experiment, this methods design filter have the good characteristic in the pass-band and the stop-band, had prevented well the algorithm easy to fall into partially the most excellent question, also the computation simple, the computation load is small, has compares the good application prospect, then has confirmed this combined algorithm serviceability and the validity.