Application of Improved Particle Swarm Optimization Algorithm Based on GSO in Optimization Design of FIR Digital Filter

摘要

Aiming at the problem that the particle swarm optimization algorithm will fall into the local optimum, and improve the convergence speed of the algorithm as much as possible, an improved particle swarm optimization algorithm based on firefly position optimization is proposed, which is improved based on the standard firefly position optimization algorithm. Adaptive inertia weights are introduced and flight factors, chaos and mutation strategies are introduced. The improved algorithm is applied to the optimization design of FIR digital filter. The optimization algorithm is used to efficiently search the whole particle swarm space and obtain the optimal parameters. The simulation proves the superiority of the algorithm in convergence speed and precision.