计算机科学 ›› 2011, Vol. 38 ›› Issue (Z10): 423-424.

• 新技术应用 • 上一篇    下一篇

基于改进粒子群算法的自适应陷波器设计

章洁,蒋世奇   

  1. (成都信息工程学院控制工程系 成都610225)
  • 出版日期:2018-11-16 发布日期:2018-11-16
  • 基金资助:
    本文受航空科学基金((20101024005)资助。

New Particle Swarm Optimization Algorithm for the Design of the Adaptive Notch Filter

ZHANG Jie, JIANG Shi-qi   

  • Online:2018-11-16 Published:2018-11-16

摘要: 在信号处理中,接收信号常伴随着干扰和噪声,这就需要最优滤波器来实现,其中工频干扰的消除则以自适应陷波器为最优。利用粒子群算法自适应地调节其权值,得到与干扰信号接近的期望信号,最终达到消除干扰得到有用信号的目的。同时,针对此算法存在局部收敛和收敛速度不高的问题,提出了改进方法。计算机仿真结果表明了该改进粒子群算法在自适应陷波器设计上的有效性,并取得了较高的效率。

关键词: 粒子群算法,自适应陷波器,最优滤器,干扰

Abstract: In signal processing ficld,disturbanee and noise signal often exists in the received signal. Adaptive notch filter, as one of the optimal filter, is the best structure to eliminate the low frequency interference. In this paper, the particle swarm optimization was applied to the adaptive notch filter, it can get useful signal by the adaptive algorithm to adjusting its weight and eliminating the low frequency interference. Then,a new PSO algorithm was proposed to improve the local convergence and the speed of convergence, the simulation results show that the algorithm is efficient and hasgood global optimization ability.

Key words: Particle swarm optimization, Adaptive notch filter, Optimal filter, Disturbance

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