• DocumentCode
    2519891
  • Title

    FIR Digital Filters Design Based on Quantum-behaved Particle Swarm Optimization

  • Author

    Fang, Wei ; Sun, Jun ; Xu, Wenbo ; Liu, Jing

  • Author_Institution
    Center of Intelligent & High Performance Comput., Southern Yangtze Univ.
  • Volume
    1
  • fYear
    2006
  • fDate
    Aug. 30 2006-Sept. 1 2006
  • Firstpage
    615
  • Lastpage
    619
  • Abstract
    FIR digital filters design involves multi-parameter optimization, on which the existing optimization algorithm doesn´t work efficiently. This paper focuses on employing the proposed quantum-behaved particle swarm optimization (QPSO) to design FIR digital filters. QPSO is a global stochastic searching technique that can find out the global optima of the problem more rapidly than original PSO. After describing the origin and development of QPSO, we present how to use it in FIR digital filters design. It has been demonstrated by experiment results that QPSO outperforms the PSO and genetic algorithm (GA) for the problem
  • Keywords
    FIR filters; particle swarm optimisation; quantum computing; search problems; stochastic processes; FIR digital filter design; QPSO; multiparameter optimization; quantum-behaved particle swarm optimization; stochastic search technique; Algorithm design and analysis; Convergence; Design optimization; Digital filters; Finite impulse response filter; Frequency; Genetic algorithms; High performance computing; Particle swarm optimization; Sun;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Innovative Computing, Information and Control, 2006. ICICIC '06. First International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    0-7695-2616-0
  • Type

    conf

  • DOI
    10.1109/ICICIC.2006.77
  • Filename
    1691875