• DocumentCode
    2999292
  • Title

    Adaptive noise canceller based on PSO algorithm

  • Author

    Xia, Liu ; Hui, Gao ; Jinfeng, Liu

  • Author_Institution
    Sch. of Electr. & Inf. Eng., Daqing Pet. Inst., Daqing
  • fYear
    2008
  • fDate
    1-3 Sept. 2008
  • Firstpage
    1759
  • Lastpage
    1762
  • Abstract
    Adaptive noise cancellation technology is a very good signal processing technology, which can eliminate background noise effectively. In order to restrain the traditional adaptive canceller from trapping in local optimum, the improved PSO algorithm is leading into the mutation operator according to standard derivation of swarm fit value to inhibit local optimum, and design an adaptive noise canceller based on three-tier neural network trained by improving PSO algorithm. Theoretical analysis and computer simulations show that this system has better noise cancellation capability compared to the traditional adaptive noise canceller, and increase SNR. greatly.
  • Keywords
    adaptive filters; adaptive signal processing; learning (artificial intelligence); neural nets; particle swarm optimisation; signal denoising; adaptive filter; adaptive noise cancellation; particle swarm optimisation; signal processing technology; three-tier neural network; Automation; Background noise; Convergence; Genetic mutations; Neural networks; Noise cancellation; Particle swarm optimization; Petroleum; Signal processing algorithms; Signal to noise ratio; PSO; adaptive noise canceller; neural network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Automation and Logistics, 2008. ICAL 2008. IEEE International Conference on
  • Conference_Location
    Qingdao
  • Print_ISBN
    978-1-4244-2502-0
  • Electronic_ISBN
    978-1-4244-2503-7
  • Type

    conf

  • DOI
    10.1109/ICAL.2008.4636441
  • Filename
    4636441