• DocumentCode
    1715547
  • Title

    Lifting wavelet de-noising method with dual-threshold based on PSO algorithm

  • Author

    Liu Sheng ; Zhang Qing-chun ; Gu Ming-ming

  • Author_Institution
    Sch. of Autom., Harbin Eng. Univ., Harbin, China
  • fYear
    2013
  • Firstpage
    3680
  • Lastpage
    3684
  • Abstract
    To remove the noise of signal and improve the signal-to-noise ratio, we present a lifting wavelet de-noising method with flexible dual-threshold based on PSO algorithm. We use the lifting wavelet instead of traditional wavelet to decompose the signal, in order to improve the operation speed. we use the quantization function by flexible dual-threshold to quantify the detail coefficients. By doing this, we preferably retained the fine features of the signal, while preventing the signal oscillation. PSO algorithm is used to optimize the dual-threshold, in order to get the optimal threshold value, to improve the signal-to-noise ratio. The simulation and experimental results show that this new de-noising method can effectively suppress the noise, and get a higher signal-to-noise ratio and faster processing speed compared to the traditional denoising method.
  • Keywords
    particle swarm optimisation; quantisation (signal); signal denoising; wavelet transforms; PSO algorithm; flexible dual-threshold; lifting wavelet denoising method; noise suppression; particle swarm optimisation; quantization function; signal oscillation; signal-to-noise ratio; Educational institutions; Electronic mail; Noise reduction; Signal to noise ratio; Wavelet transforms; Flexible Dual-Threshold; Lifting Wavelet Transform; PSO algorithm; Signal De-noising;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Conference (CCC), 2013 32nd Chinese
  • Conference_Location
    Xi´an
  • Type

    conf

  • Filename
    6640060