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
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;
Conference_Titel :
Control Conference (CCC), 2013 32nd Chinese
Conference_Location :
Xi´an