小波
算法
计算机科学
平稳小波变换
小波变换
离散小波变换
小波包分解
级联算法
数学
吊装方案
噪音(视频)
第二代小波变换
人工智能
模式识别(心理学)
图像(数学)
降噪
粒子群优化
作者
Liu Sheng,Zhang Qing-chun,Gu Ming-ming
出处
期刊:Chinese Control Conference
日期:2013-07-26
卷期号:: 3680-3684
被引量:1
摘要
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.
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