摘要
针对传感器水声信号存在随机噪声的问题,提出了一种正余弦算法(SCA)和粒子群算法(PSO)相结合优化变分模态分解(VMD)参数k和α,将含噪信号通过VMD分解为k个固有模态函数,选取相关系数高的模态分量进行小波阈值(WT)去噪后重构信号分量,得到目标信号的算法,记为SCA-PSO-VMD-WT算法.通过将本算法与VMD-WT,PSO-VMD-WT,SCA-VMD-WT算法相比,并从信噪比、均方误差2个评估指标发现本算法的去噪效果最好.
Aiming at the problem of random noise in sensor underwater acoustic signals,this paper proposes a method of combining sine cosine algorithm(SCA)and particle swarm optimization(PSO)to optimize the parameter of variational modal decomposition(VMD).The noisy signal is decomposed into an inherent modal function by VMD,and the modal component with high correlation coefficient is selected for wavelet threshold(WT)denoising and then the signal component is reconstructed to obtain the target signal algorithm,which is called SCA-PSO-VMD-WT algorithm.By comparing this algorithm with VMD-WT,PSO-VMD-WT,SCA-VMD-WT,and from two evaluation indexes of signal-to-noise ratio and mean square error,it is found that this algorithm has the best denoising effect.
作者
奥彦
胡红萍
白艳萍
史娜
AO Yan;HU Hong-ping;BAI Yan-ping;SHI Na(School of Science,North University of China,Taiyuan 030051,China)
出处
《数学的实践与认识》
2021年第2期158-163,共6页
Mathematics in Practice and Theory
基金
山西省回国留学人员科研资助项目(2020-104)
山西省自然科学基金(201801D121026,201701D221121)
国家自然科学基金(61774137)
山西省研究生教育创新计划项目(2020SY387)
山西省重点研发计划项目(201903D121156)。
关键词
正余弦算法
粒子群算法
变分模态分解
小波阈值去噪
sine and cosine algorithm
particle swarm optimization algorithm
variational modal decomposition
wavelet threshold denoising
