摘要
超宽谱混沌信号经过经验模态分解(EMD)后得到具有不同时间特征尺度的固有模态函数(IMF)分量,由于各分量中噪声与信号同时存在,会发生模态混叠。针对此问题,提出一种改进EMD与小波阈值法相结合的光生混沌信号降噪方法。首先对经过EMD分解后的IMF分量采用两种不同阈值函数分别对信号主导模态分量和噪声主导模态分量进行去噪处理,然后将提取出的信号成分相加重构得到混沌信号。仿真结果表明:该方法能够有效地去除噪声,且降噪效果优于已有的EMD分解去噪方法,可进一步提高重构信号的信噪比,降低其均方误差,是一种有效可行的光生混沌信号降噪方法。
The empirical mode decomposition(EMD)of the ultra-wideband chaotic signals is used to obtain the intrinsic mode function(IMF)components with different time feature scales.Because the noise and the signal exist in each component simultaniously,the modal aliasing may occur.Therefore,a photogenerated chaotic signal denoising method based on the improved EMD and wavelet threshold method is proposed in this paper.The IMF component is decomposed by EMD.Two different threshold functions are used to denoise the signal dominant modal component and noise dominant modal component respectively,and then the extracted signal components are added and reconstructed to obtain the chaos signal.The simulation results indicate that the method can remove the noise effectively,improve the signal-to-noise ratio further,reduce the mean square error,and its noise reduction effect is superior to the existing EMD denoising method,which is a feasible denoising method for the photogenerated chaotic signal.
作者
牛阔
张朝霞
王娟芬
杨玲珍
NIU Kuo;ZHANG Zhaoxia;WANG Juanfen;YANG Lingzhen(College of Physics and Optoelectronics,Taiyuan University of Technology,Taiyuan 030024,China;MOE Key Laboratory of Advanced Transducers and Intelligent Control System,Taiyuan University of Technology,Taiyuan 030024,China)
出处
《现代电子技术》
北大核心
2018年第17期53-58,共6页
Modern Electronics Technique
基金
国家自然科学基金面上项目(61377089)
国家自然科学基金面上项目(61575137)
山西省自然科学基金资助项目(2013011019-6)
山西省教育厅科技创新项目(2014112)
山西省科学技术发展计划(工业)项目(20140321003-02)~~
关键词
光生混沌信号
经验模态分解
固有模态函数
小波阈值去噪法
相关分析
降噪方法
photogenerated chaos signal
empirical mode decomposition
intrinsic mode function
wavelet threshold denoising method
correlation analysis
denoising method
