摘要
在机动通信网络中通信信号优化研究的过程中,由于由于信号受到噪声干扰产生误差,采用当前的算法进行去噪时对通信的频率考虑不充分,致使通信系统存在恒定的偏差,容易造成去噪效果差的问题。为此提出了一种改进经验模态分解(EMD)算法的机动通信网络中通信尖峰信号去噪方法。该方法利用经验模态分解原理将机动通信网络中通信尖峰信号分解为由高至低不同的频率段,融合于小波阙值将各频段内的通信尖峰信号逆向循环平移小波,在此基础上利用小波阈值估计不同频段内的通信尖峰信号,计算其平均值,进而获得重构的通信尖峰信号,精确的实现了对机动通信网络中通信尖峰信号的去噪。仿真结果证明,改进经验模态分解(EMD)算法的机动通信网络中通信去噪效果稳定,鲁棒性强。
A peak signal denoising method for mobile communication network is presented based on improved empirical mode decomposition （EMD） algorithm. The method decomposes the peak signal into different frequency bands from high to low by using empirical mode decomposition principle, and moves the peak signal in each band reversely according to the wavelet threshold. The peak signals in different frequency bands are estimated based on the wavelet threshold, and the average value is calculated. Then the refactored peak signal is obtained, and the peak signal de- noising is accurately implemented. Simulation results show that the proposed algorithm can achieve stable and robust denoising effect.
出处
《计算机仿真》
CSCD
北大核心
2015年第10期310-313,共4页
Computer Simulation
关键词
经验模态分解
去噪
小波阀值
Empirical mode decomposition（EMD）
Denoising
Wavelet threshold
