消除局域分解端部效应的BP神经网络闭合方法  

Local mean decomposition method to eliminate end effects of BP neural network method of closing the mirror

作　　者：王莉娜[1] 杨剑[2] 孟庆强 

机构地区：[1]江苏第二师范学院数学与信息技术学院,江苏南京210036 [2]江苏第二师范学院信息化建设与管理办公室,江苏南京210036 [3]南京南瑞集团信息通信技术分公司,江苏南京210003

出　　处：《电子技术应用》2017年第5期127-130,133,共5页Application of Electronic Technique

基　　金：国家自然科学基金(61272506);国家科技支撑计划课题(2007BAB18B01)

摘　　要：详细阐述了局部均值分解(LMD)信号处理方法,该方法非常适合处理非平稳信号,可其端部效应严重制约了其进一步应用推广。镜像延拓是局域分解端部效应处理的基本途径,需要镜像面放置在局部极值点处,而实际信号有时难以满足这个条件,可能导致信号分解结果严重失真现象。为此,提出了一种基于传统镜像延拓与BP神经网络相结合进行信号预测以改进LMD端部效应消除效果的新方法。通过BP神经网络模型预测原始信号端点之外的数据点,由此捕捉到端点之外的一个或者多个极值点,再用镜像技术形成闭合处理,从而抑制端部效应。仿真信号的应用实例表明,所提方法可以有效抑制LMD端部效应。Local mean decomposition （LMD） signal processing method is elaborated and is very suitable for non-stationary signals, which can end effect severely restrict its further application. And promotion of local mirror extension is decomposed basic ways end effect processing, which needs to be mirrored surface in local extreme point. Actual signal is sometimes difficult to satisfy this con- dition, which may lead to serious distortion signal decomposition. To solve this problem, a conventional mirror extension and neural network is proposed to improve new LMD end effect eliminate the effect by a combination of data extrapolation method. The neural network model predictions fit the data points outside the end of original signal, thereby captures one or more endpoints than the extreme point. And then ,mirroring technology forms a closed process, thereby inhibits the end effect. Simulation results show that the proposed method can effectively suppress LMD end effect.

关 键 词：局部均值分解 BP神经网络 仿真信号 端部效应 

分 类 号：TN911.7[电子电信—通信与信息系统]