本文關(guān)鍵詞： 局部均值分解 BP神經(jīng)網(wǎng)絡(luò) 仿真信號(hào) 端部效應(yīng)　出處：《電子技術(shù)應(yīng)用》2017年05期 　論文類型：期刊論文

【摘要】：詳細(xì)闡述了局部均值分解(LMD)信號(hào)處理方法,該方法非常適合處理非平穩(wěn)信號(hào),可其端部效應(yīng)嚴(yán)重制約了其進(jìn)一步應(yīng)用推廣。鏡像延拓是局域分解端部效應(yīng)處理的基本途徑,需要鏡像面放置在局部極值點(diǎn)處,而實(shí)際信號(hào)有時(shí)難以滿足這個(gè)條件,可能導(dǎo)致信號(hào)分解結(jié)果嚴(yán)重失真現(xiàn)象。為此,提出了一種基于傳統(tǒng)鏡像延拓與BP神經(jīng)網(wǎng)絡(luò)相結(jié)合進(jìn)行信號(hào)預(yù)測(cè)以改進(jìn)LMD端部效應(yīng)消除效果的新方法。通過BP神經(jīng)網(wǎng)絡(luò)模型預(yù)測(cè)原始信號(hào)端點(diǎn)之外的數(shù)據(jù)點(diǎn),由此捕捉到端點(diǎn)之外的一個(gè)或者多個(gè)極值點(diǎn),再用鏡像技術(shù)形成閉合處理,從而抑制端部效應(yīng)。仿真信號(hào)的應(yīng)用實(shí)例表明,所提方法可以有效抑制LMD端部效應(yīng)。
[Abstract]:The method of local mean decomposition (LMD) signal processing is described in detail. This method is very suitable for dealing with non-stationary signals, but its end effect seriously restricts its further application and popularization. Image continuation is the basic way to deal with local decomposition end effects. The image plane needs to be placed at the local extremum, and the actual signal is sometimes difficult to satisfy this condition, which may lead to serious distortion of the signal decomposition result. A new method of signal prediction based on the combination of traditional image continuation and BP neural network is proposed to improve the effect of eliminating the end effect of LMD. The BP neural network model is used to predict the data points outside the original signal endpoint. One or more extreme points outside the endpoint are captured, and then closed processing is formed by mirror image technique to suppress the end effect. The application of the simulation signal shows that the proposed method can effectively suppress the end effect of LMD.
【作者單位】： 江蘇第二師范學(xué)院數(shù)學(xué)與信息技術(shù)學(xué)院;江蘇第二師范學(xué)院信息化建設(shè)與管理辦公室;南京南瑞集團(tuán)信息通信技術(shù)分公司;
【基金】：國(guó)家自然科學(xué)基金(61272506) 國(guó)家科技支撐計(jì)劃課題(2007BAB18B01)
【分類號(hào)】：TN911.7;TP183
，

本文編號(hào)：1527686