RESTRAIN END-EFFECT IN EMPIRICAL MODE DECOMPOSITION BY MIRROR EXTENSION AND RADIAL BASIS FUNCTION NEURAL NETWORK PREDICTION

	RESTRAIN END-EFFECT IN EMPIRICAL MODE DECOMPOSITION BY MIRROR EXTENSION AND RADIAL BASIS FUNCTION NEURAL NETWORK PREDICTION
	Han Jianping 2; Qian Jiongn 1
	2010
关键词	signal processing empirical mode decomposition end-effect mirror extension radial basis function neural network
页码	375-+
英文摘要	Hilbert-Huang Transform (HHT) is a new powerful signal processing approach, especially for nonlinear and non-stationary signal. HHT consists of Empirical Mode Decomposition (EMD) and Hilbert Transform (HT) and EMD is the crucial step. However, there is a troublesome end-effect issue to apply spline interpolation to get the upper and lower envelopes. Based on discussion of cause and influence of end-effect, mirror extension and prediction via radial basis function (RBF) neural network are investigated to restrain end-effect in EMD. Then a simulated signal and a recorded acceleration signal from shaking table test of a 12-stroey reinforced concrete frame model are preprocessed by these methods and decomposed by EMD respectively. The results indicate that the proposed methods can restrain end-effect to some extent, but still can not completely eliminate end-effect in EMD. In addition, for complex signal such as acceleration record of a structure, only extending signal by RBF neural network is not effective to restrain end-effect in EMD. But applying mirror extension after predicting the filtered signal using RBF neural network can restrain end-effect in EMD effectively.
会议录	PROCEEDINGS OF THE 12TH INTERNATIONAL CONFERENCE ON INSPECTION APPRAISAL REPAIRS AND MAINTENANCE OF STRUCTURES, VOLS 1 AND 2
会议录出版者	CI-PREMIER PTE LTD
会议录出版地	150 ORCHARD ROAD #07-14, ORCHARD PLAZA, SINGAPORE, 238841, SINGAPORE
语种	英语
WOS研究方向	Engineering
WOS记录号	WOS:000290459300051
内容类型	会议论文
源URL	[http://119.78.100.223/handle/2XXMBERH/37709]
专题	教务处（创新创业学院）
通讯作者	Han Jianping
作者单位	1.Planning & Construct Bur Anji Cty, Anji County, Zhejiang, Peoples R China 2.Lanzhou Univ Technol, Lanzhou, Gansu, Peoples R China
推荐引用方式 GB/T 7714	Han Jianping,Qian Jiongn. RESTRAIN END-EFFECT IN EMPIRICAL MODE DECOMPOSITION BY MIRROR EXTENSION AND RADIAL BASIS FUNCTION NEURAL NETWORK PREDICTION[C]. 见:.