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中国科学院地质与地球物理研究所2013年度（第13届）学术年会

作者： Liu Lanfeng Li Lihua Wei Xiucheng Huang Zhongyu Petroleum Research Institute of Exploration & Development SINOPEC China University of Petroleum(Beijing) Beijing Yadan Technology Development Co. Ltd

A new time-frequency decomposition method is implemented based on the general matching pursuit in virtue of the high resolution and the parameter -adjustment flexibility of wideband B-spline wavelet with four *** paper discusses the accuracy and validity of the method through theoretic model *** time-frequency spectrum calculated by this algorithm has higher resolution and better time-frequency localization than that calculated by Morlet *** apply it to the real seismic data successfully,and the low-frequency energy section calculated by this method can well reflect the reservoir heterogeneity and detail information in the reservoir.

关键词： wideband B-spline wavelet matching pursuit time-frequency decomposition instantaneous spectrum

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NON-STATIONARY SIGNAL DENOISING USING time-frequency CURVE SURFACE FITTING

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Journal of Electronics(China) 2007年第6期24卷 776-781页

作者： Liu Xiaofeng Qin Shuren Bo Lin Test Center of Mechanical Engineering Chongqing University Chongqing 400044 China

Based on the theory of adaptive time-frequency decomposition and time-frequency Dis- tribution Series (TFDS), this paper presents a novel denoising method for non-stationary signal. Ac- cording to the input signal features, an appropriate kind of elementary functions with great concen- tration in the time-frequency (TF) plane is selected. Then the input signal is decomposed into a linear combination of these functions. The elementary function parameters are determined by using ele- mentary function TF curve surface to fit the input signal’s TFDS. The process of curved surface fitting corresponds to the signal structure matching process. The input signal’s dominating component whose structure has the resemblance with elementary function is fitted out firstly. Repeating the fitting process, the residue can be regarded as noises, which are greatly different from the function. Selecting the functions fitted out initially for reconstruction, the denoised signal is obtained. The performance of the proposed method is assessed by means of several tests on an emulated signal and a gearbox vi- brating signal.

关键词： time-frequency decomposition Elementary function time-frequency Distribution Series (TFDS) Curve surface fitting Noise suppressing

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