标题:Adaptive microseismic data compressed sensing method based on dictionary learning
作者:Peng, Yanjun; Tian, Sai
通讯作者:Peng, YJ;Peng, Yanjun
作者机构:[Peng, Yanjun; Tian, Sai] Shandong Univ Sci & Technol, Coll Comp Sci & Engn, Qingdao 266000, Shandong, Peoples R China.
会议名称:6th International Multi-Conference on Engineering and Technology Innovation (IMETI)
会议日期:OCT 27-31, 2017
来源:MICROSYSTEM TECHNOLOGIES-MICRO-AND NANOSYSTEMS-INFORMATION STORAGE AND PROCESSING SYSTEMS
出版年:2019
卷:25
期:5
页码:2085-2091
DOI:10.1007/s00542-018-4225-3
摘要:The theory of compressed sensing brings a revolutionary breakthrough to signal acquisition technology, it can sample the signal far below the Nyquist frequency, and accurately reconstruct the original signal through numerical optimization method. In order to improve the precision of microseismic signal after reconstruction and improve the sampling efficiency, an adaptive microseismic data compressed sensing method based on dictionary learning is proposed in this paper. Firstly, the adaptive redundancy dictionary is constructed according to the characteristics of the microseismic signal. Then the energy and the sparsity under redundant dictionary of signal are calculated. Finally, according to the comprehensive index of energy and sparseness, an adaptive sampling strategy of compressed sensing is developed. Simulation experiment show that, the algorithm reduces the number of samples by 10% compared with traditional compressed sensing, and improves the reconstruction accuracy.
收录类别:CPCI-S;EI;SCIE
资源类型:会议论文;期刊论文
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