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A Sparse Representation Algorithm for the Mode Separation and SNR Improvement of Lamb Wave Signals

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【Author】 YU Yong-Ling;ZHANG Hai-Yan;SHI Fang-Fang;FENG Guo-Rui;MA Shi-Wei;School of Communication and Information Engineering,Key Laboratory of Specialty Fiber Optics and Optical Access Networks,Shanghai University;Institute of Acoustics,Chinese Academy of Sciences;Shanghai Key Laboratory of Power Station Automation Technology,School of Mechatronic Engineering andAutomation,Shanghai University;

【机构】 School of Communication and Information Engineering,Key Laboratory of Specialty Fiber Optics and Optical Access Networks,Shanghai University； Institute of Acoustics,Chinese Academy of Sciences； Shanghai Key Laboratory of Power Station Automation Technology,School of Mechatronic Engineering andAutomation,Shanghai University；

【摘要】 A matching pursuit method based on training an over-complete dictionary is investigated.By using the K-singular value decomposition(K-SVD) algorithm,an over-complete dictionary that describes the Lamb wave signals is trained.The results demonstrate that the method can effectively remove redundant information and separate multiple Lamb wave modes.The matching pursuit method with the K-SVD algorithm shows its efficiency for Lamb wave signal processing.更多还原

【Abstract】 A matching pursuit method based on training an over-complete dictionary is investigated.By using the K-singular value decomposition(K-SVD) algorithm,an over-complete dictionary that describes the Lamb wave signals is trained.The results demonstrate that the method can effectively remove redundant information and separate multiple Lamb wave modes.The matching pursuit method with the K-SVD algorithm shows its efficiency for Lamb wave signal processing.更多还原

【基金】 Supported by the National Natural Science Foundation of China under Grant Nos 11074164,11274226,11074273 and 61171145;the Innovation Foundation of Shanghai Municipal Commission of Education(No 11YZ17);the Ph.D.Foundation of Ministry of Education of China(20103108120011)

【文献出处】 Chinese Physics Letters ,中国物理快报(英文版) , 编辑部邮箱 ,2013年03期

【分类号】TN911.7

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