期刊文献+

基于二分递推SVD的信号奇异性位置精确检测 被引量:13

Accurate Detection of Signal Singularity Position Based on Dichotomizing Recursion SVD
下载PDF
导出
摘要 提出利用信号构造行数为2的矩阵,在奇异值分解后保留小奇异值对应的分量,并取大奇异值所对应的分量信号重复构造相同矩阵进行奇异值分解,从而将原始信号分解为一组分量信号.这种分量信号具有二阶消失矩,可实现对原始信号中Lipschitz指数为0和1的奇异性的位置精确检测,其检测脉宽小,且在同一层分量中指示奇异点位置的模极大值和奇异点处的突变量、转折斜率具有正比线性关系.此法克服了小波变换检测结果的位置偏移和脉冲宽大的缺陷,在对铣削力信号的处理中,准确地检测出了其中的微弱冲击. It is proposed that a matrix with row number 2 is created by original signal and is processed by singular value de- composition (SVD),the component signal corresponding to the small singular value is retained, while the one corresponding to the big singular value is continuously used to create the same matrix to be continuously processed by SVD, by this way original signal can be decomposed into a group of cornponent signals, which have the second order vanishing moment and can detect the accurate position of singularity with Lipschitz index 0 and 1 in original signal.Furthermore,the width of their detection impulse is small,and the modulus maxima in the component signals of the same level are proportional to the quantity of sudden change and the turning slope in the singular point. The defects of wavelet singularity detection, i. e. the deviation of singularity position and big width of detection imoulse, are overcome and the faint imoacts in the mininz force signal are accurately detected by this method.
出处 《电子学报》 EI CAS CSCD 北大核心 2012年第1期53-59,共7页 Acta Electronica Sinica
基金 国家自然科学基金(No.50875086) 中央高校基本科研业务费专项资金(No.2009ZM0287) 广州市科技计划(No.2008J1-C101)
关键词 奇异值分解 二分递推矩阵构造 奇异性检测 信号处理 singular value decomposition (SVD) dichotomizing recursion creation of matrix singularity detection signalprocessing
  • 相关文献

参考文献15

  • 1Figarella T, Jansen M H. Brush wear detection by continuous wavelet transform[J]. Mechanical Systems and Signal Process- ing,2007,21(3) :1212 - 1222.
  • 2刘玉良,李刚,林凌,王焱.基于小波分析的光电脉搏波奇异性处理[J].信号处理,2007,23(1):64-68. 被引量:7
  • 3柳春光,刘海兵,贾玲玲.基于小波奇异性的梁结构损伤评估方法研究[J].大连理工大学学报,2009,49(1):105-109. 被引量:2
  • 4Jiang Huiqin,Ma Ling, Jiang Hongyu, Rinoshika A. Application of wavelet-based singularity detection technique in automatic inspection system[ J ]. International Journal of Wavelets, Mul- tiresolution and Information Processing, 2006,4(2) : 285 - 295.
  • 5Li ChunFeng, Liner C. Wavelet-based detection of singularities in acoustic impedances from surface seismic reflection data[ J]. Geophysics, 2008,73( 1 ) : 1 - 9.
  • 6Zhong J,Ning R. Image denoising based on wavelets and multi- fractals for singularity detection[J]. IEEE Transactions on Im- age Processing, 2005,14(10) : 1435 - 1447.
  • 7崔长彩,张耕培,张彬,张倩.小波滤波及奇异性分析在表面形貌评定中的应用[J].光学精密工程,2009,17(9):2255-2261. 被引量:8
  • 8赵学智,林颖,陈文戈,陈统坚,叶邦彦.奇异性信号检测时小波基的选择[J].华南理工大学学报(自然科学版),2000,28(10):75-80. 被引量:31
  • 9王佰玲,田志宏,张永铮.奇异值分解算法优化[J].电子学报,2010,38(10):2234-2239. 被引量:21
  • 10Selvan S, Ramakrishnan S. SVD-based modeling for image texture classification using wavelet transformation [ J ]. IEEE Transactions on Image Processing, 2007, 16 ( 11 ):2688 -2696.

二级参考文献51

共引文献111

同被引文献140

引证文献13

二级引证文献96

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部