메뉴 건너뛰기




Volumn 6795, Issue , 2007, Pages

Ricker wavelet LS-SVM and its parameters setting for seismic prospecting signals denoising

Author keywords

LS SVM; Parameters estimation; Ricker wavelet; Seismic prospecting event

Indexed keywords

PARAMETER ESTIMATION; RANDOM PROCESSES; SEISMIC PROSPECTING; SIGNAL ANALYSIS; SIGNAL TO NOISE RATIO;

EID: 42949155727     PISSN: 0277786X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.773771     Document Type: Conference Paper
Times cited : (4)

References (10)
  • 2
    • 27144489164 scopus 로고    scopus 로고
    • A tutorial on support vector machines for pattern recognition
    • C. J. C. Burges, "A tutorial on support vector machines for pattern recognition," Data Mining and Knowledge Discovery, vol.2 (2 ), pp.121-167, 1998
    • (1998) Data Mining and Knowledge Discovery , vol.2 , Issue.2 , pp. 121-167
    • Burges, C.J.C.1
  • 3
    • 42949124055 scopus 로고    scopus 로고
    • Text categorization with support vector machines
    • Royal Holloway university of London
    • T. Joachims, "Text categorization with support vector machines," CSD-TR-98-04, Royal Holloway university of London, 1998.
    • (1998) CSD-TR-98-04
    • Joachims, T.1
  • 5
    • 23244449283 scopus 로고    scopus 로고
    • Chaotic time series prediction using least squares support vector machines
    • M.Y. Ye, and X.D. Wang, "Chaotic time series prediction using least squares support vector machines," Chinese Physics, vol. 13(4), pp. 454-458, 2004.
    • (2004) Chinese Physics , vol.13 , Issue.4 , pp. 454-458
    • Ye, M.Y.1    Wang, X.D.2
  • 6
    • 13244265605 scopus 로고    scopus 로고
    • B.Y. Sun, D.S. Huang, Senior Member, IEEE, and H.T. Fang, Lidar Signal Denoising Using Least-Squares Support Vector Machine, IEEE Signal processing letters, 12 (2), pp. 101-104, February 2005.
    • B.Y. Sun, D.S. Huang, Senior Member, IEEE, and H.T. Fang, "Lidar Signal Denoising Using Least-Squares Support Vector Machine," IEEE Signal processing letters, vol.12 (2), pp. 101-104, February 2005.
  • 7
    • 0032098361 scopus 로고    scopus 로고
    • A. Smola, B. Scholkopf and K. R. Muller, The connection between regularization operators and support vector kernels, Neural Networks, 11(4), pp. 637-649, 998.
    • A. Smola, B. Scholkopf and K. R. Muller, "The connection between regularization operators and support vector kernels," Neural Networks, vol. 11(4), pp. 637-649, 998.
  • 8
    • 42949085192 scopus 로고
    • Beijing, China: Higher Education Press, In Chinese
    • D.Z. Wu, Signal and linear system analysis, Beijing, China: Higher Education Press, 1986.(In Chinese)
    • (1986) Signal and linear system analysis
    • Wu, D.Z.1
  • 9
    • 0346250790 scopus 로고    scopus 로고
    • Practical selection of SVM parameters and noise estimation for SVM regression
    • V. Cherkassky, Y.Q. Ma, "Practical selection of SVM parameters and noise estimation for SVM regression," Neural Networks, vol.17, pp.113-126, 2004
    • (2004) Neural Networks , vol.17 , pp. 113-126
    • Cherkassky, V.1    Ma, Y.Q.2
  • 10
    • 0002941010 scopus 로고    scopus 로고
    • Support vector machines for dynamic reconstruction of a chaotic system
    • B. Scholkopf, J.Burges, and A. SmolaEds, Cambridge, MA: MIT Press
    • D. Mattera, and S. Haykin, "Support vector machines for dynamic reconstruction of a chaotic system," In B. Scholkopf, J.Burges, and A. Smola(Eds.), Advances in kernel methods: Support vector machine. Cambridge, MA: MIT Press, 1999.
    • (1999) Advances in kernel methods: Support vector machine
    • Mattera, D.1    Haykin, S.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.