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Volumn 57, Issue 1, 2013, Pages 17-26

Separation of deterministic signals using independent component analysis (ICA)

Author keywords

4th order cumulant; ICA; separation of deterministic signals

Indexed keywords

ALGORITHM; DATA SET; GEODESY; GEOPHYSICS; STOCHASTICITY;

EID: 84880774670     PISSN: 00393169     EISSN: None     Source Type: Journal    
DOI: 10.1007/s11200-012-0718-1     Document Type: Article
Times cited : (43)

References (21)
  • 2
    • 84857000969 scopus 로고    scopus 로고
    • Extracting independent local oscillatory geophysical signals by geodetic tropospheric delay
    • In: D. Behrend and K. D. Baver (Eds.), NASA/CP-2010-215864, Greenbelt, MD
    • Botai O. J., Combrinck L., Sivankumar V., Schuh H. and Böhm J., 2010. Extracting independent local oscillatory geophysical signals by geodetic tropospheric delay. In: D. Behrend and K. D. Baver (Eds.), International VLBI Service for Geodesy and Astrometry 2010 General Meeting Proceedings. NASA/CP-2010-215864, Greenbelt, MD, 345-354 (http://ivscc. gsfc. nasa. gov/publications/gm2010/botai).
    • (2010) International VLBI Service for Geodesy and Astrometry 2010 General Meeting Proceedings , pp. 345-354
    • Botai, O.J.1    Combrinck, L.2    Sivankumar, V.3    Schuh, H.4    Böhm, J.5
  • 3
    • 0032612381 scopus 로고    scopus 로고
    • High-order contrasts for independent component analysis
    • Cardoso J. F., 1999. High-order contrasts for independent component analysis. Neural Comput., 11, 157-192, DOI: 10. 1162/089976699300016863.
    • (1999) Neural Comput. , vol.11 , pp. 157-192
    • Cardoso, J.F.1
  • 4
    • 0027812550 scopus 로고
    • Blind beamforming for non-Gaussian signals
    • Cardoso J. F. and Souloumiac A., 1993. Blind beamforming for non-Gaussian signals. IEEE Proc. F, 140, 362-370, DOI: 10. 1. 1. 8. 5684.
    • (1993) IEEE Proc. F , vol.140 , pp. 362-370
    • Cardoso, J.F.1    Souloumiac, A.2
  • 6
    • 0028416938 scopus 로고
    • Independent component analysis, a new concept?
    • Comon P., 1994. Independent component analysis, a new concept? Signal Process., 36, 287-314, DOI: 10. 1016/0165-1684(94)90029-9.
    • (1994) Signal Process. , vol.36 , pp. 287-314
    • Comon, P.1
  • 7
    • 84862613223 scopus 로고    scopus 로고
    • Separation of global time-variable gravity signals into maximally independent components
    • Forootan E. and Kusche J., 2012. Separation of global time-variable gravity signals into maximally independent components. J. Geodesy, 86, 477-497, DOI: 10. 1007/s00190-011-0532-5.
    • (2012) J. Geodesy , vol.86 , pp. 477-497
    • Forootan, E.1    Kusche, J.2
  • 8
    • 84862772192 scopus 로고    scopus 로고
    • Independent patterns of water mass anomalies over Australia from satellite data and models
    • Forootan E., Awange J., Kusche J., Heck B. and Eicker A., 2012. Independent patterns of water mass anomalies over Australia from satellite data and models. Remote Sens. Environ., 124, 427-443, DOI: 0. 1016/j. rse. 2012. 05. 023.
    • (2012) Remote Sens. Environ. , vol.124 , pp. 427-443
    • Forootan, E.1    Awange, J.2    Kusche, J.3    Heck, B.4    Eicker, A.5
  • 9
    • 77958083021 scopus 로고    scopus 로고
    • An independent component analysis filtering approach for estimating continental hydrology in the GRACE gravity data
    • Frappart F., Ramillien G., Leblanc M., Tweed S. O., Bonnet M. P. and Maisongrande P., 2010a. An independent component analysis filtering approach for estimating continental hydrology in the GRACE gravity data. Remote Sens. Environ., 115, 187-204, DOI: 10. 1016/j. rse. 2010. 08. 017.
    • (2010) Remote Sens. Environ. , vol.115 , pp. 187-204
    • Frappart, F.1    Ramillien, G.2    Leblanc, M.3    Tweed, S.O.4    Bonnet, M.P.5    Maisongrande, P.6
  • 11
    • 0000466122 scopus 로고    scopus 로고
    • On independent component analysis
    • Hyvärinen A., 1999. On independent component analysis. Neural Comput. Surv., 2, 94-128.
    • (1999) Neural Comput. Surv. , vol.2 , pp. 94-128
    • Hyvärinen, A.1
  • 12
    • 0042826822 scopus 로고    scopus 로고
    • Independent component analysis: algorithms and applications
    • Hyvärinen A. and Oja E., 2000. Independent component analysis: algorithms and applications. Neural Netw., 13, 411-430.
    • (2000) Neural Netw. , vol.13 , pp. 411-430
    • Hyvärinen, A.1    Oja, E.2
  • 13
    • 78650936747 scopus 로고    scopus 로고
    • Separation of mixtures of complex sinusoidal signals with independent component analysis
    • Kirimoto T., Amishima T. and Okamura A., 2011. Separation of mixtures of complex sinusoidal signals with independent component analysis. IEICE Trans. Commun., 94-B, 215-221, DOI: 10. 1587/transcom. E94. B. 215.
    • (2011) IEICE Trans. Commun. , vol.94 B , pp. 215-221
    • Kirimoto, T.1    Amishima, T.2    Okamura, A.3
  • 16
    • 0029359578 scopus 로고
    • 4th-order criteria for blind sources separation
    • Mansour A. and Jutten C., 1995. 4th-order criteria for blind sources separation. IEEE Trans. Signal Process., 43, 2022-2025, DOI: 10. 1109/78. 403370.
    • (1995) IEEE Trans. Signal Process. , vol.43 , pp. 2022-2025
    • Mansour, A.1    Jutten, C.2
  • 17
    • 0030400237 scopus 로고    scopus 로고
    • Fourth-order cumulant based blind source separation
    • Nandi A. K. and Zarzoso V., 1996. Fourth-order cumulant based blind source separation. IEEE Signal Process. Lett., 3, 312-314, DOI: 10. 1109/97. 544786.
    • (1996) IEEE Signal Process. Lett. , vol.3 , pp. 312-314
    • Nandi, A.K.1    Zarzoso, V.2
  • 19
    • 84863852354 scopus 로고    scopus 로고
    • Resolving sea level contributions by identifying fingerprints in time-variable gravity and altimetry
    • Rietbroek R., Brunnabend S. E., Kusche J. and Schröter J., 2012. Resolving sea level contributions by identifying fingerprints in time-variable gravity and altimetry. J. Geodyn., 59-60, 72-81, DOI: 10. 1016/j. jog. 2011. 06. 007.
    • (2012) J. Geodyn. , vol.59-60 , pp. 72-81
    • Rietbroek, R.1    Brunnabend, S.E.2    Kusche, J.3    Schröter, J.4
  • 21
    • 0032675191 scopus 로고    scopus 로고
    • Blind separation of independent sources for virtually any source probability density function
    • Zarzoso V. and Nandi K., 1999. Blind separation of independent sources for virtually any source probability density function. IEEE Trans. Signal Process, 47, 2419-2432, DOI: 10. 1109/78. 782186.
    • (1999) IEEE Trans. Signal Process , vol.47 , pp. 2419-2432
    • Zarzoso, V.1    Nandi, K.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.