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Volumn 4, Issue , 2006, Pages

Independent component analysis and time-frequency method for noisy EEG signal analysis

Author keywords

[No Author keywords available]

Indexed keywords

ELECTROENCEPHALOGRAPHY; SIGNAL PROCESSING; SPURIOUS SIGNAL NOISE;

EID: 34249284827     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICOSP.2006.345938     Document Type: Conference Paper
Times cited : (1)

References (10)
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    • 0037441741 scopus 로고    scopus 로고
    • Analysis of EEG records in an epileptic patient using wavelet transform
    • Hojjat A. and Ziqin Z. "Analysis of EEG records in an epileptic patient using wavelet transform", Journal of Neuroscience Methods, 123, pp. 69- 87, 2003.
    • (2003) Journal of Neuroscience Methods , vol.123 , pp. 69-87
    • Hojjat, A.1    Ziqin, Z.2
  • 2
    • 32544446152 scopus 로고    scopus 로고
    • EEG classification using generative independent component analysis
    • Silvia C. and David B. "EEG classification using generative independent component analysis", Neurocomputing,69, pp.769-777, 2006.
    • (2006) Neurocomputing , vol.69 , pp. 769-777
    • Silvia, C.1    David, B.2
  • 3
    • 16244408617 scopus 로고    scopus 로고
    • A method for detection of Alzheimer's disease using ICA-enhanced EEG measurements
    • Co M. and Alexander Y. "A method for detection of Alzheimer's disease using ICA-enhanced EEG measurements", Artificial Intelligence in Medicine,33, pp.209-222,2005.
    • (2005) Artificial Intelligence in Medicine , vol.33 , pp. 209-222
    • Co, M.1    Alexander, Y.2
  • 4
    • 0036468495 scopus 로고    scopus 로고
    • Independent component analysis: An introduction
    • James and Stone V. "Independent component analysis: an introduction", TRENDS in Cognitive Sciences, 6(2), pp.59-64, 2002.
    • (2002) TRENDS in Cognitive Sciences , vol.6 , Issue.2 , pp. 59-64
    • James1    Stone, V.2
  • 5
    • 0034551787 scopus 로고    scopus 로고
    • Independent component analysis for noisy data MEG data analysis
    • Ikeda and Toyama. "Independent component analysis for noisy data MEG data analysis", Neural Networks, 13 ,pp. 1063- 1074, 2000.
    • (2000) Neural Networks , vol.13 , pp. 1063-1074
    • Ikeda1    Toyama2
  • 7
    • 10244270619 scopus 로고    scopus 로고
    • Classification of individual trials based on the best independent component of EEG-recorded sentences
    • Dik K. W. and Marcos P. G. "Classification of individual trials based on the best independent component of EEG-recorded sentences", Neurocomputing, 61 ,pp.479-484, 2004.
    • (2004) Neurocomputing , vol.61 , pp. 479-484
    • Dik, K.W.1    Marcos, P.G.2
  • 8
    • 0037508535 scopus 로고    scopus 로고
    • Wigner distributions (nearly) everywhere: Time-frequency analysis of signals, systems, random processes, signal spaces, and frames
    • Matz G. and Hlawatsch F. "Wigner distributions (nearly) everywhere: time-frequency analysis of signals, systems, random processes", signal spaces, and frames, Signal Processing, 83, pp.1355-1378, 2003.
    • (2003) Signal Processing , vol.83 , pp. 1355-1378
    • Matz, G.1    Hlawatsch, F.2
  • 9
    • 0037504167 scopus 로고    scopus 로고
    • Time-frequency analysis as asymptotic method
    • David V. "Time-frequency analysis as asymptotic method", Journal of the Franklin Institute , 340 ,pp.77-86,2003.
    • (2003) Journal of the Franklin Institute , vol.340 , pp. 77-86
    • David, V.1
  • 10
    • 0035975673 scopus 로고    scopus 로고
    • Phase and amplitude analysis in time-frequency space - application to voluntary finger movement
    • Ginter J. and Blinowska K. J. "Phase and amplitude analysis in time-frequency space - application to voluntary finger movement", Journal of Neuroscience Methods, 110, pp. 113-124, 2001.
    • (2001) Journal of Neuroscience Methods , vol.110 , pp. 113-124
    • Ginter, J.1    Blinowska, K.J.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.