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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 한국자료분석학회 Journal of The Korean Data Analysis Society Journal of The Korean Data Analysis Society 제21권 제6호
- 발행연도
- 2019.1
- 수록면
- 2,721 - 2,735 (15page)
이용수
초록· 키워드
오류제보하기
For estimating the original signals only through observing the mixed data, independent component analysis (ICA) is a useful dimension reduction method, since it contains more statistical concepts: independence and non-Gaussianity. In other words, it does not end up in solving (generalized) eigenvalue problems, which are mostly restricted in considering up to the second moment as many other dimension reduction methods are. In this paper, we reviewed and explored various methods of ICA, such as Fast-ICA, Infomax-ICA, joint approximate diagonalization of eigenmatrices ICA (JADE ICA), product density estimation ICA (ProDenICA), and distance covariance ICA (dCovICA). We also proposed a method based on ball covariance, called B-dCovICA. Compared to other methods, B-dCovICA showed relatively high performance, supported by the higher accuracy of results when applied to simulated/real data. B-dCovICA is better than dCovICA, in that a non-parametric way is used to measure dependence, yet showed higher accuracy than dCovICA.
목차
등록된 정보가 없습니다.
참고문헌 (23)
참고문헌 신청
Amari, S. I. / 1996 / A new learning algorithm for blind signal separation / Advances in Neural Information Processing Systems 8:757~763
Bach, F. R. / 2002 / Kernel independent component analysis / Journal of Machine Learning Research 3:1~48
Bell, A. J. / 1995 / An information-maximization approach to blind separation and blind deconvolution / Neural Computation 7(6):1129~1159
Cardoso, J. F. / 1993 / Blind beamforming for non-gaussian signals / IEE Proceedings F(Radar and Signal Processing) 140(6):362~370
최필근 / 2012 / Estimating Structural Dimensionality using Contour Regression / Journal of The Korean Data Analysis Society 14(2):577~586
Bach, F. R. / 2002 / Kernel independent component analysis / Journal of Machine Learning Research 3:1~48
Bell, A. J. / 1995 / An information-maximization approach to blind separation and blind deconvolution / Neural Computation 7(6):1129~1159
Cardoso, J. F. / 1993 / Blind beamforming for non-gaussian signals / IEE Proceedings F(Radar and Signal Processing) 140(6):362~370
최필근 / 2012 / Estimating Structural Dimensionality using Contour Regression / Journal of The Korean Data Analysis Society 14(2):577~586
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