메뉴 건너뛰기




Volumn 5, Issue , 2004, Pages 4804-4809

Research of independent component analysis

Author keywords

Blind source separation; High order cumulant; Independent component analysis (ICA); Infomax; Maximum likelihood estimation; Mutual information; Negentropy

Indexed keywords

HIGH-ORDER CUMULANT; INFOMAX; MULTUAL INFORMATION; NEGENTROPY;

EID: 15744384855     PISSN: 1062922X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICSMC.2004.1401291     Document Type: Conference Paper
Times cited : (9)

References (30)
  • 3
    • 0032477880 scopus 로고    scopus 로고
    • Spatially independent activity patterns in functional MRI data during the Stroop color-naming task
    • February
    • Martin J.Mckeown, Tzyy-Ping Jung, Scott Makeig et al. Spatially independent activity patterns in functional MRI data during the Stroop color-naming task Proc Natl. Acad. Sci. USA Vol95,pp.803-810,February 1998
    • (1998) Proc Natl. Acad. Sci. USA , vol.95 , pp. 803-810
    • Martin, J.M.1    Jung, T.-P.2    Makeig, S.3
  • 4
    • 0029185402 scopus 로고
    • Adaptive separation of mixed broadband sound sources with delays by a beam-forming Herault-Jutten network
    • S.Li and T.J. Sejnowski, Adaptive separation of mixed broadband sound sources with delays by a beam-forming Herault-Jutten network, IEEE Journal of Oceanic Engineering Vol.20,No. 1, pp.73-79,1994
    • (1994) IEEE Journal of Oceanic Engineering , vol.20 , Issue.1 , pp. 73-79
    • Li, S.1    Sejnowski, T.J.2
  • 7
    • 0029938380 scopus 로고    scopus 로고
    • Emergence of simple-cell receptive field properties by learning a sparse code for natural images
    • B. A. Olshausen, D. J. Field., Emergence of simple-cell receptive field properties by learning a sparse code for natural images. Nature, 381:607-609, 1996.
    • (1996) Nature , vol.381 , pp. 607-609
    • Olshausen, B.A.1    Field, D.J.2
  • 8
    • 0032492432 scopus 로고    scopus 로고
    • Independent component filters of natural images compared with simple cells in primary visual cortex
    • J. H. van Hateren and A. van der Schaaf. Independent component filters of natural images compared with simple cells in primary visual cortex. Proc. Royal Society ser. B, 265:359-366, 1998.
    • (1998) Proc. Royal Society Ser. B , vol.265 , pp. 359-366
    • Van Hateren, J.H.1    Van Der Schaaf, A.2
  • 9
    • 0041849740 scopus 로고    scopus 로고
    • Independent component analysis applied to feature extraction from color and stereo images
    • Patrik O. Hoyer, Aapo Hyvärinen,Independent component analysis applied to feature extraction from color and stereo images, Network :Comput .Neural Syst.11 pp.191-210, 2000
    • (2000) Network: Comput. Neural Syst. , vol.11 , pp. 191-210
    • Hoyer, P.O.1    Hyvärinen, A.2
  • 12
    • 0028416938 scopus 로고
    • Independent component analysis - A new concept?
    • P.Comon, Independent component analysis - a new concept? Signal Processing,1994, 36:287 - 314
    • (1994) Signal Processing , vol.36 , pp. 287-314
    • Comon, P.1
  • 13
    • 0029411030 scopus 로고
    • An information maximisation approach to blind separation and blind deconvolution
    • Bell A.J. and Sejnowski T.J. An information maximisation approach to blind separation and blind deconvolution, Neural Computation.Vol.7, pp.1129-1159,1995
    • (1995) Neural Computation , vol.7 , pp. 1129-1159
    • Bell, A.J.1    Sejnowski, T.J.2
  • 14
    • 0031122399 scopus 로고    scopus 로고
    • Infomax and maximum likelihood for source separation
    • April
    • Jean-François Cardoso, Infomax and maximum likelihood for source separation, IEEE Letters on Signal Processing, Vol. 4, No. 4, pp. 112-114, April, 1997.
    • (1997) IEEE Letters on Signal Processing , vol.4 , Issue.4 , pp. 112-114
    • Cardoso, J.-F.1
  • 15
    • 0033556834 scopus 로고    scopus 로고
    • Independent component analysis using an extended infomax algorithm for mixed sub-gaussian and super-gaussian sources
    • T-W. Lee, M. Girolami and T.J. Sejnowski, Independent Component Analysis using an Extended Infomax Algorithm for Mixed Sub-Gaussian and Super-Gaussian Sources, Neural Computation, Vol.11,1999
    • (1999) Neural Computation , vol.11
    • Lee, T.-W.1    Girolami, M.2    Sejnowski, T.J.3
  • 16
    • 0000466122 scopus 로고    scopus 로고
    • Survey on independent component analysis
    • Aapo Hyvärinen, Survey on Independent Component Analysis, Neural Computing Surveys, pp.94-128,1999
    • (1999) Neural Computing Surveys , pp. 94-128
    • Hyvärinen, A.1
  • 18
    • 0036648194 scopus 로고    scopus 로고
    • Mutual information approach to blind separation of stationary sources
    • July
    • Dinh Tuan Pham, Mutual Information Approach to Blind Separation of Stationary Sources, IEEE transactions on information theory, Vol.48, No.7, pp. 1935-1946,July ,2002
    • (2002) IEEE Transactions on Information Theory , vol.48 , Issue.7 , pp. 1935-1946
    • Pham, D.T.1
  • 22
    • 15744369724 scopus 로고    scopus 로고
    • Fast algorithms for mutual information based independent component analysis
    • August
    • Dinh-Tuan Pham, Fast algorithms for Mutual Information Based Independent Component Analysis, IEEE transactions on Signal Processing, August 2002
    • (2002) IEEE Transactions on Signal Processing
    • Pham, D.-T.1
  • 23
    • 5644280210 scopus 로고    scopus 로고
    • An improved Infomax algorithm of independent component analysis applied to fMRI data
    • San Diego,California USA
    • Xia Wu, Li Yao, Zh.Y.Long, An improved Infomax algorithm of independent component analysis applied to fMRI data, SPIE International Symposium Medical Imaging 2004,San Diego,California USA, 2004
    • (2004) SPIE International Symposium Medical Imaging 2004
    • Wu, X.1    Yao, L.2    Long, Zh.Y.3
  • 24
    • 0003168213 scopus 로고
    • Learningin nonlinear constrained Hebbian networks
    • T. Kohonen et al., editor, Espoo, Finland, North-Holland, Amsterdam
    • E. Oja, H. Ogawa, and J. Wangviwattana., Learningin nonlinear constrained Hebbian networks. In T. Kohonen et al., editor, Artificial Neural Networks, Proc. ICANN'91, pp. 385-390, Espoo, Finland, 1991. North-Holland, Amsterdam.
    • (1991) Artificial Neural Networks, Proc. ICANN'91 , pp. 385-390
    • Oja, E.1    Ogawa, H.2    Wangviwattana, J.3
  • 25
    • 0029061996 scopus 로고
    • Generalizations of principal component analysis, optimization problems, and neural networks
    • J. Karhunen and J. Joutsensalo. Generalizations of principal component analysis, optimization problems, and neural networks. Neural Networks, Vol.8, No.4, pp.549-562, 1995.
    • (1995) Neural Networks , vol.8 , Issue.4 , pp. 549-562
    • Karhunen, J.1    Joutsensalo, J.2
  • 26
    • 0343416807 scopus 로고    scopus 로고
    • The nonlinear PCA learning rule in independent component analysis
    • E. Oja. The nonlinear PCA learning rule in independent component analysis. Neurocomputing, Vol.17,No.1,pp.25-46, 1997.
    • (1997) Neurocomputing , vol.17 , Issue.1 , pp. 25-46
    • Oja, E.1
  • 29
    • 0026866246 scopus 로고
    • Current-Mode subthreshold MOS implementation of the Herault-Jutten autoadaptive network
    • 1994
    • M.H. Cohen and A.G Andreou (1994), Current-Mode subthreshold MOS implementation of the Herault-Jutten autoadaptive network, IEEE J. Solid-State Circuits Vol.27,No.5,714-727,1994
    • (1994) IEEE J. Solid-State Circuits , vol.27 , Issue.5 , pp. 714-727
    • Cohen, M.H.1    Andreou, A.G.2
  • 30
    • 15744369964 scopus 로고    scopus 로고
    • Implementation of Infomax ICA Algorithm with Analog CMOS circuits
    • Ki-Seok Cho, Soo-Young Lee, Kaist, Tae-Jon, Implementation of Infomax ICA Algorithm with Analog CMOS circuits, ICA Conf. 2001
    • (2001) ICA Conf.
    • Cho, K.-S.1    Lee, S.-Y.2    Kaist, T.-J.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.