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Volumn 84, Issue 2, 2004, Pages 267-282

Hierarchical models of variance sources

Author keywords

Blind source separation; Factor analysis; Hierarchical model; Variance modelling; Variational Bayesian learning

Indexed keywords

BLIND SOURCE SEPARATION; CONVERGENCE OF NUMERICAL METHODS; DATA REDUCTION; HIERARCHICAL SYSTEMS; INDEPENDENT COMPONENT ANALYSIS; ITERATIVE METHODS; LEARNING ALGORITHMS; MATHEMATICAL MODELS; MAXIMUM LIKELIHOOD ESTIMATION; OPTIMIZATION; PARAMETER ESTIMATION; PROBABILITY DENSITY FUNCTION; SYSTEM STABILITY; VARIATIONAL TECHNIQUES; VECTORS;

EID: 0346724352     PISSN: 01651684     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.sigpro.2003.10.014     Document Type: Conference Paper
Times cited : (33)

References (28)
  • 1
    • 0033561886 scopus 로고    scopus 로고
    • Independent factor analysis
    • Attias H. Independent factor analysis. Neural Comput. 11(4):1999;803-851.
    • (1999) Neural Comput. , vol.11 , Issue.4 , pp. 803-851
    • Attias, H.1
  • 2
    • 0000065017 scopus 로고    scopus 로고
    • Ensemble learning in Bayesian neural networks
    • C. Bishop. Berlin: Springer
    • Barber D., Bishop C. Ensemble learning in Bayesian neural networks. Bishop C. Neural Networks and Machine Learning. 1998;215-237 Springer, Berlin.
    • (1998) Neural Networks and Machine Learning , pp. 215-237
    • Barber, D.1    Bishop, C.2
  • 3
    • 42449156579 scopus 로고
    • Generalized autoregressive conditional heteroskedasticity
    • Bollerslev T. Generalized autoregressive conditional heteroskedasticity. J. Econometrics. 31:1986;307-327.
    • (1986) J. Econometrics , vol.31 , pp. 307-327
    • Bollerslev, T.1
  • 8
    • 0346305993 scopus 로고    scopus 로고
    • FastICA, The FastICA MATLAB package, 1998. Available at http://www.cis.hut.fi/projects/ica/fastica/.
    • (1998) The FastICA MATLAB Package
  • 9
    • 0034170950 scopus 로고    scopus 로고
    • Variational learning for switching state-space models
    • Ghahramani Z., Hinton G.E. Variational learning for switching state-space models. Neural Comput. 12(4):2000;963-996.
    • (2000) Neural Comput. , vol.12 , Issue.4 , pp. 963-996
    • Ghahramani, Z.1    Hinton, G.E.2
  • 10
    • 67649497847 scopus 로고    scopus 로고
    • Stochastic volatility
    • C.R. Rao, & G.S. Maddala. Amsterdam: North-Holland
    • Ghysels E., Harvey A.C., Renault E. Stochastic volatility. Rao C.R., Maddala G.S. Statistical Methods in Finance. 1996;119-191 North-Holland, Amsterdam.
    • (1996) Statistical Methods in Finance , pp. 119-191
    • Ghysels, E.1    Harvey, A.C.2    Renault, E.3
  • 11
    • 0038132749 scopus 로고    scopus 로고
    • Variational method for learning sparse and overcomplete representations
    • Girolami M. Variational method for learning sparse and overcomplete representations. Neural Comput. 13(11):2001;2517-2532.
    • (2001) Neural Comput. , vol.13 , Issue.11 , pp. 2517-2532
    • Girolami, M.1
  • 13
    • 0038173234 scopus 로고    scopus 로고
    • Accelerating cyclic update algorithms for parameter estimation by pattern searches
    • Honkela A., Valpola H., Karhunen J. Accelerating cyclic update algorithms for parameter estimation by pattern searches. Neural Process. Lett. 17(2):2003;191-203.
    • (2003) Neural Process. Lett. , vol.17 , Issue.2 , pp. 191-203
    • Honkela, A.1    Valpola, H.2    Karhunen, J.3
  • 14
    • 0034222304 scopus 로고    scopus 로고
    • Emergence of phase and shift invariant features by decomposition of natural images into independent feature subspaces
    • Hyvärinen A., Hoyer P. Emergence of phase and shift invariant features by decomposition of natural images into independent feature subspaces. Neural Comput. 12(7):2000;1705-1720.
    • (2000) Neural Comput. , vol.12 , Issue.7 , pp. 1705-1720
    • Hyvärinen, A.1    Hoyer, P.2
  • 15
    • 25944467692 scopus 로고    scopus 로고
    • Blind separation of sources that have spatiotemporal dependencies
    • submitted for publication
    • A. Hyvärinen, J. Hurri, Blind separation of sources that have spatiotemporal dependencies, Signal Processing, (2003) submitted for publication.
    • (2003) Signal Processing
    • Hyvärinen, A.1    Hurri, J.2
  • 19
    • 0001251517 scopus 로고    scopus 로고
    • Stochastic volatility: Likelihood inference and comparison with ARCH models
    • July
    • Kim S., Shepard N., Chib S. Stochastic volatility. likelihood inference and comparison with ARCH models Rev. Econ. Stud. 65(3):July 1998;361-393.
    • (1998) Rev. Econ. Stud. , vol.65 , Issue.3 , pp. 361-393
    • Kim, S.1    Shepard, N.2    Chib, S.3
  • 20
    • 0000761101 scopus 로고    scopus 로고
    • Self-organized formation of various invariant-feature filters in the adaptive-subspace SOM
    • Kohonen T., Kaski S., Lappalainen H. Self-organized formation of various invariant-feature filters in the adaptive-subspace SOM. Neural Comput. 9(6):1997;1321-1344.
    • (1997) Neural Comput. , vol.9 , Issue.6 , pp. 1321-1344
    • Kohonen, T.1    Kaski, S.2    Lappalainen, H.3
  • 22
    • 0006397661 scopus 로고    scopus 로고
    • Ensemble learning for blind image separation and deconvolution
    • M. Girolami. Berlin: Springer
    • Miskin J., MacKay D.J.C. Ensemble learning for blind image separation and deconvolution. Girolami M. Advances in Independent Component Analysis. 2000;123-141 Springer, Berlin.
    • (2000) Advances in Independent Component Analysis , pp. 123-141
    • Miskin, J.1    Mackay, D.J.C.2
  • 23
    • 84898988668 scopus 로고    scopus 로고
    • Higher-order statistical properties arising from the non-stationarity of natural signals
    • T. Leen, T. Dietterich, V. Tresp (Eds.), The MIT Press, Cambridge, MA, USA
    • L. Parra, C. Spence, P. Sajda, Higher-order statistical properties arising from the non-stationarity of natural signals, in: T. Leen, T. Dietterich, V. Tresp (Eds.), Advances in Neural Information Processing Systems, Vol. 13, The MIT Press, Cambridge, MA, USA, 2001, pp. 786-792.
    • (2001) Advances in Neural Information Processing Systems , vol.13 , pp. 786-792
    • Parra, L.1    Spence, C.2    Sajda, P.3
  • 25
    • 0038132747 scopus 로고    scopus 로고
    • An unsupervised ensemble learning method for nonlinear dynamic state-space models
    • Valpola H., Karhunen J. An unsupervised ensemble learning method for nonlinear dynamic state-space models. Neural Comput. 14(11):2002;2647-2692.
    • (2002) Neural Comput. , vol.14 , Issue.11 , pp. 2647-2692
    • Valpola, H.1    Karhunen, J.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.