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Cited by 8,705

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Independent component analysis: algorithms and applications

Hyvärinen, A., Oja, E.·2000·Neural Networks
DOI 10.1016/s0893-6080(00)00026-5
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Research works printed but not linked: 33

  1. Back, 1998, A first application of independent component analysis to extracting structure from stock returns, International Journal on Neural Systems, 8, 473, 10.1142/S0129065797000458 · DOI · Paper page
  2. Bell, 1997, The ‘independent components’ of natural scenes are edge filters, Vision Research, 37, 3327, 10.1016/S0042-6989(97)00121-1 · DOI · Paper page
  3. Cardoso, 1997, Infomax and maximum likelihood for source separation, IEEE Letters on Signal Processing, 4, 112, 10.1109/97.566704 · DOI · Paper page
  4. Cardoso, 1996, Equivariant adaptive source separation, IEEE Transactions on Signal Processing, 44, 3017, 10.1109/78.553476 · DOI · Paper page
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  6. Comon, 1994, Independent component analysis—a new concept?, Signal Processing, 36, 287, 10.1016/0165-1684(94)90029-9 · DOI · Paper page
  7. Cristescu, R., Ristaniemi, T., Joutsensalo, J., & Karhunen, J. (2000). Delay estimation in CDMA communications using a Fast ICA algorithm. Proceedings of the International Workshop on Independent Component Analysis and Blind Signal Separation (ICA2000). Helsinki, Finland. In press.
  8. Delfosse, 1995, Adaptive blind separation of independent sources: a deflation approach, Signal Processing, 45, 59, 10.1016/0165-1684(95)00042-C · DOI
  9. Donoho, 1995, Wavelet shrinkage: asymptopia?, Journal of the Royal Statistical Society, Series B, 57, 301, 10.1111/j.2517-6161.1995.tb02032.x · DOI · Paper page
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  11. Friedman, 1974, A projection pursuit algorithm for exploratory data analysis, IEEE Transactions of Computers, c-23, 881, 10.1109/T-C.1974.224051 · DOI · Paper page
  12. Giannakopoulos, X., Karhunen, J., & Oja, E. (1998). Experimental comparison of neural ICA algorithms. Proceedings of the International Conference on Artificial Neural Networks (ICANN’98) (pp. 651–656). Skövde, Sweden. · doi:10.1007/978-1-4471-1599-1_99
  13. Hyvärinen, 1998, Independent component analysis in the presence of Gaussian noise by maximizing joint likelihood, Neurocomputing, 22, 49, 10.1016/S0925-2312(98)00049-6 · DOI · Paper page
  14. Hyvärinen, 1999, Fast and robust fixed-point algorithms for independent component analysis, IEEE Transactions on Neural Networks, 10, 626, 10.1109/72.761722 · DOI · Paper page
  15. Hyvärinen, 1999, The fixed-point algorithm and maximum likelihood estimation for independent component analysis, Neural Processing Letters, 10, 1, 10.1023/A:1018647011077 · DOI · Paper page
  16. Hyvärinen, 1999, Gaussian moments for noisy independent component analysis, IEEE Signal Processing Letters, 6, 145, 10.1109/97.763148 · doi:10.1109/97.763148
  17. Hyvärinen, 1999, Sparse code shrinkage: denoising of nonGaussian data by maximum likelihood estimation, Neural Computation, 11, 1739, 10.1162/089976699300016214 · DOI · Paper page
  18. Hyvärinen, 1999, Survey on independent component analysis, Neural Computing Surveys, 2, 94
  19. Hyvärinen, 1997, A fast fixed-point algorithm for independent component analysis, Neural Computation, 9, 1483, 10.1162/neco.1997.9.7.1483 · DOI · Paper page
  20. Hyvärinen, 1998, Independent component analysis by general nonlinear Hebbian-like learning rules, Signal Processing, 64, 301, 10.1016/S0165-1684(97)00197-7 · DOI
  21. Hyvärinen, A., Särelä, J., & Vigário, R. (1999). Spikes and bumps: Artefacts generated by independent component analysis with insufficient sample size. Proceedings of the International Workshop on Independent Component Analysis and Signal Separation (ICA’99) (pp. 425–429). Aussois, France.
  22. Hyvärinen, A., Hoyer, P. O., & Oja, E. (2000). Image denoising by sparse code shrinkage. In S. Haykin & B. Kosko (Eds.), New York: IEEE Press (in press).
  23. Jones, 1987, What is projection pursuit?, Journal of the Royal Statistical Society, Series A, 150, 1, 10.2307/2981662 · DOI · Paper page
  24. Jutten, 1991, Blind separation of sources, part I: an adaptive algorithm based on neuromimetic architecture, Signal Processing, 24, 1, 10.1016/0165-1684(91)90079-X · DOI · Paper page
  25. Karhunen, 1997, A class of neural networks for independent component analysis, IEEE Transactions on Neural Networks, 8, 486, 10.1109/72.572090 · DOI · Paper page
  26. Kiviluoto, K., & Oja, E. (1998). Independent component analysis for parallel financial time series. Proceedings of the International Conference on Neural Information Processing (ICONIP’98) Vol. 2 (pp. 895–898). Tokyo, Japan.
  27. Lee, 1999, Independent component analysis using an extended infomax algorithm for mixed sub-Gaussian and super-Gaussian sources, Neural Computation, 11, 417, 10.1162/089976699300016719 · DOI · Paper page
  28. Mallat, 1989, A theory for multiresolution signal decomposition: the wavelet representation, IEEE Transactions on PAMI, 11, 674, 10.1109/34.192463 · DOI · Paper page
  29. Nadal, 1994, Non-linear neurons in the low noise limit: a factorial code maximizes information transfer, Network, 5, 565, 10.1088/0954-898X/5/4/008 · doi:10.1088/0954-898x/5/4/008 · Paper page
  30. Pham, D.-T., Garrat, P., & Jutten, C. (1992). Separation of a mixture of independent sources through a maximum likelihood approach. Proceedings EUSIPCO (pp. 771–774).
  31. Ristaniemi, T., & Joutsensalo, J. (1999). On the performance of blind source separation in CDMA downlink. Proceedings of the International Workshop on Independent Component Analysis and Signal Separation (ICA ’99) (pp. 437–441). Aussois, France.
  32. Vigário, 1997, Extraction of ocular artifacts from EEG using independent component analysis, Electroencephalography and Clinical Neurophysiology, 103, 395, 10.1016/S0013-4694(97)00042-8 · DOI · Paper page
  33. Vigário, R., Särelä, J. & Oja, E. (1998b). Independent component analysis in wave decomposition of auditory evoked fields. Proceedings of the International Conference on Artificial Neural Networks (ICANN’98) (pp. 287–292). Skövde, Sweden. · doi:10.1007/978-1-4471-1599-1_41

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Metadata

Authors
Hyvärinen, A., & Oja, E.
Venue
Neural Networks
Publisher
Elsevier BV
Published
2000-06
Volume
13
Issue
4-5
Pages
411-430
ISSN
0893-6080 (ISSN-L)
DOI
10.1016/s0893-6080(00)00026-5
OpenAlex
W2123649031
Cited by
8,705
References
3
FWCI
92.09
Type
journal article
Language
en
Open access
closed
Licence
www.elsevier.com/tdm/userlicense/1.0/ (tdm)

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Hyvärinen, A., & Oja, E. (2000). Independent component analysis: algorithms and applications. Neural Networks. https://doi.org/10.1016/s0893-6080(00)00026-5

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