Independent component analysis: Algorithms and applications

Neural Networks

Volumn 13, Issue 4-5, 2000, Pages 411-430

  Hyvarinen A ^a   Oja, E ^a  

^a AALTO UNIVERSITY   (Finland)

Author keywords

Blind signal separation; Factor analysis; Independent component analysis; Projection pursuit; Representation; Source separation

Indexed keywords

ALGORITHMS; FEATURE EXTRACTION; MATHEMATICAL TRANSFORMATIONS; STATISTICAL METHODS;

BLIND SIGNAL SEPARATION; FACTOR ANALYSIS; INDEPENDENT COMPONENT ANALYSIS;

NEURAL NETWORKS;

ALGORITHM; ARTIFICIAL NEURAL NETWORK; BINOCULAR CONVERGENCE; DEFENSE MECHANISM; ELECTROENCEPHALOGRAM; FACTORIAL ANALYSIS; IMAGE PROCESSING; MULTIVARIATE ANALYSIS; PRINCIPAL COMPONENT ANALYSIS; PRIORITY JOURNAL; PROBABILITY; REVIEW; STATISTICS;

EID: 0042826822     PISSN: 08936080     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0893-6080(00)00026-5     Document Type: Article

References (45)

1. Amari S.-I., Cichocki A., Yang H. A new learning algorithm for blind source separation. Advances in Neural Information Processing Systems. 1996;Cambridge, MA, MIT Press. (pp. 757-763).
2. Back A.D., Weigend A.S. A first application of independent component analysis to extracting structure from stock returns. International Journal on Neural Systems. 8:(4):1998;473-484.
3. Bell A., Sejnowski T. An information-maximization approach to blind separation and blind deconvolution. Neural Computation. 7:1995;1129-1159.
4. Bell A., Sejnowski T. The 'independent components' of natural scenes are edge filters. Vision Research. 37:1997;3327-3338.
5. Cardoso J.-F. Infomax and maximum likelihood for source separation. IEEE Letters on Signal Processing. 4:1997;112-114.
6. Cardoso J.-F., Laheld B.H. Equivariant adaptive source separation. IEEE Transactions on Signal Processing. 44:(12):1996;3017-3030.
7. Cichocki A., Unbehauen R. Robust neural networks with on-line learning for blind identification and blind separation of sources. IEEE Transactions on Circuits and Systems. 43:(11):1996;894-906.
8. Comon P. Independent component analysis - a new concept? Signal Processing. 36:1994;287-314.
9. Cover T.M., Thomas J.A. Elements of information theory. 1991;Wiley, New York.
10. 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.
11. Delfosse N., Loubaton P. Adaptive blind separation of independent sources: a deflation approach. Signal Processing. 45:1995;59-83.
12. Donoho D.L., Johnstone I.M., Kerkyacharian G., Picard D. Wavelet shrinkage: asymptopia? Journal of the Royal Statistical Society, Series B. 57:1995;301-337.
13. Friedman J. Exploratory projection pursuit. Journal of the American Statistical Association. 82:(397):1987;249-266.
14. Friedman J.H., Tukey J.W. A projection pursuit algorithm for exploratory data analysis. IEEE Transactions of Computers. c-23:(9):1974;881-890.
15. 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.
16. Gonzalez R., Wintz P. Digital image processing. 1987;Addison-Wesley, Reading, MA.
17. Huber P. Projection pursuit. The Annals of Statistics. 13:(2):1985;435-475.
18. Hyvärinen A. Independent component analysis in the presence of Gaussian noise by maximizing joint likelihood. Neurocomputing. 22:1998;49-67.
19. Hyvärinen A. New approximations of differential entropy for independent component analysis and projection pursuit. Advances in Neural Information Processing Systems. 1998;MIT Press, Cambridge, MA. (pp. 273-279).
20. Hyvärinen A. Fast and robust fixed-point algorithms for independent component analysis. IEEE Transactions on Neural Networks. 10:(3):1999;626-634.
21. Hyvärinen A. The fixed-point algorithm and maximum likelihood estimation for independent component analysis. Neural Processing Letters. 10:(1):1999;1-5.
22. Hyvärinen A. Gaussian moments for noisy independent component analysis. IEEE Signal Processing Letters. 6:(6):1999;145-147.
23. Hyvärinen A. Sparse code shrinkage: denoising of nonGaussian data by maximum likelihood estimation. Neural Computation. 11:(7):1999;1739-1768.
24. Hyvärinen A. Survey on independent component analysis. Neural Computing Surveys. 2:1999;94-128.
25. Hyvärinen A., Oja E. A fast fixed-point algorithm for independent component analysis. Neural Computation. 9:(7):1997;1483-1492.
26. Hyvärinen A., Oja E. Independent component analysis by general nonlinear Hebbian-like learning rules. Signal Processing. 64:(3):1998;301-313.
27. 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.
28. 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).
29. Jones M., Sibson R. What is projection pursuit? Journal of the Royal Statistical Society, Series A. 150:1987;1-36.
30. Jutten C., Herault J. Blind separation of sources, part I: an adaptive algorithm based on neuromimetic architecture. Signal Processing. 24:1991;1-10.
31. Karhunen J., Oja E., Wang L., Vigário R., Joutsensalo J. A class of neural networks for independent component analysis. IEEE Transactions on Neural Networks. 8:(3):1997;486-504.
32. 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.
33. Lee T.-W., Girolami M., Sejnowski T.J. Independent component analysis using an extended infomax algorithm for mixed sub-Gaussian and super-Gaussian sources. Neural Computation. 11:(2):1999;417-441.
34. Luenberger D.G. Optimization by vector space methods. 1969;Wiley, New York.
35. Makeig S., Bell A., Jung T.-P., Sejnowski T.-J. Independent component analysis of electroencephalographic data. Advances in Neural Information Processing Systems. 1996;MIT Press, Cambridge, MA. (pp. 145-151).
36. Mallat S.G. A theory for multiresolution signal decomposition: the wavelet representation. IEEE Transactions on PAMI. 11:1989;674-693.
37. Nadal J.-P., Parga N. Non-linear neurons in the low noise limit: a factorial code maximizes information transfer. Network. 5:1994;565-581.
38. Olshausen B.A., Field D.J. Emergence of simple-cell receptive field properties by learning a sparse code for natural images. Nature. 381:1996;607-609.
39. Papoulis A. Probability, random variables, and stochastic processes. 3rd ed. 1991;McGraw-Hill, New York.
40. Pearlmutter B.A., Parra L.C. Maximum likelihood blind source separation: a context-sensitive generalization of ica. Advances in Neural Information Processing Systems. 1997;. (pp. 613-619).
41. 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).
42. 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.
43. Vigário R. Extraction of ocular artifacts from EEG using independent component analysis. Electroencephalography and Clinical Neurophysiology. 103:(3):1997;395-404.
44. Vigário R., Jousmäki V., Hämäläinen M., Hari R., Oja E. Independent component analysis for identification of artifacts in magnetoencephalographic recordings. Advances in Neural Information Processing Systems. 1998;MIT Press, Cambridge, MA. (pp. 229-235).
45. 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.