Independent Component Analysis A Hyvärinen, J Karhunen, E Oja John Wiley & Sons, inc., 2001 | 38302* | 2001 |

Simplified neuron model as a principal component analyzer E Oja Journal of mathematical biology 15, 267-273, 1982 | 3385 | 1982 |

A new curve detection method: randomized Hough transform (RHT) L Xu, E Oja, P Kultanen Pattern recognition letters 11 (5), 331-338, 1990 | 1621 | 1990 |

Subspace methods of pattern recognition E Oja (No Title), 1983 | 1314 | 1983 |

Engineering applications of the self-organizing map T Kohonen, E Oja, O Simula, A Visa, J Kangas Proceedings of the IEEE 84 (10), 1358-1384, 1996 | 1226 | 1996 |

Neural networks, principal components, and subspaces E Oja International journal of neural systems 1 (01), 61-68, 1989 | 1224 | 1989 |

Principal components, minor components, and linear neural networks E Oja Neural networks 5 (6), 927-935, 1992 | 1180 | 1992 |

Independent component approach to the analysis of EEG and MEG recordings R Vigário, J Sarela, V Jousmiki, M Hamalainen, E Oja IEEE transactions on biomedical engineering 47 (5), 589-593, 2000 | 1020 | 2000 |

Randomized Hough transform (RHT): basic mechanisms, algorithms, and computational complexities L Xu, E Oja CVGIP: Image understanding 57 (2), 131-154, 1993 | 897 | 1993 |

Rival penalized competitive learning for clustering analysis, RBF net, and curve detection L Xu, A Krzyzak, E Oja IEEE Transactions on Neural networks 4 (4), 636-649, 1993 | 876 | 1993 |

On stochastic approximation of the eigenvectors and eigenvalues of the expectation of a random matrix E Oja, J Karhunen Journal of mathematical analysis and applications 106 (1), 69-84, 1985 | 745 | 1985 |

A class of neural networks for independent component analysis J Karhunen, E Oja, L Wang, R Vigario, J Joutsensalo IEEE Transactions on neural networks 8 (3), 486-504, 1997 | 647 | 1997 |

Sparse code shrinkage: Denoising by nonlinear maximum likelihood estimation A Hyvärinen, P Hoyer, E Oja Advances in Neural Information Processing Systems 11, 1998 | 595 | 1998 |

Efficient variant of algorithm FastICA for independent component analysis attaining the Cramér-Rao lower bound Z Koldovsky, P Tichavsky, E Oja IEEE Transactions on neural networks 17 (5), 1265-1277, 2006 | 433 | 2006 |

Texture discrimination with multidimensional distributions of signed gray-level differences T Ojala, K Valkealahti, E Oja, M Pietikäinen Pattern Recognition 34 (3), 727-739, 2001 | 382 | 2001 |

Probabilistic and non-probabilistic Hough transforms: overview and comparisons H Kälviäinen, P Hirvonen, L Xu, E Oja Image and vision computing 13 (4), 239-252, 1995 | 357 | 1995 |

Clustering properties of hierarchical self-organizing maps J Lampinen, E Oja Journal of Mathematical Imaging and vision 2, 261-272, 1992 | 354 | 1992 |

Self-organizing hierarchical feature maps P Koikkalainen, E Oja 1990 IJCNN international joint conference on neural networks, 279-284, 1990 | 342 | 1990 |

Modified Hebbian learning for curve and surface fitting L Xu, E Oja, CY Suen Neural Networks 5 (3), 441-457, 1992 | 335 | 1992 |

The nonlinear PCA learning rule in independent component analysis E Oja Neurocomputing 17 (1), 25-45, 1997 | 334 | 1997 |