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Christian Jutten: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Jordi Solé i Casals, Anisse Taleb, Christian Jutten
    Parametric approach to blind deconvolution of nonlinear channels. [Citation Graph (0, 0)][DBLP]
    ESANN, 2000, pp:21-26 [Conf]
  2. Massoud Babaie-Zadeh, Christian Jutten
    Semi-Blind Approaches for Source Separation and Independent component Analysis. [Citation Graph (0, 0)][DBLP]
    ESANN, 2006, pp:301-312 [Conf]
  3. Christian Jutten
    From source separation to ICA: an introduction to the special session. [Citation Graph (0, 0)][DBLP]
    ESANN, 1997, pp:- [Conf]
  4. Shahram Hosseini, Christian Jutten
    Improving neural network estimation in presence of non i.i.d. noise. [Citation Graph (0, 0)][DBLP]
    ESANN, 1998, pp:327-332 [Conf]
  5. Anisse Taleb, Christian Jutten
    Nonlinear source separation: the post-nonlinear mixtures. [Citation Graph (0, 0)][DBLP]
    ESANN, 1997, pp:- [Conf]
  6. Vincent Vigneron, Sebastien Lagrange, Christian Jutten
    Acceptability conditions for BSS problems. [Citation Graph (0, 0)][DBLP]
    ESANN, 2003, pp:143-148 [Conf]
  7. Christian Jutten, A. Guérin, Jeanny Hérault
    Simulation Machine and Integrated Implementation of Neural Networks: a Review of Methods, Problems and Realizations. [Citation Graph (0, 0)][DBLP]
    EURASIP Workshop, 1990, pp:244-266 [Conf]
  8. John Aldo Lee, Christian Jutten, Michel Verleysen
    Non-linear ICA by Using Isometric Dimensionality Reduction. [Citation Graph (0, 0)][DBLP]
    ICA, 2004, pp:710-717 [Conf]
  9. Massoud Babaie-Zadeh, Ali Mansour, Christian Jutten, Farrokh Marvasti
    A Geometric Approach for Separating Several Speech Signals. [Citation Graph (0, 0)][DBLP]
    ICA, 2004, pp:798-806 [Conf]
  10. Shahram Hosseini, Rima Guidara, Yannick Deville, Christian Jutten
    Markovian Blind Image Separation. [Citation Graph (0, 0)][DBLP]
    ICA, 2006, pp:106-114 [Conf]
  11. Sebastien Lagrange, Luc Jaulin, Vincent Vigneron, Christian Jutten
    Analytical Solution of the Blind Source Separation Problem Using Derivatives. [Citation Graph (0, 0)][DBLP]
    ICA, 2004, pp:81-88 [Conf]
  12. Anthony Larue, Christian Jutten, Shahram Hosseini
    Markovian Source Separation in Post-nonlinear Mixtures. [Citation Graph (0, 0)][DBLP]
    ICA, 2004, pp:702-709 [Conf]
  13. Samareh Samadi, Massoud Babaie-Zadeh, Christian Jutten, Kambiz Nayebi
    Blind Source Separation by Adaptive Estimation of Score Function Difference. [Citation Graph (0, 0)][DBLP]
    ICA, 2004, pp:9-17 [Conf]
  14. Vincent Vigneron, Christian Jutten
    Fisher Information in Source Separation Problems. [Citation Graph (0, 0)][DBLP]
    ICA, 2004, pp:168-176 [Conf]
  15. Frédéric Vrins, Deniz Erdogmus, Christian Jutten, Michel Verleysen
    Zero-Entropy Minimization for Blind Extraction of Bounded Sources (BEBS). [Citation Graph (0, 0)][DBLP]
    ICA, 2006, pp:747-754 [Conf]
  16. Frédéric Vrins, Christian Jutten, Michel Verleysen
    Sensor Array and Electrode Selection for Non-invasive Fetal Electrocardiogram Extraction by Independent Component Analysis. [Citation Graph (0, 0)][DBLP]
    ICA, 2004, pp:1017-1014 [Conf]
  17. Bertrand Rivet, Vincent Vigneron, Anisoara Paraschiv-Ionescu, Christian Jutten
    Wavelet De-noising for Blind Source Separation in Noisy Mixtures. [Citation Graph (0, 0)][DBLP]
    ICA, 2004, pp:263-270 [Conf]
  18. Anisoara Paraschiv-Ionescu, Christian Jutten, G. Bouvier
    Neural Network Based Processing for Smart Sensors Arrays. [Citation Graph (0, 0)][DBLP]
    ICANN, 1997, pp:565-570 [Conf]
  19. Anisse Taleb, Christian Jutten
    Entropy Optimization - Application to Blind Source Separation. [Citation Graph (0, 0)][DBLP]
    ICANN, 1997, pp:529-534 [Conf]
  20. Anisoara Paraschiv-Ionescu, Christian Jutten, Kamiar Aminian, Bijan Najafi, Philippe Robert
    Wavelet denoising for highly noisy source separation. [Citation Graph (0, 0)][DBLP]
    ISCAS (1), 2002, pp:201-204 [Conf]
  21. Massoud Babaie-Zadeh, Christian Jutten, Kambiz Nayebi
    Separating Convolutive Mixtures by Mutual Information Minimization. [Citation Graph (0, 0)][DBLP]
    IWANN (2), 2001, pp:834-842 [Conf]
  22. Jordi Solé i Casals, Christian Jutten, Dinh-Tuan Pham
    Initialisation of Nonlinearities for PNL and Wiener Systems Inversion. [Citation Graph (0, 0)][DBLP]
    IWANN (2), 2003, pp:225-232 [Conf]
  23. Rachida Chentouf, Christian Jutten
    Incremental Learning with a Stopping Criterion - Experimental Results. [Citation Graph (0, 0)][DBLP]
    IWANN, 1995, pp:519-526 [Conf]
  24. Shahram Hosseini, Christian Jutten
    Weight Freezing in Constructive Neural Networks: A Novel Approach. [Citation Graph (0, 0)][DBLP]
    IWANN (2), 1999, pp:11-20 [Conf]
  25. Shahram Hosseini, Christian Jutten, Sylvie Charbonnier
    Neural Network Modeling of Ambulatory Systolic Blood Pressure for Hypertension Diagnosis. [Citation Graph (0, 0)][DBLP]
    IWANN (2), 2003, pp:599-606 [Conf]
  26. Christian Jutten
    Learning in Evolutive Neural Architectures: An Ill-Posed Problem? [Citation Graph (0, 0)][DBLP]
    IWANN, 1995, pp:361-373 [Conf]
  27. Christian Jutten, Pierre Comon
    Neural Bayesian Classifier. [Citation Graph (0, 0)][DBLP]
    IWANN, 1993, pp:119-124 [Conf]
  28. Christian Jutten, Anne Guérin-Dugué, H. L. Nguyen Thi
    Adaptive Optimization of Neural Algorithms. [Citation Graph (0, 0)][DBLP]
    IWANN, 1991, pp:54-61 [Conf]
  29. Anisse Taleb, Jordi Solé i Casals, Christian Jutten
    Blind Inversion of Wiener Systems. [Citation Graph (0, 0)][DBLP]
    IWANN (2), 1999, pp:655-664 [Conf]
  30. Shahram Hosseini, Christian Jutten
    Simultaneous Estimation of Signal and Noise in the Constructive Neural Networks. [Citation Graph (0, 0)][DBLP]
    NC, 1998, pp:412-418 [Conf]
  31. Christian Jutten, Juha Karhunen
    Advances in blind source separation (BSS) and independent component analysis (ICA) for nonlinear mixtures. [Citation Graph (0, 0)][DBLP]
    Int. J. Neural Syst., 2004, v:14, n:5, pp:267-292 [Journal]
  32. Jordi Solé i Casals, Christian Jutten, Anisse Taleb
    Parametric approach to blind deconvolution of nonlinear channels. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2002, v:48, n:1-4, pp:339-355 [Journal]
  33. Vincent Vigneron, Ludovic Aubry, Christian Jutten
    General conditions of stability in blind source separation models and score function selection. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2004, v:62, n:, pp:65-78 [Journal]
  34. Massoud Babaie-Zadeh, Christian Jutten, Ali Mansour
    Sparse ICA via cluster-wise PCA. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2006, v:69, n:13-15, pp:1458-1466 [Journal]
  35. Samareh Samadi, Massoud Babaie-Zadeh, Christian Jutten
    Quasi-optimal EASI algorithm based on the Score Function Difference (SFD). [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2006, v:69, n:13-15, pp:1415-1424 [Journal]
  36. David Sodoyer, Laurent Girin, Christian Jutten, Jean-Luc Schwartz
    Developing an audio-visual speech source separation algorithm. [Citation Graph (0, 0)][DBLP]
    Speech Communication, 2004, v:44, n:1-4, pp:113-125 [Journal]
  37. C. Simon, Philippe Loubaton, Christian Jutten
    Separation of a class of convolutive mixtures: a contrast function approach. [Citation Graph (0, 0)][DBLP]
    Signal Processing, 2001, v:81, n:4, pp:883-887 [Journal]
  38. Christian Jutten, Massoud Babaie-Zadeh, Shahram Hosseini
    Three easy ways for separating nonlinear mixtures? [Citation Graph (0, 0)][DBLP]
    Signal Processing, 2004, v:84, n:2, pp:217-229 [Journal]
  39. Massoud Babaie-Zadeh, Christian Jutten
    A general approach for mutual information minimization and its application to blind source separation. [Citation Graph (0, 0)][DBLP]
    Signal Processing, 2005, v:85, n:5, pp:975-995 [Journal]
  40. Sophie Achard, Dinh-Tuan Pham, Christian Jutten
    Criteria based on mutual information minimization for blind source separation in post nonlinear mixtures. [Citation Graph (0, 0)][DBLP]
    Signal Processing, 2005, v:85, n:5, pp:965-974 [Journal]
  41. J. Solé-Casals, Christian Jutten, Dinh-Tuan Pham
    Fast approximation of nonlinearities for improving inversion algorithms of PNL mixtures and Wiener systems. [Citation Graph (0, 0)][DBLP]
    Signal Processing, 2005, v:85, n:9, pp:1780-1786 [Journal]
  42. Yoan Miche, Patrick Bas, Amaury Lendasse, Christian Jutten, Olli Simula
    Advantages of Using Feature Selection Techniques on Steganalysis Schemes. [Citation Graph (0, 0)][DBLP]
    IWANN, 2007, pp:606-613 [Conf]

  43. A Methodology for Building Regression Models using Extreme Learning Machine: OP-ELM. [Citation Graph (, )][DBLP]


  44. Riemannian Geometry Applied to BCI Classification. [Citation Graph (, )][DBLP]


  45. Fast Sparse Representation Based on Smoothed l0 Norm. [Citation Graph (, )][DBLP]


  46. Fast Block-Sparse Decomposition Based on SL0. [Citation Graph (, )][DBLP]


  47. Non-negative Independent Component Analysis Algorithm Based on 2D Givens Rotations and a Newton Optimization. [Citation Graph (, )][DBLP]


  48. Sparse Component Analysis in Presence of Noise Using an Iterative EM-MAP Algorithm. [Citation Graph (, )][DBLP]


  49. Blind Source Separation of Overdetermined Linear-Quadratic Mixtures. [Citation Graph (, )][DBLP]


  50. Estimating the Mixing Matrix in Sparse Component Analysis Based on Converting a Multiple Dominant to a Single Dominant Problem. [Citation Graph (, )][DBLP]


  51. An Alternating Minimization Method for Sparse Channel Estimation. [Citation Graph (, )][DBLP]


  52. Adaptive and Non-adaptive ISI Sparse Channel Estimation Based on SL0 and Its Application in ML Sequence-by-Sequence Equalization. [Citation Graph (, )][DBLP]


  53. Blind Source Separation of a Class of Nonlinear Mixtures. [Citation Graph (, )][DBLP]


  54. Using Non-Negative Matrix Factorization for Removing Show-Through. [Citation Graph (, )][DBLP]


  55. Blind Extraction of Intermittent Sources. [Citation Graph (, )][DBLP]


  56. Ion-Selective Electrode Array Based on a Bayesian Nonlinear Source Separation Method. [Citation Graph (, )][DBLP]


  57. Iterative Subspace Decomposition for Ocular Artifact Removal from EEG Recordings. [Citation Graph (, )][DBLP]


  58. Image Coding and Compression with Sparse 3D Discrete Cosine Transform. [Citation Graph (, )][DBLP]


  59. Image Denoising Using Sparse Representations. [Citation Graph (, )][DBLP]


  60. A first step to convolutive sparse representation. [Citation Graph (, )][DBLP]


  61. Decoding real-field codes by an iterative Expectation-Maximization (EM) algorithm. [Citation Graph (, )][DBLP]


  62. Complex-valued sparse representation based on smoothed l0 norm. [Citation Graph (, )][DBLP]


  63. Sparse Decomposition over non-full-rank dictionaries. [Citation Graph (, )][DBLP]


  64. Robust-SL0 for stable sparse representation in noisy settings. [Citation Graph (, )][DBLP]


  65. Inflating compressed samples: A joint source-channel coding approach for noise-resistant compressed sensing. [Citation Graph (, )][DBLP]


  66. Sparse decomposition of two dimensional signals. [Citation Graph (, )][DBLP]


  67. Bayesian Pursuit algorithm for sparse representation. [Citation Graph (, )][DBLP]


  68. A fast approach for overcomplete sparse decomposition based on smoothed L0 norm [Citation Graph (, )][DBLP]


  69. A First Step to Convolutive Sparse Representation [Citation Graph (, )][DBLP]


  70. Approximate Sparse Decomposition Based on Smoothed L0-Norm [Citation Graph (, )][DBLP]


  71. A New Trend in Optimization on Multi Overcomplete Dictionary toward Inpainting [Citation Graph (, )][DBLP]


  72. Sparse Recovery using Smoothed $\ell^0$ (SL0): Convergence Analysis [Citation Graph (, )][DBLP]


  73. Bayesian Cramér-Rao Bound for Noisy Non-Blind and Blind Compressed Sensing [Citation Graph (, )][DBLP]


  74. On the stable recovery of the sparsest overcomplete representations in presence of noise [Citation Graph (, )][DBLP]


  75. On the Achievability of Cramér-Rao Bound In Noisy Compressed Sensing [Citation Graph (, )][DBLP]


  76. Bayesian Hypothesis Testing for Sparse Representation [Citation Graph (, )][DBLP]


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