Multimodal data fusion: an overview of methods, challenges, and prospects D Lahat, T Adali, C Jutten Proceedings of the IEEE 103 (9), 1449-1477, 2015 | 1173 | 2015 |
Second-order multidimensional ICA: Performance analysis D Lahat, JF Cardoso, H Messer IEEE Transactions on Signal Processing 60 (9), 4598-4610, 2012 | 61 | 2012 |
Challenges in multimodal data fusion D Lahat, T Adalı, C Jutten EUSIPCO, 2014 | 58 | 2014 |
Joint independent subspace analysis using second-order statistics D Lahat, C Jutten IEEE Transactions on Signal Processing 64 (18), 4891-4904, 2015 | 38 | 2015 |
Joint block diagonalization algorithms for optimal separation of multidimensional components D Lahat, JF Cardoso, H Messer Latent Variable Analysis and Signal Separation: 10th International …, 2012 | 19 | 2012 |
Blind Separation of Multidimensional Components via Subspace Decomposition: Performance Analysis D Lahat, JF Cardoso, H Messer IEEE Transactions on Signal Processing 62 (11), 2894-2905, 2014 | 16 | 2014 |
Joint independent subspace analysis: A quasi-Newton algorithm D Lahat, C Jutten International Conference on Latent Variable Analysis and Signal Separation …, 2015 | 13 | 2015 |
An alternative proof for the identifiability of independent vector analysis using second order statistics D Lahat, C Jutten Acoustics, Speech and Signal Processing (ICASSP), 2016 IEEE International …, 2016 | 11 | 2016 |
Joint blind source separation of multidimensional components: Model and algorithm D Lahat, C Jutten EUSIPCO, 2014 | 11 | 2014 |
Joint independent subspace analysis: Uniqueness and identifiability D Lahat, C Jutten IEEE Transactions on Signal Processing 67 (3), 684-699, 2018 | 10 | 2018 |
Identifiability of second-order multidimensional ICA D Lahat, JF Cardoso, H Messer 2012 Proceedings of the 20th European Signal Processing Conference (EUSIPCO …, 2012 | 8 | 2012 |
Optimal performance of second-order multidimensional ICA D Lahat, JF Cardoso, H Messer Independent Component Analysis and Signal Separation: 8th International …, 2009 | 8 | 2009 |
Positive semidefinite matrix factorization: A link to phase retrieval and a block gradient algorithm D Lahat, C Févotte ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 7 | 2020 |
A generalization to Schur's lemma with an application to joint independent subspace analysis D Lahat, C Jutten | 6 | 2016 |
Joint analysis of multiple datasets by cross-cumulant tensor (block) diagonalization D Lahat, C Jutten Sensor Array and Multichannel Signal Processing Workshop (SAM), 2016 IEEE, 1-5, 2016 | 5 | 2016 |
A new link between joint blind source separation using second order statistics and the canonical polyadic decomposition D Lahat, C Jutten International Conference on Latent Variable Analysis and Signal Separation …, 2018 | 4 | 2018 |
ICA of correlated sources mismodeled as uncorrelated: Performance analysis D Lahat, H Messer, JF Cardoso 2009 IEEE/SP 15th Workshop on Statistical Signal Processing, 489-492, 2009 | 4 | 2009 |
Positive semidefinite matrix factorization: A connection with phase retrieval and affine rank minimization D Lahat, Y Lang, VYF Tan, C Févotte IEEE Transactions on Signal Processing 69, 3059-3074, 2021 | 3 | 2021 |
Positive semidefinite matrix factorization based on truncated Wirtinger flow D Lahat, C Févotte 2020 28th European Signal Processing Conference (EUSIPCO), 1035-1039, 2021 | 3 | 2021 |
Schur's lemma for coupled reducibility and coupled normality D Lahat, C Jutten, H Shapiro SIAM Journal on Matrix Analysis and Applications 40 (3), 998-1021, 2019 | 2 | 2019 |