| Blind multichannel deconvolution and convolutive extensions of canonical polyadic and block term decompositions M Sørensen, F Van Eeghem, L De Lathauwer IEEE Transactions on Signal Processing 65 (15), 4132-4145, 2017 | 24 | 2017 |
| Tensor decompositions with several block-Hankel factors and application in blind system identification F Van Eeghem, M Sørensen, L De Lathauwer IEEE Transactions on Signal Processing 65 (15), 4090-4101, 2017 | 10 | 2017 |
| Second-order tensor-based convolutive ICA: deconvolution versus tensorization F Van Eeghem, L De Lathauwer | 7* | |
| Tensorlab Demos-Release 3.0 O Debals, F Van Eeghem, N Vervliet, L De Lathauwer Technical Report 16–68, ESAT–STADIUS, KU Leuven, Belgium, 2016 | 4 | 2016 |
| Tensor computations using Tensorlab O Debals, F Van Eeghem, N Vervliet, L De Lathauwer | 3 | 2019 |
| Coupled and incomplete tensors in blind system identification F Van Eeghem, O Debals, N Vervliet, L De Lathauwer IEEE Transactions on Signal Processing 66 (23), 6137-6147, 2018 | 3 | 2018 |
| Tensor similarity in two modes F Van Eeghem, O Debals, L De Lathauwer IEEE Transactions on Signal Processing 66 (5), 1273-1285, 2017 | 3 | 2017 |
| Algorithms for canonical polyadic decomposition with block-circulant factors F Van Eeghem, L De Lathauwer IEEE Signal Processing Letters 25 (6), 798-802, 2018 | 1 | 2018 |
| Tensorlab demos O Debals, F Van Eeghem, N Vervliet, L De Lathauwer | 1 | 2016 |
| ‘Some examples of big data analysis using tensors M Boussé, O Debals, N Vervliet, F Van Eeghem, L De Lathauwer Proc. 25th Belg.-Dutch Conf. Mach. Learn, 1-3, 2016 | 1 | 2016 |
| Tensor-based algorithms for the analysis of data similarity in a blind system identification context F Van Eeghem, O Debals, L De Lathauwer Workshop on data-driven modeling methods and applications, 1-1, 2014 | 1 | 2014 |
| Tensor-Based Independent Component Analysis: from Instantaneous to Convolutive Mixtures F Van Eeghem | | 2021 |
| Tensor similarity in chemometrics F Van Eeghem, L De Lathauwer Elsevier, 2020 | | 2020 |
| Tensor-based convolutive independent component analysis (presentation) F Van Eeghem, L De Lathauwer 9th International Conference of the ERCIM WG on Computational and …, 2016 | | 2016 |
| Subspace-based algorithms for the blind identification of systems with iid inputs (talk) F Van Eeghem, M Sorensen, L De Lathauwer 20th Cfonference of the International Linear Algebra Society, 1-1, 2016 | | 2016 |
| Tensorlab: A toolbox for (multilinear) data analysis (presentation) O Debals, N Vervliet, M Boussé, F Van Eeghem, L De Lathauwer Deutchen ArbeitsGemeinschaft STATistik, Date: 2016/03/01-2016/03/01 …, 2016 | | 2016 |
| Convolutive independent component analysis as a Kronecker product equation (poster) F Van Eeghem, L De Lathauwer Proc. Workshop on Tensor Decompositions and Applications, 1-1, 2016 | | 2016 |
| A tensor-based framework for blind identification of linear MIMO FIR systems F Van Eeghem, O Debals, L De Lathauwer 34th Benelux Meeting on Systems and Control, 1-1, 2015 | | 2015 |
| What can tensors do in telecommunications? (poster) F Van Eeghem, L De Lathauwer KULAK Research Day 2015, 1-1, 2015 | | 2015 |
| .................................................................. K. Nomura, D. Sugimura, and T. Hamamoto 893 Information Forensics and Security Efficient JPEG Steganography … M Doostmohammadian, HR Rabiee, UA Khan, F Van Eeghem, ... | | |
Nico VervlietPostdoc at KU Leuven, BelgiumVerified email at esat.kuleuven.be
