Frederik Van Eeghem
Frederik Van Eeghem
Ph.D. researcher at KU Leuven
Verified email at kuleuven.be - Homepage
Title
Cited by
Cited by
Year
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
162017
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
92017
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
42016
Second-order tensor-based convolutive ICA: deconvolution versus tensorization
F Van Eeghem, L De Lathauwer
4*
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
32018
Tensor computations using Tensorlab
O Debals, F Van Eeghem, N Vervliet, L De Lathauwer
22019
Tensor similarity in two modes
F Van Eeghem, O Debals, L De Lathauwer
IEEE Transactions on Signal Processing 66 (5), 1273-1285, 2017
12017
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
12016
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
12014
Tensor-Based Independent Component Analysis: from Instantaneous to Convo Lutive Mixtures
F Van Eeghem
2021
Algorithms for canonical polyadic decomposition with block-circulant factors
F Van Eeghem, L De Lathauwer
IEEE Signal Processing Letters 25 (6), 798-802, 2018
2018
Tensorlab Demos
O Debals, F Van Eeghem, N Vervliet, L De Lathauwer
2016
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
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
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
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
What can tensors do in telecommunications? (poster)
F Van Eeghem, L De Lathauwer
KULAK Research Day 2015, 1-1, 2015
2015
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
.................................................................. K. Nomura, D. Sugimura, and T. Hamamoto 893 Information Forensics and Security Efficient JPEG Steganography …
M Doostmohammadian, HR Rabiee, UA Khan, F Van Eeghem, ...
Blind System Identification as a Compressed Sensing Problem
F Van Eeghem, L De Lathauwer
The system can't perform the operation now. Try again later.
Articles 1–20