Sustainable computational science: the ReScience initiative NP Rougier, K Hinsen, F Alexandre, T Arildsen, LA Barba, FCY Benureau, ... PeerJ Computer Science 3, e142, 2017 | 113 | 2017 |
Structure assisted compressed sensing reconstruction of undersampled AFM images CS Oxvig, T Arildsen, T Larsen Ultramicroscopy 172, 1-9, 2017 | 37 | 2017 |
Demodulating subsampled direct sequence spread spectrum signals using compressive signal processing K Fyhn, T Arildsen, T Larsen, SH Jensen 2012 Proceedings of the 20th European Signal Processing Conference (EUSIPCO …, 2012 | 28 | 2012 |
Sensitivity of the random demodulation framework to filter tolerances PJ Pankiewicz, T Arildsen, T Larsen 2011 19th European Signal Processing Conference, 534-538, 2011 | 27 | 2011 |
Reconstruction algorithms in undersampled AFM imaging T Arildsen, CS Oxvig, PS Pedersen, J Østergaard, T Larsen IEEE Journal of Selected Topics in Signal Processing 10 (1), 31-46, 2016 | 25 | 2016 |
Compressed sensing with linear correlation between signal and measurement noise T Arildsen, T Larsen Signal Processing 98, 275-283, 2014 | 20 | 2014 |
Reconstruction of undersampled atomic force microscopy images: Interpolation versus basis pursuit TL Jensen, T Arildsen, J Østergaard, T Larsen 2013 International Conference on Signal-Image Technology & Internet-Based …, 2013 | 15 | 2013 |
Improving smoothed l0 norm in compressive sensing using adaptive parameter selection CS Oxvig, PS Pedersen, T Arildsen, T Larsen arXiv preprint arXiv:1210.4277, 2012 | 15 | 2012 |
Magni: A python package for compressive sampling and reconstruction of atomic force microscopy images C Oxvig, P Pedersen, T Arildsen, J Østergaard, T Larsen Journal of Open Research Software 2 (1), 2014 | 14 | 2014 |
Model-based calibration of filter imperfections in the random demodulator for compressive sensing PJ Pankiewicz, T Arildsen, T Larsen arXiv preprint arXiv:1303.6135, 2013 | 11 | 2013 |
Reducing the computational complexity of reconstruction in compressed sensing nonuniform sampling R Grigoryan, TL Jensen, T Arildsen, T Larsen 21st European Signal Processing Conference (EUSIPCO 2013), 1-5, 2013 | 9 | 2013 |
On predictive coding for erasure channels using a Kalman framework T Arildsen, MN Murthi, SV Andersen, SH Jensen IEEE Transactions on Signal Processing 57 (11), 4456-4466, 2009 | 9 | 2009 |
On Predictive Coding for Erasure Channels Using a Kalman Framework T Arildsen, MN Murthi, SV Andersen, SH Jensen 17th European Signal Processing Conference (EUSIPCO), 1646-1650, 2009 | 9 | 2009 |
Performance comparison of reconstruction algorithms in discrete blind multi-coset sampling R Grigoryan, T Arildsen, D Tandur, T Larsen 2012 IEEE International Symposium on Signal Processing and Information …, 2012 | 7 | 2012 |
Storing reproducible results from computational experiments using scientific Python packages CS Oxvig, T Arildsen, T Larsen Scientific Computing with Python 2016, 45-50, 2016 | 6 | 2016 |
Compressed sensing with rank deficient dictionaries TL Hansen, DH Johansen, PB Jørgensen, KF Trillingsgaard, T Arildsen, ... 2012 IEEE Global Communications Conference (GLOBECOM), 3594-3599, 2012 | 6 | 2012 |
Surpassing the theoretical 1-norm phase transition in compressive sensing by tuning the smoothed l0 algorithm CS Oxvig, PS Pedersen, T Arildsen, T Larsen 2013 IEEE International Conference on Acoustics, Speech and Signal …, 2013 | 5 | 2013 |
WLCp2-09: Novel IP Header Compression Technique for Wireless Technologies with Fixed Link Layer Packet Types TK Madsen, FHP Fitzek, S Nethi, T Arildsen, GP Perrucci IEEE Globecom 2006, 1-5, 2006 | 5 | 2006 |
Generation and Analysis of Constrained Random Sampling Patterns J Pierzchlewski, T Arildsen Circuits, Systems, and Signal Processing 35 (10), 3619-3643, 2016 | 4 | 2016 |
Interpolation PR Turner, T Arildsen, K Kavanagh Applied Scientific Computing, 189-228, 2018 | 3 | 2018 |