| Quantized Compressive Sensing with RIP Matrices: The Benefit of Dithering C Xu, L Jacques Information and Inference: A Journal of the IMA, 2019 | 38 | 2019 |
| 1-Bit compressive sensing: Reformulation and RRSP-based sign recovery theory YB Zhao, CL Xu Science China Mathematics 59 (10), 2049-2074, 2016 | 17 | 2016 |
| The rare eclipse problem on tiles: Quantised embeddings of disjoint convex sets V Cambareri, C Xu, L Jacques 2017 International Conference on Sampling Theory and Applications (SampTA …, 2017 | 11 | 2017 |
| 1-bit Localization Scheme for Radar using Dithered Quantized Compressed Sensing T Feuillen, C Xu, L Vandendorpe, L Jacques arXiv preprint arXiv:1806.05408, 2018 | 8 | 2018 |
| Quantity over quality: dithered quantization for compressive radar systems T Feuillen, C Xu, J Louveaux, L Vandendorpe, L Jacques 2019 IEEE Radar Conference (RadarConf), 1-6, 2019 | 4 | 2019 |
| Taking the edge off quantization: projected back projection in dithered compressive sensing C Xu, V Schellekens, L Jacques The IEEE Statistical Signal Processing Workshop 2018, 2018 | 1 | 2018 |
| Uniqueness Conditions for A Class of ℓ0-Minimization Problems C Xu, YB Zhao Asia-Pacific Journal of Operational Research 32 (01), 1540002, 2015 | 1 | 2015 |
| Rare Eclipses in Quantised Random Embeddings of Disjoint Convex Sets: a Matter of Consistency? V Cambareri, C Xu, L Jacques Signal Processing with Adaptive Sparse Structured Representations (SPARS'17 …, 2017 | | 2017 |
| Sparsity optimization and RRSP-based theory far l-bit compressive sensing C Xu University of Birmingham, 2016 | | 2016 |
| The Rare Eclipse Problem in Quantised Random Embeddings: a Matter of Consistency? V Cambareri, C Xu, L Jacques | | |
