1 |
戴琼海, 付长军, 季向阳. 压缩感知研究[J]. 计算机学报, 2011, 34(3): 425-434.
|
|
DAI Q H, FU C J, JI X Y. Research on compressed sensing[J]. Chinese Journal of Computers, 2011, 34(3): 425-434. (in Chinese)
|
2 |
钱慧, 杨超. 频谱互质重排亚奈奎斯特率采样方法[J]. 电子学报, 2017, 45(10): 2506-2510.
|
|
QIAN H, YANG C. Sub-Nyquist sampling on spectrum co-prime permutation[J]. Acta Electronica Sinica, 2017, 45(10): 2506-2510. (in Chinese)
|
3 |
王亚军, 李明, 刘高峰. 复杂脉冲序列的有限新息率采样方法[J]. 电子与信息学报, 2013, 35(7): 1606-1611.
|
|
WANG Y J, LI M, LIU G F. Sampling complex pulse streams with finite rate of innovation methods[J]. Journal of Electronics and Information Technology, 2013, 35(7): 1606-1611. (in Chinese)
|
4 |
VETTERLI M, MARZILIANO P, BLU T. Sampling signals with finite rate of innovation[J]. IEEE Transactions on Signal Processing, 2002, 50(6): 1417-1428.
|
5 |
DONOHO D L. Compressed sensing[J]. IEEE Transactions on Information Theory, 2006, 52(4): 1289-1306.
|
6 |
BHANDARI A, BLU T. FRI sampling and time-varying pulses: Some theory and four short stories[C]//Proceedings of the 2017 IEEE International Conference on Acoustics, Speech and Signal Processing. New Orleans, LA, USA: IEEE, 2017: 3804-3808.
|
7 |
MARAVIC I, VETTERLI M. Sampling and reconstruction of signals with finite rate of innovation in the presence of noise[J]. IEEE Transactions on Signal Processing, 2005, 53(8): 2788-2805.
|
8 |
PAN H, SCHEIBLER R, BEZZAM E, et al. FRIDA: FRI-based DOA estimation for arbitrary array layouts[C]//Proceedings of the 2017 IEEE International Conference on Acoustics, Speech and Signal Processing. New Orleans, LA, USA: IEEE, 2017: 3186-3190.
|
9 |
BLU T, DRAGOTTI P L, VETTERLI M, et al. Sparse sampling of signal innovation[J]. IEEE Signal Processing Magazine, 2012, 25(2): 31-40.
|
10 |
MULLETI S, SEELAMANTULA C S. Paley-wiener characterization of kernels for finite-rate-of-innovation sampling[J]. IEEE Transactions on Signal Processing, 2017, 65(22): 5860-5872.
|
11 |
DOGAN Z, GILLIAM C, BLU T, et al. Reconstruction of finite rate of innovation signals with model-fitting approach[J]. IEEE Transactions on Signal Processing, 2015, 63(22): 6024-6036.
|
12 |
ZHANG Y, DRAGOTTI P L. On the reconstruction of wavelet-sparse signals from partial fourier information[J]. IEEE Signal Processing Letters, 2015, 22(9): 1234-1238.
|
13 |
BAECHLER G, SCHOLEFIELD A, BABOULAZ L, et al. Sampling and exact reconstruction of pulses with variable width[J]. IEEE Transactions on Signal Processing, 2017, 65(10): 2629-2644.
|
14 |
RUDRESH S, NAGESH S, SEELAMANTULA C S. Asymmetric pulse modeling for FRI sampling[J]. IEEE Transactions on Signal Processing, 2018, 66(8): 2027-2040.
|
15 |
LEUNG V C H, HUANG J J, DRAGOTTI P L. Reconstruction of FRI signals using deep neural network approaches[C]//Proceedings of the 2020 IEEE International Conference on Acoustics, Speech and Signal Processing. Barcelona, Spain: IEEE, 2020: 5430-5434.
|
16 |
TARAR M O, KHALID Z. Reconstruction of finite rate of innovation spherical signals in the presence of noise using deep learning architecture[C]//Proceedings of the 28th European Signal Processing Conference. Amsterdam, Netherlands: IEEE, 2021: 1487-1491.
|
17 |
REDDY P S, PREMKUMAR A, SAIKIRAN B, et al. Finite rate of innovation signal reconstruction using residual neural networks[C]//Proceedings of the 2020 IEEE 4th Conference on Information & Communication Technology. Chennai, India: IEEE, 2021: 1-6.
|