Spectrum-blind sampling and compressive sensing for continuous-index signals
暂无分享,去创建一个
[1] Bede Liu,et al. Sampling representations and the optimum reconstruction of signals , 1965, IEEE Trans. Inf. Theory.
[2] H. Landau. Necessary density conditions for sampling and interpolation of certain entire functions , 1967 .
[3] Ilan Ziskind,et al. On unique localization of multiple sources by passive sensor arrays , 1989, IEEE Trans. Acoust. Speech Signal Process..
[4] R. Marks,et al. Imaging sampling below the Nyquist density without aliasing , 1990 .
[5] Y. Bresler,et al. Spectrum-blind minimum-rate sampling and reconstruction of 2-D multiband signals , 1996, Proceedings of 3rd IEEE International Conference on Image Processing.
[6] Ping Feng,et al. Spectrum-blind minimum-rate sampling and reconstruction of multiband signals , 1996, 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings.
[7] Yoram Bresler,et al. Further results on spectrum blind sampling of 2D signals , 1998, Proceedings 1998 International Conference on Image Processing. ICIP98 (Cat. No.98CB36269).
[8] Cormac Herley,et al. Minimum rate sampling and reconstruction of signals with arbitrary frequency support , 1999, IEEE Trans. Inf. Theory.
[9] Yoram Bresler,et al. Perfect reconstruction formulas and bounds on aliasing error in sub-nyquist nonuniform sampling of multiband signals , 2000, IEEE Trans. Inf. Theory.
[10] Yoram Bresler,et al. Optimal sub-Nyquist nonuniform sampling and reconstruction for multiband signals , 2001, IEEE Trans. Signal Process..
[11] Bhaskar D. Rao,et al. Sparse solutions to linear inverse problems with multiple measurement vectors , 2005, IEEE Transactions on Signal Processing.
[12] Emmanuel J. Candès,et al. Decoding by linear programming , 2005, IEEE Transactions on Information Theory.
[13] Emmanuel J. Candès,et al. Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information , 2004, IEEE Transactions on Information Theory.
[14] J. Tropp. Algorithms for simultaneous sparse approximation. Part II: Convex relaxation , 2006, Signal Process..
[15] Joel A. Tropp,et al. ALGORITHMS FOR SIMULTANEOUS SPARSE APPROXIMATION , 2006 .
[16] David L Donoho,et al. Compressed sensing , 2006, IEEE Transactions on Information Theory.
[17] Jie Chen,et al. Theoretical Results on Sparse Representations of Multiple-Measurement Vectors , 2006, IEEE Transactions on Signal Processing.
[18] Richard G. Baraniuk,et al. Random Filters for Compressive Sampling and Reconstruction , 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.
[19] S. Kirolos,et al. Random Sampling for Analog-to-Information Conversion of Wideband Signals , 2006, 2006 IEEE Dallas/CAS Workshop on Design, Applications, Integration and Software.
[20] Joel A. Tropp,et al. Algorithms for simultaneous sparse approximation. Part I: Greedy pursuit , 2006, Signal Process..
[21] Richard G. Baraniuk,et al. Theory and Implementation of an Analog-to-Information Converter using Random Demodulation , 2007, 2007 IEEE International Symposium on Circuits and Systems.
[22] Minh N. Do,et al. A Theory for Sampling Signals from a Union of Subspaces , 2022 .
[23] Yonina C. Eldar,et al. Blind Multiband Signal Reconstruction: Compressed Sensing for Analog Signals , 2007, IEEE Transactions on Signal Processing.