Enhancing the sufficient condition of sparsity pattern recovery
Tài liệu tham khảo
Donoho, 2006, Compressed sensing, IEEE Trans. Inf. Theory, 52, 1289, 10.1109/TIT.2006.871582
Chen, 1998, Atomic decomposition by basis pursuit, SIAM J. Sci. Comput., 20, 33, 10.1137/S1064827596304010
Candes, 2006, Stable signal recovery for incomplete and inaccurate measurements, Commun. Pure Appl. Math., 59, 1207, 10.1002/cpa.20124
Even, 2009, A note on compressed sensing and the complexity of matrix multiplication, Inf. Process. Lett., 109, 468, 10.1016/j.ipl.2009.01.010
Donoho, 2006, Stable recovery of sparse over complete representations in the presence of noise, IEEE Trans. Inf. Theory, 52, 6, 10.1109/TIT.2005.860430
Civril, 2013, A note on the hardness of sparse approximation, Inf. Process. Lett., 113, 543, 10.1016/j.ipl.2013.04.014
Klopp, 2015, Estimation of matrices with row sparsity, Probl. Inf. Transm., 51, 335, 10.1134/S0032946015040031
Candes, 2005, Decoding by linear programming, IEEE Trans. Inf. Theory, 51, 4203, 10.1109/TIT.2005.858979
Tibshirani, 1996, Regression shrinkage and selection via the lasso, J. R. Stat. Soc., Ser. B, 58, 267
Tropp, 2006, Just relax: convex programming methods for identifying sparse signals in noise, IEEE Trans. Inf. Theory, 52, 1030, 10.1109/TIT.2005.864420
Baillet, 2001, Electromagnetic brain mapping, IEEE Signal Process. Mag., 18, 14, 10.1109/79.962275
Wipf, 2008, A unified Bayesian framework for MEG/EEG source imaging, NeuroImage, 44, 947, 10.1016/j.neuroimage.2008.02.059
Tian, 2007, Compressed sensing for wideband cognitive radios, 1357
Miller, 1990
Guo, 2009, Neighbour discovery in ad hoc networks as a compressed sensing problem
Wainwright, 2009, Information-theoretic limits on sparsity recovery in the high-dimensional and noisy setting, IEEE Trans. Inf. Theory, 55, 5728, 10.1109/TIT.2009.2032816
Akcakaya, 2010, Shannon-theoretic limits on noisy compressive sampling, IEEE Trans. Inf. Theory, 56, 492, 10.1109/TIT.2009.2034796
Reeves, 2013, Approximate sparsity pattern recovery: information-theoretic lower bounds, IEEE Trans. Inf. Theory, 59, 3451, 10.1109/TIT.2013.2253852
Fletcher, 2009, Necessary and sufficient conditions on sparsity pattern recovery, IEEE Trans. Inf. Theory, 55, 5758, 10.1109/TIT.2009.2032726
Rad, 2011, Nearly sharp sufficient conditions on exact sparsity pattern recovery, IEEE Trans. Inf. Theory, 57, 4672, 10.1109/TIT.2011.2145670
Shaeiri, 2017, Enhancing the fundamental limits of sparsity pattern recovery, Digit. Signal Process., 69, 275, 10.1016/j.dsp.2017.06.027
Wang, 2009, Information-theoretic limits on sparse signal recovery: dense versus sparse measurement matrices, IEEE Trans. Inf. Theory, 56, 2967, 10.1109/TIT.2010.2046199
Aeron, 2010, Information theoretic bounds for compressed sensing, IEEE Trans. Inf. Theory, 56, 5111, 10.1109/TIT.2010.2059891
Wainwright, 2009, Sharp thresholds for high-dimensional and noisy sparsity recovery using l1-constrained quadratic programming (Lasso), IEEE Trans. Inf. Theory, 55, 2183, 10.1109/TIT.2009.2016018
Scarllet, 2013, Compressed sensing with prior information: information-theoretic limits and practical decoders, IEEE Trans. Inf. Theory, 61, 427, 10.1109/TSP.2012.2225051
Alzer, 2003, On Ramanujan's double inequality for the gamma function, Bull. Lond. Math. Soc., 35, 601, 10.1112/S0024609303002261
Merkle, 1993, Some inequality for chi-square distribution function and the exponential function, Arch. Math., 60, 451, 10.1007/BF01202311
Natalini, 2000, In equalities for the incomplete gamma function, Math. Inequal. Appl., 3, 69
