94 results on '"Ge, Huanmin"'
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2. Signal and Image Reconstruction with Tight Frames via Unconstrained $\ell_1-\alpha \ell_2$-Analysis Minimizations
3. Image restoration based on transformed total variation and deep image prior
4. The Dantzig selector: Recovery of Signal via $\ell_1-\alpha \ell_2$ Minimization
5. Low-Rank tensor completion based on nonconvex regularization
6. Stable Recovery of Sparsely Corrupted Signals Through Justice Pursuit De-Noising
7. Deep image prior and weighted anisotropic-isotropic total variation regularization for solving linear inverse problems
8. Uniform RIP analysis for the [formula omitted]-[formula omitted] minimization
9. Efficient and Robust Recovery of Signal and Image in Impulsive Noise via $\ell_1-\alpha \ell_2$ Minimization
10. Signal and Image Reconstruction with Tight Frames via Unconstrained [formula omitted]-Analysis Minimizations
11. Recovery of signals by a weighted $\ell_2/\ell_1$ minimization under arbitrary prior support information
12. A sharp recovery condition for sparse signals with partial support information via orthogonal matching pursuit
13. A sharp recovery condition for block sparse signals by block orthogonal multi-matching pursuit
14. A sharp bound on RIC in generalized orthogonal matching pursuit
15. \(\boldsymbol{L_1-\beta L_q}\) Minimization for Signal and Image Recovery
16. Recovery of signals by a weighted ℓ2/ℓ1 minimization under arbitrary prior support information
17. An Optimal Recovery Condition for Sparse Signals with Partial Support Information via OMP
18. Analysis of the ratio of ℓ1 and ℓ2 norms for signal recovery with partial support information
19. Analysis of the ratio of ℓ1 and ℓ2 norms for signal recovery with partial support information.
20. Signal and Image Reconstruction with Tight Frames via Unconstrained ℓ1−αℓ2-Analysis Minimizations
21. RIP Analysis for $\ell _{1}/\ell _{p}$ ($p\gt 1$) Minimization Method
22. Analysis of the ratio of ℓ1and ℓ2norms for signal recovery with partial support information
23. Analysis of defensive playing styles in the professional Chinese Football Super League.
24. A sharp recovery condition for block sparse signals by block orthogonal multi-matching pursuit
25. Performance analysis for unconstrained analysis based approaches*
26. Stable Image Reconstruction Using Transformed Total Variation Minimization
27. Analysis of defensive playing styles in the professional Chinese Football Super League
28. A general theory for subspace-sparse recovery
29. Quantifying the Effectiveness of Defensive Playing Styles in the Chinese Football Super League
30. Impact of Match Type and Match Halves on Referees’ Physical Performance and Decision-Making Distance in Chinese Football Super League
31. On the existence of a mild solution for impulsive hybrid fractional differential equations
32. The Dantzig selector: recovery of signal via ℓ 1 − αℓ 2 minimization
33. Orthogonal Least Squares Detector for Generalized Spatial Modulation
34. RIP Analysis for <inline-formula><tex-math notation="LaTeX">$\ell _{1}/\ell _{p}$</tex-math></inline-formula> (<inline-formula><tex-math notation="LaTeX">$p> 1$</tex-math></inline-formula>) Minimization Method
35. The Dantzig selector: Recovery of Signal via $\ell_1-��\ell_2$ Minimization
36. Signal and Image Reconstruction with Tight Frames via Unconstrained $\ell_1-��\ell_2$-Analysis Minimizations
37. New Restricted Isometry Property Analysis for $\ell_1-\ell_2$ Minimization Methods
38. On Recovery of Sparse Signals with Prior Support Information via Weighted ℓp-minimization
39. The Dantzig selector: recovery of signal via â„" 1 â' αâ„" 2 minimization.
40. New RIP Bounds for Recovery of Sparse Signals With Partial Support Information via Weighted ${\ell_{p}}$ -Minimization
41. ℓ 1 − αℓ 2minimization methods for signal and image reconstruction with impulsive noise removal
42. On Recovery of Sparse Signals With Prior Support Information via Weighted ℓ ₚ -Minimization.
43. Efficient and Robust Recovery of Signal and Image in Impulsive Noise via $\ell_1-��\ell_2$ Minimization
44. Perturbation Analysis of Orthogonal Least Squares
45. An RIP Condition for Exact Support Recovery With Covariance-Assisted Matching Pursuit
46. New Bounds Based on RIP for the Sparse Matrix Recovery via the Weighted $\ell_{2,1}$ Minimization
47. ℓ1 − αℓ2 minimization methods for signal and image reconstruction with impulsive noise removal.
48. The Null Space Property of the Truncated $\ell _{1-2}$ -Minimization
49. Recovery of signals by a weighted ℓ 2 /ℓ 1 minimization under arbitrary prior support information
50. A Sharp Bound on RIC in Generalized Orthogonal Matching Pursuit
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