Inertial projection neural network for nonconvex sparse signal recovery with prior information

References

[1] Candès E J. Compressive sampling. In: Proceedings of the International Congress of Mathematicians. 2006, 1433–1452

[2] Chartrand R. Exact reconstruction of sparse signals via nonconvex minimization. IEEE Signal Processing Letters, 2007, 14( 10): 707–710

[3] Yin P, Lou Y, He Q, Xin J. Minimization of ℓ_1-2 for compressed sensing. SIAM Journal on Scientific Computing, 2015, 37( 1): A536–A563

[4] Ince T, Nacaroglu A, Watsuji N. Nonconvex compressed sensing with partially known signal support. Signal Processing, 2013, 93( 1): 338–344

[5] Zhang J, Zhang S, Wang W. Robust signal recovery for ℓ_1-2 minimization via prior support information. Inverse Problems, 2021, 37( 11): 115001

[6] Zhu L, Wang J, He X, Zhao Y. An inertial projection neural network for sparse signal reconstruction via l_1-2 minimization. Neurocomputing, 2018, 315: 89–95

[7] Zhang H, Qiao G, Lu S, Yao L, Chen X. Attention-based feature fusion generative adversarial network for yarn-dyed fabric defect detection. Textile Research Journal, 2022,

[8] Chartrand R, Staneva V. Restricted isometry properties and nonconvex compressive sensing. Inverse Problems, 2008, 24( 3): 035020

RIGHTS & PERMISSIONS

Higher Education Press