Pages that link to "Item:Q413642"
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The following pages link to Recovery of sparsest signals via \(\ell^q \)-minimization (Q413642):
Displaying 50 items.
- Entropy function-based algorithms for solving a class of nonconvex minimization problems (Q259115) (← links)
- The gap between the null space property and the restricted isometry property (Q273151) (← links)
- A smoothing SQP framework for a class of composite \(L_q\) minimization over polyhedron (Q304258) (← links)
- Iterative reweighted minimization methods for \(l_p\) regularized unconstrained nonlinear programming (Q463732) (← links)
- Stable recovery of sparse signals via \(\ell_p\)-minimization (Q466983) (← links)
- Compressed sensing with coherent tight frames via \(l_q\)-minimization for \(0 < q \leq 1\) (Q479885) (← links)
- On the null space property of \(l_q\)-minimization for \(0 < q \leq 1\) in compressed sensing (Q492558) (← links)
- The null space property for sparse recovery from multiple measurement vectors (Q533503) (← links)
- Nonlinear frames and sparse reconstructions in Banach spaces (Q682869) (← links)
- The \(\ell_{2,q}\) regularized group sparse optimization: lower bound theory, recovery bound and algorithms (Q778013) (← links)
- A theoretical perspective of solving phaseless compressive sensing via its nonconvex relaxation (Q778434) (← links)
- A note on guaranteed sparse recovery via \(\ell_1\)-minimization (Q984666) (← links)
- Global optimality condition and fixed point continuation algorithm for non-Lipschitz \(\ell_p\) regularized matrix minimization (Q1650690) (← links)
- The sparsity of underdetermined linear system via \(l_p\) minimization for \(0 < p < 1\) (Q1666063) (← links)
- Analysis of the equivalence relationship between \(l_{0}\)-minimization and \(l_{p}\)-minimization (Q1688516) (← links)
- Exact recovery of sparse multiple measurement vectors by \(l_{2,p}\)-minimization (Q1691327) (← links)
- \(\ell _p\) regularized low-rank approximation via iterative reweighted singular value minimization (Q1694395) (← links)
- Affine matrix rank minimization problem via non-convex fraction function penalty (Q1696454) (← links)
- A sharp recovery condition for block sparse signals by block orthogonal multi-matching pursuit (Q1700711) (← links)
- An iterative support shrinking algorithm for non-Lipschitz optimization in image restoration (Q1716780) (← links)
- Bound alternative direction optimization for image deblurring (Q1717868) (← links)
- On monotone and primal-dual active set schemes for \(\ell^p\)-type problems, \(p \in (0,1]\) (Q1734767) (← links)
- Sparse recovery in probability via \(l_q\)-minimization with Weibull random matrices for \(0 < q\leq 1\) (Q1747365) (← links)
- Spark-level sparsity and the \(\ell_1\) tail minimization (Q1748258) (← links)
- A new globally convergent algorithm for non-Lipschitz \(\ell_{p}-\ell_q\) minimization (Q2000528) (← links)
- A unified primal dual active set algorithm for nonconvex sparse recovery (Q2038299) (← links)
- Sparse recovery using the discrete cosine transform (Q2050708) (← links)
- Sparse recovery with integrality constraints (Q2192094) (← links)
- Stability of 1-bit compressed sensing in sparse data reconstruction (Q2217038) (← links)
- An evaluation of the sparsity degree for sparse recovery with deterministic measurement matrices (Q2251220) (← links)
- The nonnegative zero-norm minimization under generalized \(Z\)-matrix measurement (Q2251573) (← links)
- A numerical exploration of compressed sampling recovery (Q2267399) (← links)
- On a monotone scheme for nonconvex nonsmooth optimization with applications to fracture mechanics (Q2275329) (← links)
- The sparsest solution of the union of finite polytopes via its nonconvex relaxation (Q2311128) (← links)
- New conditions on stable recovery of weighted sparse signals via weighted \(l_1\) minimization (Q2312513) (← links)
- A simple Gaussian measurement bound for exact recovery of block-sparse signals (Q2320652) (← links)
- Optimal RIP bounds for sparse signals recovery via \(\ell_p\) minimization (Q2330928) (← links)
- Improved RIP conditions for compressed sensing with coherent tight frames (Q2403862) (← links)
- Concentration of \(S\)-largest mutilated vectors with \(\ell_p\)-quasinorm for \(0<p\leq 1\) and its applications (Q2449220) (← links)
- Stable recovery of low-rank matrix via nonconvex Schatten \(p\)-minimization (Q2629808) (← links)
- On the Schatten \(p\)-quasi-norm minimization for low-rank matrix recovery (Q2659733) (← links)
- The finite steps of convergence of the fast thresholding algorithms with \(f\)-feedbacks in compressed sensing (Q2672726) (← links)
- Sparse signal recovery from quadratic measurements via convex programming (Q2870598) (← links)
- Exact Recoverability From Dense Corrupted Observations via $\ell _{1}$-Minimization (Q2989298) (← links)
- Sparse Recovery via <i>ℓ<sub>q</sub></i>-Minimization for Polynomial Chaos Expansions (Q3176044) (← links)
- Note on sparsity in signal recovery and in matrix identification (Q3192763) (← links)
- Recovery of Short, Complex Linear Combinations Via&lt;tex&gt;$ell _1$&lt;/tex&gt;Minimization (Q3547717) (← links)
- Stable Recovery of Sparse Signals Via Regularized Minimization (Q3604412) (← links)
- Sparsest representations and approximations of an underdetermined linear system (Q4569345) (← links)
- On the Reconstruction of Block-Sparse Signals With an Optimal Number of Measurements (Q4569805) (← links)
