Pages that link to "Item:Q927127"

The following pages link to The restricted isometry property and its implications for compressed sensing (Q927127):

Displaying 50 items.

• Hybrid reconstruction of quantum density matrix: when low-rank meets sparsity (Q1698802) (← links)
• A sharp recovery condition for block sparse signals by block orthogonal multi-matching pursuit (Q1700711) (← links)
• Random matrices and erasure robust frames (Q1704861) (← links)
• Recovery of signals under the condition on RIC and ROC via prior support information (Q1713645) (← links)
• Error in the reconstruction of nonsparse images (Q1720910) (← links)
• Roles of clustering coefficient for the network reconstruction (Q1721001) (← links)
• A remark on joint sparse recovery with OMP algorithm under restricted isometry property (Q1740232) (← links)
• Sparse signal recovery with prior information by iterative reweighted least squares algorithm (Q1746492) (← links)
• A strong converse bound for multiple hypothesis testing, with applications to high-dimensional estimation (Q1746556) (← links)
• Sparse recovery in probability via \(l_q\)-minimization with Weibull random matrices for \(0 < q\leq 1\) (Q1747365) (← links)
• Stable recovery of low-dimensional cones in Hilbert spaces: one RIP to rule them all (Q1748256) (← links)
• Spark-level sparsity and the \(\ell_1\) tail minimization (Q1748258) (← links)
• Robust sparse signal reconstructions against basis mismatch and their applications (Q1749812) (← links)
• Adaptive compressive learning for prediction of protein-protein interactions from primary sequence (Q1783649) (← links)
• Capped \(\ell_p\) approximations for the composite \(\ell_0\) regularization problem (Q1785036) (← links)
• Statistical properties of SNR for compressed measurements (Q1792981) (← links)
• Sliding-MOMP based channel estimation scheme for ISDB-T systems (Q1793180) (← links)
• On a gradient-based algorithm for sparse signal reconstruction in the signal/measurements domain (Q1793419) (← links)
• Compressive sensing based sampling and reconstruction for wireless sensor array network (Q1793853) (← links)
• Linear program relaxation of sparse nonnegative recovery in compressive sensing microarrays (Q1929588) (← links)
• Strengthening hash families and compressive sensing (Q1932362) (← links)
• Full spark frames (Q1934656) (← links)
• How well can we estimate a sparse vector? (Q1940130) (← links)
• A short note on compressed sensing with partially known signal support (Q1957941) (← links)
• Phase retrieval from Fourier measurements with masks (Q1983452) (← links)
• A preconditioning approach for improved estimation of sparse polynomial chaos expansions (Q1986404) (← links)
• A data-driven framework for sparsity-enhanced surrogates with arbitrary mutually dependent randomness (Q1987969) (← links)
• An efficient adaptive forward-backward selection method for sparse polynomial chaos expansion (Q1988232) (← links)
• Adversarial noise attacks of deep learning architectures: stability analysis via sparse-modeled signals (Q1988345) (← links)
• Overcoming the limitations of phase transition by higher order analysis of regularization techniques (Q1991696) (← links)
• Sparse polynomial interpolation: sparse recovery, super-resolution, or Prony? (Q2000529) (← links)
• Maximum correntropy adaptation approach for robust compressive sensing reconstruction (Q2004743) (← links)
• A new linearized split Bregman iterative algorithm for image reconstruction in sparse-view X-ray computed tomography (Q2007198) (← links)
• Learning general sparse additive models from point queries in high dimensions (Q2007617) (← links)
• Compressed data separation via dual frames based split-analysis with Weibull matrices (Q2016924) (← links)
• Sparse identification of nonlinear dynamical systems via reweighted \(\ell_1\)-regularized least squares (Q2021994) (← links)
• Application of ESN prediction model based on compressed sensing in stock market (Q2038120) (← links)
• The global convergence of the nonlinear power method for mixed-subordinate matrix norms (Q2049097) (← links)
• Accelerating the Bayesian inference of inverse problems by using data-driven compressive sensing method based on proper orthogonal decomposition (Q2055173) (← links)
• Memoryless scalar quantization for random frames (Q2059810) (← links)
• Asymptotic analysis for extreme eigenvalues of principal minors of random matrices (Q2075335) (← links)
• Recovering sparse networks: basis adaptation and stability under extensions (Q2077695) (← links)
• Perturbation analysis of \(L_{1-2}\) method for robust sparse recovery (Q2082139) (← links)
• Learning ``best'' kernels from data in Gaussian process regression. With application to aerodynamics (Q2083686) (← links)
• Sparse recovery of sound fields using measurements from moving microphones (Q2106497) (← links)
• Adaptive iterative hard thresholding for least absolute deviation problems with sparsity constraints (Q2108537) (← links)
• Sparse PSD approximation of the PSD cone (Q2118107) (← links)
• Hierarchical isometry properties of hierarchical measurements (Q2118397) (← links)
• A compressed sampling receiver based on modulated wideband converter and a parameter estimation algorithm for fractional bandlimited LFM signals (Q2118689) (← links)
• Derandomized compressed sensing with nonuniform guarantees for \(\ell_1\) recovery (Q2124653) (← links)