Dequantizing Compressed Sensing: When Oversampling and Non-Gaussian Constraints Combine

DOI10.1109/TIT.2010.2093310zbMath1366.94106OpenAlexW2128804753MaRDI QIDQ5281147

Jalal Fadili, David K. Hammond, Laurent Jacques

Publication date: 27 July 2017

Published in: IEEE Transactions on Information Theory (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1109/tit.2010.2093310

Mathematics Subject Classification ID

Signal theory (characterization, reconstruction, filtering, etc.) (94A12) Coding and information theory (compaction, compression, models of communication, encoding schemes, etc.) (aspects in computer science) (68P30) Sampling theory in information and communication theory (94A20)

Related Items

A scheme for distributed compressed video sensing based on hypothesis set optimization techniques ⋮ Error bounds for consistent reconstruction: random polytopes and coverage processes ⋮ A primal-dual homotopy algorithm for \(\ell _{1}\)-minimization with \(\ell _{\infty }\)-constraints ⋮ Quantization and Compressive Sensing ⋮ Stable and robust $\ell_p$-constrained compressive sensing recovery via robust width property ⋮ Quantization of compressive samples with stable and robust recovery ⋮ Robust signal recovery via \(\ell_{1-2}/ \ell_p\) minimization with partially known support ⋮ Representation and coding of signal geometry ⋮ Time for dithering: fast and quantized random embeddings via the restricted isometry property ⋮ Sobolev duals for random frames and \(\varSigma \varDelta \) quantization of compressed sensing measurements ⋮ Democracy in action: quantization, saturation, and compressive sensing ⋮ Proximal methods for the latent group lasso penalty ⋮ Signal separation under coherent dictionaries and \(\ell_p\)-bounded noise ⋮ Compressive optical deflectometric tomography: a constrained total-variation minimization approach ⋮ Mathematics of Analog‐to‐Digital Conversion ⋮ Robust dequantized compressive sensing ⋮ Analysis of Quantization Noise Spectrum in Signal Reconstruction ⋮ Memoryless scalar quantization for random frames ⋮ One-Bit Compressed Sensing by Linear Programming ⋮ Quantized compressed sensing for random circulant matrices ⋮ Iteratively consistent one-bit phase retrieval