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An Introduction to Compressed Sensing (Q3296174)

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Language	Label	Description	Also known as
English	An Introduction to Compressed Sensing	scientific article

Statements

scholarly article

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An Introduction to Compressed Sensing (English)

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Applied and Numerical Harmonic Analysis

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publication date

7 July 2020

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zbMATH Keywords

compressed sensing, sparsity

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signal recovery

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conic integral geometry

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describes a project that uses

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MaRDI profile type

MaRDI publication profile

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full work available at URL

https://doi.org/10.1007/978-3-319-73074-5_1

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Geometry of log-concave ensembles of random matrices and approximate reconstruction

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Restricted isometry property of matrices with independent columns and neighborly polytopes by random sampling

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Living on the edge: phase transitions in convex programs with random data

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Uniform recovery of fusion frame structured sparse signals

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Discrete uncertainty principles and sparse signal processing

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A simple proof of the restricted isometry property for random matrices

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A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems

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NESTA: A Fast and Accurate First-Order Method for Sparse Recovery

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Atomic Norm Denoising With Applications to Line Spectral Estimation

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Sparse Recovery From Combined Fusion Frame Measurements

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Quantization and Compressive Sensing

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An Improved Estimate in the Restricted Isometry Problem

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The Dantzig selector: statistical estimation when \(p\) is much larger than \(n\). (With discussions and rejoinder).

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The restricted isometry property and its implications for compressed sensing

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New tight frames of curvelets and optimal representations of objects with piecewise <i>C</i><sup>2</sup> singularities

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Near-ideal model selection by \(\ell _{1}\) minimization

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Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information

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Stable signal recovery from incomplete and inaccurate measurements

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Decoding by Linear Programming

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Near-Optimal Signal Recovery From Random Projections: Universal Encoding Strategies?

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Introduction to Compressed Sensing and Sparse Filtering

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Introduction to Finite Frame Theory

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The convex geometry of linear inverse problems

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Restricted Isometry of Fourier Matrices and List Decodability of Random Linear Codes

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Compressed sensing and best 𝑘-term approximation

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Subspace Pursuit for Compressive Sensing Signal Reconstruction

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An elementary proof of a theorem of Johnson and Lindenstrauss

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CVXPY: A Python-Embedded Modeling Language for Convex Optimization

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On the Gap Between Restricted Isometry Properties and Sparse Recovery Conditions

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Compressed sensing

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Optimally sparse representation in general (nonorthogonal) dictionaries via ℓ <sup>1</sup> minimization

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Stable recovery of sparse overcomplete representations in the presence of noise

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Accurate Prediction of Phase Transitions in Compressed Sensing via a Connection to Minimax Denoising

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Observed universality of phase transitions in high-dimensional geometry, with implications for modern data analysis and signal processing

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Sparse and Redundant Representations

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Gabor analysis and algorithms. Theory and applications

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Compressive Sensing

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Flavors of Compressive Sensing

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The Gelfand widths of \(\ell_p\)-balls for \(0 < p \leq 1\)

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A mathematical introduction to compressive sensing

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Corrupted Sensing: Novel Guarantees for Separating Structured Signals

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Theta Bodies for Polynomial Ideals

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The Restricted Isometry Property of Subsampled Fourier Matrices

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Extensions of Lipschitz mappings into a Hilbert space

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Oracle inequalities in empirical risk minimization and sparse recovery problems. École d'Été de Probabilités de Saint-Flour XXXVIII-2008.

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Suprema of Chaos Processes and the Restricted Isometry Property

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Shearlets. Multiscale analysis for multivariate data.

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A Simple Tool for Bounding the Deviation of Random Matrices on Geometric Sets

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From Denoising to Compressed Sensing

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Blind Multiband Signal Reconstruction: Compressed Sensing for Analog Signals

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Sparse Approximate Solutions to Linear Systems

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Learning Theory

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New constructions of RIP matrices with fast multiplication and fewer rows

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Introductory lectures on convex optimization. A basic course.

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Robust 1-bit Compressed Sensing and Sparse Logistic Regression: A Convex Programming Approach

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The Generalized Lasso With Non-Linear Observations

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Vector Approximate Message Passing

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Compressed Sensing and Redundant Dictionaries

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On sparse reconstruction from Fourier and Gaussian measurements

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Compressed Sensing Off the Grid

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Sparsity and Smoothness Via the Fused Lasso

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The Lasso problem and uniqueness

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The Computational Complexity of the Restricted Isometry Property, the Nullspace Property, and Related Concepts in Compressed Sensing

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Greed is Good: Algorithmic Results for Sparse Approximation

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Probing the Pareto Frontier for Basis Pursuit Solutions

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Estimation in High Dimensions: A Geometric Perspective

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Lower bounds on the maximum cross correlation of signals (Corresp.)

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Sparse Reconstruction by Separable Approximation

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Necessary and sufficient conditions of solution uniqueness in 1-norm minimization

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Identifiers

zbMATH Open document ID

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10.1007/978-3-319-73074-5_1

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Mathematics Subject Classification ID

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zbMATH DE Number

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Sitelinks

Mathematics(1 entry)

mardi Publication:3296174

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