Spectral Methods for Passive Imaging: Nonasymptotic Performance and Robustness
From MaRDI portal
Publication:5230405
DOI10.1137/17M1143599zbMath1428.94028arXiv1708.04343WikidataQ129244171 ScholiaQ129244171MaRDI QIDQ5230405
Justin Romberg, Kiryung Lee, Felix Krahmer
Publication date: 22 August 2019
Published in: SIAM Journal on Imaging Sciences (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1708.04343
Signal theory (characterization, reconstruction, filtering, etc.) (94A12) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08) Random matrices (algebraic aspects) (15B52)
Related Items
Exact Recovery of Multichannel Sparse Blind Deconvolution via Gradient Descent, Sparse power factorization: balancing peakiness and sample complexity, Non-asymptotic behavior of the spectrum of the sinc-kernel operator and related applications
Cites Work
- Unnamed Item
- Unnamed Item
- A mathematical introduction to compressive sensing
- Nuclear-norm penalization and optimal rates for noisy low-rank matrix completion
- User-friendly tail bounds for sums of random matrices
- Hanson-Wright inequality and sub-Gaussian concentration
- Inequalities of Bernstein-Jackson-type and the degree of compactness of operators in Banach spaces
- Block diagonally dominant matrices and generalizations of the Gerschgorin circle theorem
- Recent developments in blind channel equalization: From cyclostationarity to subspaces
- Random perturbation of low rank matrices: improving classical bounds
- Duality of metric entropy
- Adaptive estimation of a quadratic functional by model selection.
- Rapid, robust, and reliable blind deconvolution via nonconvex optimization
- Noncommutative Bennett and Rosenthal inequalities
- Blind identification of multichannel FIR blurs and perfect image restoration
- Suprema of Chaos Processes and the Restricted Isometry Property
- Identifiability in Blind Deconvolution With Subspace or Sparsity Constraints
- Blind Deconvolution Using Convex Programming
- Blind Recovery of Sparse Signals From Subsampled Convolution
- Passive Synthetic Aperture Imaging
- Optimal Sample Complexity for Blind Gain and Phase Calibration
- Self-Calibration and Bilinear Inverse Problems via Linear Least Squares
- Optimal Injectivity Conditions for Bilinear Inverse Problems with Applications to Identifiability of Deconvolution Problems
- Identifiability and Stability in Blind Deconvolution Under Minimal Assumptions
- MCA: A Multichannel Approach to SAR Autofocus
- Singular vectors under random perturbation
- The Rotation of Eigenvectors by a Perturbation. III