Yagle, Andrew E. - Department of Electrical Engineering and Computer Science, University of Michigan

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Yagle, Andrew E. - Department of Electrical Engineering and Computer Science, University of Michigan

Non-Iterative Sparse Image Reconstruction from a Few 2-D DFT Frequency Values
Non-Iterative Phase Retrieval from Magnitude of Complex-Valued Compact-Support Images
Closed-Form Reconstruction of Sparse Signals from Limited Numbers of Irregular Frequencies
Fast Non-Iterative Image Reconstruction from Irregular 2-D DFT Frequency Samples
A simple non-iterative algorithm for 2-D tomography with unknown view angles
Deconvolution of Sparse Signals and Images from Noisy Partial Data using MUSIC
Non-Iterative Computation of Sparsifiable Solutions to Underdetermined Kronecker
Location of Non-Zeros in Sparse Solutions of Underdetermined Linear Systems of Equations
Coordinate Descent for Sparse Solutions of Underdetermined Linear Systems of Equations
Shrinkage Without Thresholding: 1 Norm Minimization using the Landweber Iteration
Fast 2-D and 3-D blind deconvolution of bandlimited images from even point-spread
21 Things I've Learned About Teaching21 Things I've Learned About Teaching P f A d E Y lP f A d E Y lProfessor Andrew E. YagleProfessor Andrew E. Yagle
A Non-Iterative Procedure for Sparse Solutions to Linear Equations with Bandlimited Rows
Regularized Matrix Computations Andrew E. Yagle
Limited Angle Tomography of Sparse Images from Noisy Data using TLS MUSIC Algorithm
A New Algorithm for the Nearest Singular Toeplitz Matrix to a Given Toeplitz Matrix
A Non-Iterative Procedure for Computing Sparse and Sparsifiable Solutions to Slightly
Recovery of K-Sparse Non-Negative Signals From K DFT Values and Their Conjugates
Non-Iterative Valid Blind Deconvolution of Sparsifiable Images using an Inverse Filter
Non-Iterative Superresolution Phase Retrieval of Sparse Images without Support Constraints
Blind Deconvolution and Toeplitzation Using Iterative Null-Space and Rank-One Projections
Non-Iterative Reweighted-Norm Least-Squares Local 0 Minimization for Sparse Solutions to
Divide-and-Conquer Image Reconstruction from Irregular DTFT Samples using Subband
Discrete Tomography as 2-D Phase Retrieval Solved Using Hybrid Input-Output Algorithm
NonNon--Iterative Reconstruction ofIterative Reconstruction of Sparse Images from Limited DataSparse Images from Limited DataSparse Images from Limited DataSparse Images from Limited Data
New Atomicity-Exploiting Algorithms for Super-Resolution X-Ray Crystallography
Single-system multiple-output (SSMO) sparse solution mapped to single-output