Blind Recovery of Sparse Signals From Subsampled Convolution

Keyphrases

• Blind Deconvolution 100%
• Blind Recovery 100%
• Conic Constraints 50%
• Deconvolution Problem 50%
• Dictionary Model 50%
• Empirical Performance 50%
• High Probability 50%
• Ill-posedness 50%
• Information-theoretic Bounds 50%
• Iterative Algorithm 100%
• Measurement Model 50%
• Near-optimal 50%
• Numerical Results 50%
• Optimal Sample 50%
• Parameter Values 50%
• Performance Guarantee 100%
• Projection Step 100%
• Random Dictionaries 50%
• Rate Scaling 50%
• Robust Recovery 50%
• Sample Complexity 50%
• Solution-focused 50%
• Sparse Signal 100%
• Sparsity 50%
• Sparsity Model 100%
• Spectral Flatness 50%
• Unknown Signal 50%

Computer Science

• Blind Deconvolution 66%
• Convolution 100%
• Iterative Algorithm 66%
• Parameter Value 33%
• Performance Guarantee 66%
• Sparsity 100%
• Spectral Flatness 33%

Mathematics

• Convolution 100%
• Identifiability 33%
• Posedness 33%
• Probability 33%
• Problem Solution 33%