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| credits = 3
| credits = 3
| credit_structure = 3-0-0
| credit_structure = 3-0-0
| pre_requisites = COL106 OR Equivalent
| pre_requisites = [[COL106]] OR Equivalent
| overlaps =  
| overlaps =  
}}
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Latest revision as of 16:26, 14 April 2026

COL722
Introduction to Compressed Sensing
Credits 3
Structure 3-0-0
Pre-requisites COL106 OR Equivalent
Overlaps

COL722 : Introduction to Compressed Sensing

Sparsity, L1 minimization, Sparse regression, deterministic and probabilistic approaches to compressed sensing, restricted isometry property and its application in sparse recovery, robustness in the presence of noise, algorithms for compressed sensing. Applications in magnetic resonance imaging (MRI), applications in analog-to-digital conversion, low-rank matrix recovery, applications in image reconstruction.