Examples of Noisy Signal Reconstruction Using Compressed Sensing with Two L1-Norm Criteria

This demonstration presents two examples of noisy signal reconstruction using compressed sensing under l1-norm optimization criteria. Both examples employ DCT matrices as sparse bases, while utilizing identity matrices and random matrices as measurement matrices respectively. The implementation includes detailed step-by-step procedures and usage instructions, making it suitable for beginners learning compressed sensing methodologies. The code demonstrates signal recovery through convex optimization techniques with noise handling capabilities.