: Explain the physical constraints (e.g., pixel intensity cannot be negative).
: Document the iteration counts, regularization factors, and initial weights. 4. Results & Analysis
: Use PSNR (Peak Signal-to-Noise Ratio) or SSIM (Structural Similarity Index) to quantify performance. NNSWIBR.7z
: Explain how the NNSWIBR algorithm improves upon standard Sparse Representation or Back-Projection.
: Check the file properties for a "Last Modified" date to determine which version of the research you are documenting. : Explain the physical constraints (e
: Define the limitation of current reconstruction methods (e.g., noise, artifacts, or speed).
: Detail the dictionary learning or wavelet transform used to reduce data redundancy. Results & Analysis : Use PSNR (Peak Signal-to-Noise
: Look for a README.txt , main.m (MATLAB), or .py (Python) script. These often contain the mathematical formulas needed for your "Methodology" section.