: Describe the weighting matrix used to prioritize certain data points.
: Explain how the NNSWIBR algorithm improves upon standard Sparse Representation or Back-Projection. NNSWIBR.7z
: Detail the dictionary learning or wavelet transform used to reduce data redundancy. : Describe the weighting matrix used to prioritize
: List the specific "weights" or "iterative" steps that make this version unique. 2. Methodology (The "NNSWIBR" Logic) NNSWIBR.7z
: Define the limitation of current reconstruction methods (e.g., noise, artifacts, or speed).
If you are having trouble accessing the contents to write the paper: : Use 7-Zip or WinZip to open NNSWIBR.7z .