: Describe the source files found within the .7z archive (e.g., .mat , .csv , or raw image data).

: List the specific "weights" or "iterative" steps that make this version unique. 2. Methodology (The "NNSWIBR" Logic)

: Document the iteration counts, regularization factors, and initial weights. 4. Results & Analysis

: Define the limitation of current reconstruction methods (e.g., noise, artifacts, or speed).

: Describe the weighting matrix used to prioritize certain data points.

: Detail the dictionary learning or wavelet transform used to reduce data redundancy.

: Check the file properties for a "Last Modified" date to determine which version of the research you are documenting.

Nnswibr.7z Direct

: Describe the source files found within the .7z archive (e.g., .mat , .csv , or raw image data).

: List the specific "weights" or "iterative" steps that make this version unique. 2. Methodology (The "NNSWIBR" Logic) NNSWIBR.7z

: Document the iteration counts, regularization factors, and initial weights. 4. Results & Analysis : Describe the source files found within the

: Define the limitation of current reconstruction methods (e.g., noise, artifacts, or speed). NNSWIBR.7z

: Describe the weighting matrix used to prioritize certain data points.

: Detail the dictionary learning or wavelet transform used to reduce data redundancy.

: Check the file properties for a "Last Modified" date to determine which version of the research you are documenting.