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View Code? Open in Web Editor NEWRate adaptive LDPC based solutions for distributed source coding
License: GNU General Public License v3.0
Rate adaptive LDPC based solutions for distributed source coding
License: GNU General Public License v3.0
The frame error rates obtained using the decoding algorithm currently provided in this repository is slightly worse than what is available in AFF3CT.
This issue should investigate reasons for this and improve the decoding performance.
The code class is templated on types to store indices defining the code. If these types are chosen too small (e.g. uint8) for the arrays used to define the code, it may be instantiated incorrectly.
Is it easy to change these to python? I want to use distributed source coding to compress deep learning model parameters.
I really appreciate your repository because it is very helpful for my work. I have a question about creating new LDPC codes.
You provided some codes in .cscmat format. I would like to make more codes and compare them. Do you have an idea how can I do it?
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