Simulation of Low Density Parity Check Codes ldpc
Project description
version 0.7.3
In Brief:
Generates coding and decoding matrices.
Probabilistic decoding: Belief Propagation algorithm.
Images transmission simulation (channel model: AGWN).
Sound transmission simulation (channel model :AGWN).
Image coding-decoding example:
Sound coding-decoding example:
Installation
>From pip:
$ pip install --upgrade pyldpc
Tutorials:
Jupyter notebooks:
Many changes in tutorials in v.0.7.3
Users’ Guide:
1- LDPC Coding-Decoding Simulation
2- Images Coding-DecodingTutorial
3- Sound Coding-DecodingTutorial
4- LDPC Matrices Construction Tutorial
For LDPC construction details:
1- pyLDPC Construction(French)
version 0.7.3
Contains:
- Coding and decoding matrices Generators:
Regular parity-check matrix using Callager’s method.
Coding Matrix G both non-systematic and systematic.
Coding function adding Additive White Gaussian Noise.
- Decoding functions using Probabilistic Decoding (Belief propagation algorithm):
Default and full-log BP algorithm.
- Images transmission sub-module:
Coding and Decoding Grayscale and RGB Images.
- Sound transmission sub-module:
Coding and Decoding audio files.
Compatibility numpy ndarrays <=> scipy sparse csr format.
What’s new:
Image and Sound modules adapt data to any LDPC code: conditions on matrices’ size are no longer needed.
Use of large matrices (csr) in sound transmission sub-module.
Bug in using full rank parity check matrices fixed.
In the upcoming versions:
Library of ready-to-use large matrices (csr).
Text Transmission functions.
Contact:
Please contact hicham.janati@ensae.fr for any bug encountered / any further information.
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