version 0.7.5
- 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:
Sound Transmission
From pip:
$ pip install --upgrade pyldpc
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)
2- LDPC Images Functions Construction
3- LDPC Sound Functions Construction
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:
- Python 2 compatibility
- Library of ready-to-use large matrices (csr).
- Text Transmission functions.
Please contact [email protected] for any bug encountered / any further information.