Simulation of Low Density Parity Check Codes
Project description
version 0.4
In Brief:
Generates coding and decoding matrices.
Probabilistic decoding: Belief Propagation algorithm.
Images transmission simulation (AGWN):
e.g of decoding:
Tutorials:
Jupyter notebooks:
For LDPC construction details: pyLDPC construction
For Images coding/decoding Tutorial: Images Tutorial
version 0.4:
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 BP algorithm.
Full-log BP algorithm.
- Images transmission sub-module:
Coding and Decoding Grayscale Images.
Coding and Decoding RGB Images.
What’s new:
Images sub-module
Using Signal-Noise-Ratio (SNR) instead of AWGN’s variance.
In the upcoming versions:
In the upcoming versions:
Irregular Parity Check Matrices.
Text Transmission functions.
Sound Transmission functions.
Contact:
Please contact hicham.janati@ensae.fr for any bug encountered / any further information.
Project details
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