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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:

http://cdn.makeagif.com/media/4-04-2016/3EFoj2.gif http://cdn.makeagif.com/media/4-04-2016/EiE1qg.gif

Sound coding-decoding example:

Sound Transmission

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)

2- LDPC Images Functions Construction

3- LDPC Sound Functions Construction

version 0.7.3

Contains:

  1. Coding and decoding matrices Generators:
    • Regular parity-check matrix using Callager’s method.

    • Coding Matrix G both non-systematic and systematic.

  2. Coding function adding Additive White Gaussian Noise.

  3. Decoding functions using Probabilistic Decoding (Belief propagation algorithm):
    • Default and full-log BP algorithm.

  4. Images transmission sub-module:
    • Coding and Decoding Grayscale and RGB Images.

  5. Sound transmission sub-module:
    • Coding and Decoding audio files.

  6. 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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