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            "Intended Audience :: Science/Research",
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        "description": "\n[![Build Status](https://secure.travis-ci.org/veeresht/CommPy.svg?branch=master)](https://secure.travis-ci.org/veeresht/CommPy)\n[![Coverage](https://coveralls.io/repos/veeresht/CommPy/badge.svg)](https://coveralls.io/r/veeresht/CommPy)\n[![PyPi](https://badge.fury.io/py/scikit-commpy.svg)](https://badge.fury.io/py/scikit-commpy)\n[![Docs](https://readthedocs.org/projects/commpy/badge/?version=latest)](http://commpy.readthedocs.io/en/latest/?badge=latest)\n\nCommPy\n======\n\nCommPy is an open source toolkit implementing digital communications algorithms\nin Python using NumPy and SciPy.\n\nObjectives\n----------\n- To provide readable and useable implementations of algorithms used in the research, design and implementation of digital communication systems.\n\nAvailable Features\n------------------\nChannel Coding\n--------------\n- Encoder for Convolutional Codes (Polynomial, Recursive Systematic). Supports all rates and puncture matrices.\n- Viterbi Decoder for Convolutional Codes (Hard Decision Output).\n- MAP Decoder for Convolutional Codes (Based on the BCJR algorithm).\n- Encoder for a rate-1/3 systematic parallel concatenated Turbo Code.\n- Turbo Decoder for a rate-1/3 systematic parallel concatenated turbo code (Based on the MAP decoder/BCJR algorithm).\n- Binary Galois Field GF(2^m) with minimal polynomials and cyclotomic cosets.\n- Create all possible generator polynomials for a (n,k) cyclic code.\n- Random Interleavers and De-interleavers.\n- Belief Propagation (BP) Decoder for LDPC Codes.\n\nChannel Models\n--------------\n- SISO Channel with Rayleigh or Rician fading.\n- MIMO Channel with Rayleigh or Rician fading.\n- Binary Erasure Channel (BEC)\n- Binary Symmetric Channel (BSC)\n- Binary AWGN Channel (BAWGNC)\n\nFilters\n-------\n- Rectangular\n- Raised Cosine (RC), Root Raised Cosine (RRC)\n- Gaussian\n\nImpairments\n-----------\n- Carrier Frequency Offset (CFO)\n\nModulation/Demodulation\n-----------------------\n- Phase Shift Keying (PSK)\n- Quadrature Amplitude Modulation (QAM)\n- OFDM Tx/Rx signal processing\n\nSequences\n---------\n- PN Sequence\n- Zadoff-Chu (ZC) Sequence\n\nUtilities\n---------\n- Decimal to bit-array, bit-array to decimal.\n- Hamming distance, Euclidean distance.\n- Upsample\n- Power of a discrete-time signal\n\nFAQs\n----\nWhy are you developing this?\n----------------------------\nDuring my coursework in communication theory and systems at UCSD, I realized that the best way to actually learn and understand the theory is to try and implement ''the Math'' in practice :). Having used Scipy before, I thought there should be a similar package for Digital Communications in Python. This is a start!\n\nWhat programming languages do you use?\n--------------------------------------\nCommPy uses Python as its base programming language and python packages like NumPy, SciPy and Matplotlib.\n\nHow can I contribute?\n---------------------\nImplement any feature you want and send me a pull request :). If you want to suggest new features or discuss anything related to CommPy, please get in touch with me (veeresht@gmail.com).\n\nHow do I use CommPy?\n--------------------\nRequirements/Dependencies\n-------------------------\n- python 2.7 or above\n- numpy 1.10 or above\n- scipy 0.15 or above\n- matplotlib 1.4 or above\n- nose 1.3 or above\n\nInstallation\n------------\n\n- To use the released version on PyPi, use pip or conda to install as follows::\n```\n$ pip install scikit-commpy\n$ conda install -c https://conda.binstar.org/veeresht scikit-commpy\n```\n- To work with the development branch, clone from github and install as follows::\n```\n$ git clone https://github.com/veeresht/CommPy.git\n$ cd CommPy\n$ python setup.py install\n```\n\nCiting CommPy\n-------------\nIf you use CommPy for a publication, presentation or a demo, I request you to please cite CommPy as follows:\n\nVeeresh Taranalli, \"CommPy: Digital Communication with Python, version 0.3.0. Available at https://github.com/veeresht/CommPy\", 2015.\n\nI would also greatly appreciate your feedback if you have found CommPy useful. Just send me a mail: veeresht@gmail.com\n\nFor more details on CommPy, please visit http://veeresht.github.com/CommPy\n\n\n",
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