Metadata-Version: 1.2
Name: scikit-commpy
Version: 0.4.0
Summary: Digital Communication Algorithms with Python
Home-page: http://veeresht.github.com/CommPy
Maintainer: Veeresh Taranalli
Maintainer-email: veeresht@gmail.com
License: BSD 3-Clause
Description: 
        
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        [![Coverage](https://coveralls.io/repos/veeresht/CommPy/badge.svg)](https://coveralls.io/r/veeresht/CommPy)
        [![PyPi](https://badge.fury.io/py/scikit-commpy.svg)](https://badge.fury.io/py/scikit-commpy)
        [![Docs](https://readthedocs.org/projects/commpy/badge/?version=latest)](http://commpy.readthedocs.io/en/latest/?badge=latest)
        
        CommPy
        ======
        
        CommPy is an open source toolkit implementing digital communications algorithms
        in Python using NumPy and SciPy.
        
        Objectives
        ----------
        - To provide readable and useable implementations of algorithms used in the research, design and implementation of digital communication systems.
        
        Available Features
        ------------------
        Channel Coding
        --------------
        - Encoder for Convolutional Codes (Polynomial, Recursive Systematic). Supports all rates and puncture matrices.
        - Viterbi Decoder for Convolutional Codes (Hard Decision Output).
        - MAP Decoder for Convolutional Codes (Based on the BCJR algorithm).
        - Encoder for a rate-1/3 systematic parallel concatenated Turbo Code.
        - Turbo Decoder for a rate-1/3 systematic parallel concatenated turbo code (Based on the MAP decoder/BCJR algorithm).
        - Binary Galois Field GF(2^m) with minimal polynomials and cyclotomic cosets.
        - Create all possible generator polynomials for a (n,k) cyclic code.
        - Random Interleavers and De-interleavers.
        - Belief Propagation (BP) Decoder for LDPC Codes.
        
        Channel Models
        --------------
        - SISO Channel with Rayleigh or Rician fading.
        - MIMO Channel with Rayleigh or Rician fading.
        - Binary Erasure Channel (BEC)
        - Binary Symmetric Channel (BSC)
        - Binary AWGN Channel (BAWGNC)
        
        Filters
        -------
        - Rectangular
        - Raised Cosine (RC), Root Raised Cosine (RRC)
        - Gaussian
        
        Impairments
        -----------
        - Carrier Frequency Offset (CFO)
        
        Modulation/Demodulation
        -----------------------
        - Phase Shift Keying (PSK)
        - Quadrature Amplitude Modulation (QAM)
        - OFDM Tx/Rx signal processing
        
        Sequences
        ---------
        - PN Sequence
        - Zadoff-Chu (ZC) Sequence
        
        Utilities
        ---------
        - Decimal to bit-array, bit-array to decimal.
        - Hamming distance, Euclidean distance.
        - Upsample
        - Power of a discrete-time signal
        
        FAQs
        ----
        Why are you developing this?
        ----------------------------
        During 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!
        
        What programming languages do you use?
        --------------------------------------
        CommPy uses Python as its base programming language and python packages like NumPy, SciPy and Matplotlib.
        
        How can I contribute?
        ---------------------
        Implement 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).
        
        How do I use CommPy?
        --------------------
        Requirements/Dependencies
        -------------------------
        - python 2.7 or above
        - numpy 1.10 or above
        - scipy 0.15 or above
        - matplotlib 1.4 or above
        - nose 1.3 or above
        
        Installation
        ------------
        
        - To use the released version on PyPi, use pip or conda to install as follows::
        ```
        $ pip install scikit-commpy
        $ conda install -c https://conda.binstar.org/veeresht scikit-commpy
        ```
        - To work with the development branch, clone from github and install as follows::
        ```
        $ git clone https://github.com/veeresht/CommPy.git
        $ cd CommPy
        $ python setup.py install
        ```
        
        Citing CommPy
        -------------
        If you use CommPy for a publication, presentation or a demo, I request you to please cite CommPy as follows:
        
        Veeresh Taranalli, "CommPy: Digital Communication with Python, version 0.3.0. Available at https://github.com/veeresht/CommPy", 2015.
        
        I would also greatly appreciate your feedback if you have found CommPy useful. Just send me a mail: veeresht@gmail.com
        
        For more details on CommPy, please visit http://veeresht.github.com/CommPy
        
Platform: UNKNOWN
Classifier: Development Status :: 1 - Planning
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Telecommunications Industry
Classifier: Operating System :: Unix
Classifier: Programming Language :: Python
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Software Development
