Chapter on real-time signal processing using numerical Python

Discussion in 'Python' started by Johannes Nix, Apr 27, 2008.

  1. Johannes Nix

    Johannes Nix Guest

    Hi,

    this might be of interest for people who are look for practical
    information on
    doing real-time signal processing, possibly using multiple CPUs, and
    wonder
    whether it's possible to use Python for audio-type worst case
    latencies (around 25 ms).
    I've done that in my PhD work, both with real-time requirements on
    dual-CPU
    64 bit platforms, and with very complex algorithms running on
    multicomputers.

    What I found is that numerical Python is a great environment for such
    tasks. I've used it as well for massively parallel algorithms
    (particle filters) for simulations of auditory scene analysis. What is
    a very
    special advantage is that if you get faster hardware, you can simply
    copy your algorithms to a new system and compile - even if
    it has a different CPU!

    I've documented the approach in my PhD thesis, in Appendix A,
    starting with some thoughts on developments in signal processing
    in the last years. This piece is available online. Title and abstract
    of that
    chapter read as follows:

    --------------------------------------------------------------
    A real-time, script-based, multiprocessing Solution for experimental
    Development of Signal Processing Algorithms

    Evaluation of audio signal processing algorithms on real-time
    platforms has
    unique advantages. However, such environments also used to have the
    disadvantage
    of requiring expensive hardware, and tedious work to set them up,
    while providing only a short useful life. This report proposes to
    exploit advances
    in hardware and software development by integrating real-time
    processing
    with script-based explorative development and use of multiprocessing
    hardware.
    The concept was implemented based on standard hardware and open
    source software, and its realization and characteristics are presented
    here. Applications
    of the system for algorithm development and evaluation are described
    briefly.

    --------------------------------------------------------------


    Here is the download link for several paper formats:

    http://medi.uni-oldenburg.de/members/jnix/index.html#thesisdownload

    Alternatively, for ISO A4 paper, use one of these two URLs:

    http://medi.uni-oldenburg.de/download/paper/Nix,Johannes-PhDthesis-2005-ISO-A4-format.pdf
    http://docserver.bis.uni-oldenburg.de/publikationen/dissertation/2006/nixloc05/nixloc05.html
    (for that paper size, this are the PDF pages 155 - 163)



    If you want to cite the chapter, e.g. when doing advocacy for
    scientific
    computing using SciPy, please do this as follows:

    Nix, Johannes (2005), "A real-time, script-based, multiprocessing
    Solution for experimental
    Development of Signal Processing Algorithms", in: Localization and
    Separation of Concurrent Talkers Based on Principles of Auditory Scene
    Analysis and Multi-Dimensional Statistical Methods, Appendix A, Ph.D.
    thesis, Universit├Ąt Oldenburg, Germany.


    Also, I am currently looking for interesting further work
    opportunities
    or contracts in the domain of scientific computing and statistical
    estimation.
    If you know some interesting position, don't hesistate to contact me.

    Kind regards,

    Johannes


    --
    Dr. Johannes Nix

    Energy & Meteo Systems GmbH
    Research & Development of windpower forecasts
    Bremen, Germany
    Phone: + 49 421 8963914
     
    Johannes Nix, Apr 27, 2008
    #1
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