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Single Channel Blind Source Seperation

  1. Dec 8, 2012 #1
    1. The problem statement, all variables and given/known data
    I am trying to figure out how to do independent component analysis on a single stream of time series data. The ica algorithm comes as part of the it++ package however it is necessary to perform some preprocessing on the time series data as ica works on the premise that the number of observations is at least as large as the number of sources.
    The preprocessing involves constructing a matrix Y that contains the original time series in the 1st column, a lag-1 shifted version of the time series in the 2nd column etc.
    eg.
    Y= 1.0135518 - 0.7113242 - 0.3906069 1.565203
    - 0.7113242 - 0.3906069 1.565203 0.0439317
    - 0.3906069 1.565203 0.0439317 - 1.1656093
    etc.

    My question is what steps are necessary to recover the independent sources after ICA is performed?

    2. Relevant equations



    3. The attempt at a solution
    1. The problem statement, all variables and given/known data



    2. Relevant equations



    3. The attempt at a solution
     
  2. jcsd
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