Nonlinear Independent Component Analysis by Self-Organizing Maps

  title={Nonlinear Independent Component Analysis by Self-Organizing Maps},
  author={Petteri Pajunen},
In neural blind source separation most approaches have considered the linear source separation problem where the input data consist of unknown linear mixtures of unknown independent source signals. The solution is a linear transformation which makes the output vector components statistically independent. More generally we can consider nonlinear mixtures of sources. Then we can try to separate the sources by constructing mappings that make the components of the output vectors independent. We… CONTINUE READING
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