The goal of the ``Fractional component analysis'' proposed in this paper is to analyze the observed signal generated by the linear mixing process of unknown fractional component signals. Based on simple assumptions on the probability distributions of component signals and mixing fractions, we derive a new type of distribution, which we call ``mixed distribution,'' and characterize this model in terms of moments and cumulants. Its higher-order cumulants indicate that it is in fact either super-gaussian or sub-gaussian even if the distribution of component signals are gaussian. Finally we show methods for recovering fractional components from the observed signal.

      @InProceedings{ k:ibis01,
      author = {Asanobu KITAMOTO},
      title = {FCA: The Fractional Component Analysis},
      booktitle = {Proceedings of the 4th Workshop on Information-Based Induction Sciences (IBIS 2001)},
      pages = {297-302},
      year = 2001,
      month = 8,
      doi = {},
      note = {},
      }